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++GENERAL +
+
+
++General Concepts +
+chevron is a collection of functions to creates tables,
+listings, and graphs following Roche standards for clinical trials
+reporting. After loading the R packages and the trial data, the output
+is to be created by the main function run(...) . Two
+arguments object= and adam_db= are always
+expected in the function. object= specifies which Roche
+Standard Template ID to use. adam_db= specifies the input
+dataset. Other mandatory and optional arguments within the
+run function vary depending on which template ID is called.
+To access which arguments are required and what functions are used in
+each template, simply try ?template
+(e.g. ?aet01) to see more detailed descriptions and
+instructions.
+
++1. Input dataset and dataset names +
+The input dataset expected by the argument adam_db= in
+the run(...) function is a collection of ADaM
+datasets as a list object. Each ADaM dataset is expected to
+be an object of data frame. If the ADaM datasets are read
+in individually, user will need to combine them into a list object and
+provide the name of the list to adam_db=. Also, each
+element in the list are expected to have corresponding ADaM
+dataset names. Conventional ADaM dataset names, including
+adsl,adex, adae,
+adlb,advs,adeg,adcm,admh,adrs,
+and adtte, can be picked up by chevron with
+one exception.
+
++2. Expected variables in input analysis +dataset +
+By default, chevron does not pull any subject-level
+information from either adsl or adsub and
+merge into the analysis dataset in the underlying preprocessing steps.
+The analysis dataset fed into adam_db= is expected to have
+all variables required for analysis available.
+
+
+
+
++3. Character vs Factor +
+In the output generation, we often need to specify a particular
+sorting order of a variable at the time of display. In
+chevron, a character variable needs to be factorized with
+pre-specified levels to display in order. When encountering cases, for
+instance, "ARM A" has an Asian group only while
+"ARM B" has both Asian and White groups, it is not able to
+produce outputs like the demographic table unless "RACE" is
+factorized to provide access to the same level attribute of the variable
+"RACE" after the arm split. It is noted that the feature
+comes from rtables instead of chevron.
+proc_data <- syn_data
+proc_data$adsl <- proc_data$adsl %>%
+ mutate(RACE = case_when(
+ ARMCD == "ARM A" ~ "ASIAN",
+ ARMCD == "ARM B" & !.data$RACE %in% c("WHITE", "ASIAN") ~ "ASIAN",
+ TRUE ~ RACE
+ ))Having "RACE" as a character variable rather than a
+factor leads to error message showing up as “Error: Error applying
+analysis function (var - RACE): Number of rows generated by analysis
+function do not match across all columns,” and it is recommended to
+convert analysis variable "RACE" to a factor.
+run(dmt01, proc_data)To resolve this issue, simply try factorizing the variable
+"RACE":
+proc_data$adsl$RACE <- as.factor(proc_data$adsl$RACE)
+run(dmt01, proc_data)
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> ————————————————————————————————————————————————————————————————————————————————————————————
+#> Age (yr)
+#> n 15 15 15 45
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4) 34.3 (7.3)
+#> Median 31.0 35.0 35.0 34.0
+#> Min - Max 24 - 40 24 - 57 24 - 49 24 - 57
+#> Age Group
+#> n 15 15 15 45
+#> <65 15 (100%) 15 (100%) 15 (100%) 45 (100%)
+#> Sex
+#> n 15 15 15 45
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%) 15 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%) 30 (66.7%)
+#> Ethnicity
+#> n 15 15 15 45
+#> HISPANIC OR LATINO 2 (13.3%) 0 0 2 (4.4%)
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%) 41 (91.1%)
+#> NOT REPORTED 0 0 2 (13.3%) 2 (4.4%)
+#> RACE
+#> n 15 15 15 45
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 0 1 (6.7%) 1 (2.2%)
+#> ASIAN 15 (100%) 13 (86.7%) 8 (53.3%) 36 (80.0%)
+#> BLACK OR AFRICAN AMERICAN 0 0 4 (26.7%) 4 (8.9%)
+#> WHITE 0 2 (13.3%) 2 (13.3%) 4 (8.9%)
+
+
++4. Testing the codes for plot generation +
+The run function when calling a Graphics Template ID
+returns a gTree object which will be used in the downstream
+workflow for output generation. There are two alternative approaches to
+rendering the plot: (1) having draw = TRUE in the
+run function to enable the generated plot to be
+automatically created and viewed via the Plots tab, and (2)
+calling the function grid.draw from the package
+grid which can be utilized to render the plot for viewing
+and testing purpose. See example below:
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+
+# method 1
+run(kmg01, proc_data, dataset = "adtte", draw = TRUE)
+
+# method 2
+res <- run(kmg01, proc_data, dataset = "adtte")
+grid::grid.newpage()
+grid::grid.draw(res)
+
++General Control Arguments +
+
+
+1.
+
+
+1. lbl_overall: Column of Total
+
+The generic argument lbl_overall controls whether the
+column of total will be produced or not. lbl_overall = NULL
+suppresses the total, lbl_overall = "All Patients" produces
+the total.
+
+
++2. Column counts: N=xxx +
+Column counts are displayed by default. There is no generic argument
+controlling whether the count of unique number of subjects (N=xxx) will
+be displayed in the column header or not. Users are allowed to customize
+the display of N=xxx by forcing
+display_columncounts = FALSE to wipe column counts away
+during the postprocessing (with precautions and it is not
+recommended).
+tbl <- run(dmt01, syn_data) # table with column counts
+tbl@col_info@display_columncounts <- FALSE
+tbl # no column counts now
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> ————————————————————————————————————————————————————————————————————————————————————————————
+#> Age (yr)
+#> n 15 15 15 45
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4) 34.3 (7.3)
+#> Median 31.0 35.0 35.0 34.0
+#> Min - Max 24 - 40 24 - 57 24 - 49 24 - 57
+#> Age Group
+#> n 15 15 15 45
+#> <65 15 (100%) 15 (100%) 15 (100%) 45 (100%)
+#> Sex
+#> n 15 15 15 45
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%) 15 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%) 30 (66.7%)
+#> Ethnicity
+#> n 15 15 15 45
+#> HISPANIC OR LATINO 2 (13.3%) 0 0 2 (4.4%)
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%) 41 (91.1%)
+#> NOT REPORTED 0 0 2 (13.3%) 2 (4.4%)
+#> RACE
+#> n 15 15 15 45
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 2 (13.3%) 1 (6.7%) 3 (6.7%)
+#> ASIAN 8 (53.3%) 10 (66.7%) 8 (53.3%) 26 (57.8%)
+#> BLACK OR AFRICAN AMERICAN 4 (26.7%) 1 (6.7%) 4 (26.7%) 9 (20.0%)
+#> WHITE 3 (20.0%) 2 (13.3%) 2 (13.3%) 7 (15.6%)
+
++TABLES +
+
+
+Safety Summary (
+
+
+Safety Summary (AET01)
+
+
+
+
++1. Safety Summary +
+The aet01 template produces the
+standard safety summary.
+run(aet01, syn_data, arm_var = "ARM")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one AE 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of AEs 58 59 99
+#> Total number of deaths 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> Total number of patients withdrawn from study due to an AE 0 0 1 (6.7%)
+#> Total number of patients with at least one
+#> AE with fatal outcome 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> Serious AE 12 (80.0%) 12 (80.0%) 11 (73.3%)
+#> Serious AE leading to withdrawal from treatment 0 0 2 (13.3%)
+#> Serious AE leading to dose modification/interruption 4 (26.7%) 3 (20.0%) 4 (26.7%)
+#> Related Serious AE 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> AE leading to withdrawal from treatment 2 (13.3%) 3 (20.0%) 3 (20.0%)
+#> AE leading to dose modification/interruption 6 (40.0%) 9 (60.0%) 11 (73.3%)
+#> Related AE 11 (73.3%) 10 (66.7%) 13 (86.7%)
+#> Related AE leading to withdrawal from treatment 0 3 (20.0%) 0
+#> Related AE leading to dose modification/interruption 1 (6.7%) 4 (26.7%) 9 (60.0%)
+#> Severe AE (at greatest intensity) 11 (73.3%) 10 (66.7%) 12 (80.0%)
+
+
++2. Safety Summary with Modified Rows +
+Analyses under “Total number of patients with at least one” can be
+removed, added, or modified by editing the parameter
+anl_vars. An analysis here is an abbreviated name of the
+analysis of interest, and supported by a variable in ADAE
+derived under the condition of interest. The defined analyses currently
+include "FATAL", "SER", "SERWD",
+"SERDSM", "RELSER", "WD",
+"DSM", "REL", "RELWD",
+"RELDSM", and "SEV". When modification is
+made, analyses must all be listed in the argument anl_vars.
+The example below shows adding the customized analysis
+"RELCTC35".
+proc_data <- syn_data
+proc_data$adae <- proc_data$adae %>%
+ filter(.data$ANL01FL == "Y") %>%
+ mutate(
+ FATAL = with_label(.data$AESDTH == "Y", "AE with fatal outcome"),
+ SER = with_label(.data$AESER == "Y", "Serious AE"),
+ SEV = with_label(.data$ASEV == "SEVERE", "Severe AE (at greatest intensity)"),
+ REL = with_label(.data$AREL == "Y", "Related AE"),
+ WD = with_label(.data$AEACN == "DRUG WITHDRAWN", "AE leading to withdrawal from treatment"),
+ DSM = with_label(
+ .data$AEACN %in% c("DRUG INTERRUPTED", "DOSE INCREASED", "DOSE REDUCED"),
+ "AE leading to dose modification/interruption"
+ ),
+ SERWD = with_label(.data$SER & .data$WD, "Serious AE leading to withdrawal from treatment"),
+ SERDSM = with_label(.data$SER & .data$DSM, "Serious AE leading to dose modification/interruption"),
+ RELSER = with_label(.data$SER & .data$REL, "Related Serious AE"),
+ RELWD = with_label(.data$REL & .data$WD, "Related AE leading to withdrawal from treatment"),
+ RELDSM = with_label(.data$REL & .data$DSM, "Related AE leading to dose modification/interruption"),
+ CTC35 = with_label(.data$ATOXGR %in% c("3", "4", "5"), "Grade 3-5 AE"),
+ CTC45 = with_label(.data$ATOXGR %in% c("4", "5"), "Grade 4/5 AE"),
+ RELCTC35 = with_label(.data$ATOXGR %in% c("3", "4", "5") & .data$AEREL == "Y", "Related Grade 3-5")
+ )
+
+proc_data$adsl <- proc_data$adsl %>%
+ mutate(DCSREAS = reformat(.data$DCSREAS, missing_rule))
+
+run(aet01, proc_data, anl_vars = list(safety_var = c("FATAL", "SER", "RELSER", "RELCTC35")), auto_pre = FALSE)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one AE 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of AEs 58 59 99
+#> Total number of deaths 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> Total number of patients withdrawn from study due to an AE 0 0 1 (6.7%)
+#> Total number of patients with at least one
+#> AE with fatal outcome 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> Serious AE 12 (80.0%) 12 (80.0%) 11 (73.3%)
+#> Related Serious AE 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> Related Grade 3-5 11 (73.3%) 10 (66.7%) 12 (80.0%)
+
+Safety Summary (Adverse Events of Special Interest)
+(
+
+
+Safety Summary (Adverse Events of Special Interest)
+(AET01_AESI)
+
+
+
+
++1. Safety Summary (Adverse Events of Special +Interest) +
+The aet01_aesi template produces the
+standard safety summary for adverse events of special interest.
+run(aet01_aesi, syn_data)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one AE 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of AEs 58 59 99
+#> Total number of patients with at least one AE by worst grade
+#> Grade 1 0 1 (6.7%) 1 (6.7%)
+#> Grade 2 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> Grade 3 1 (6.7%) 2 (13.3%) 1 (6.7%)
+#> Grade 4 3 (20.0%) 2 (13.3%) 2 (13.3%)
+#> Grade 5 (fatal outcome) 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> Total number of patients with study drug withdrawn due to AE 2 (13.3%) 3 (20.0%) 3 (20.0%)
+#> Total number of patients with dose modified/interrupted due to AE 6 (40.0%) 9 (60.0%) 11 (73.3%)
+#> Total number of patients with treatment received for AE 10 (66.7%) 10 (66.7%) 14 (93.3%)
+#> Total number of patients with all non-fatal AEs resolved 9 (60.0%) 10 (66.7%) 12 (80.0%)
+#> Total number of patients with at least one unresolved or ongoing non-fatal AE 10 (66.7%) 9 (60.0%) 14 (93.3%)
+#> Total number of patients with at least one serious AE 12 (80.0%) 12 (80.0%) 11 (73.3%)
+#> Total number of patients with at least one related AE 11 (73.3%) 10 (66.7%) 13 (86.7%)
+
+
++2. Safety Summary (Adverse Events of Special Interest) +(optional lines) +
+Additional analyses can be added with the argument
+aesi_vars, please type ?aet01_aesi in console
+to find out the list of all pre-defined optional analyses in the
+HELP.
+run(aet01_aesi, syn_data, aesi_vars = c("RESLWD", "RELSER"))
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one AE 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of AEs 58 59 99
+#> Total number of patients with at least one AE by worst grade
+#> Grade 1 0 1 (6.7%) 1 (6.7%)
+#> Grade 2 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> Grade 3 1 (6.7%) 2 (13.3%) 1 (6.7%)
+#> Grade 4 3 (20.0%) 2 (13.3%) 2 (13.3%)
+#> Grade 5 (fatal outcome) 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> Total number of patients with study drug withdrawn due to AE 2 (13.3%) 3 (20.0%) 3 (20.0%)
+#> Total number of patients with dose modified/interrupted due to AE 6 (40.0%) 9 (60.0%) 11 (73.3%)
+#> Total number of patients with treatment received for AE 10 (66.7%) 10 (66.7%) 14 (93.3%)
+#> Total number of patients with all non-fatal AEs resolved 9 (60.0%) 10 (66.7%) 12 (80.0%)
+#> Total number of patients with at least one unresolved or ongoing non-fatal AE 10 (66.7%) 9 (60.0%) 14 (93.3%)
+#> Total number of patients with at least one serious AE 12 (80.0%) 12 (80.0%) 11 (73.3%)
+#> Total number of patients with at least one related AE 11 (73.3%) 10 (66.7%) 13 (86.7%)
+#> No. of patients with serious, related AE 8 (53.3%) 8 (53.3%) 10 (66.7%)
+
++3. Safety Summary (Adverse Events of Special Interest) (for +studies with multiple drugs) +
+For studies with more than one study drug, users need to define the
+analyses in adae and add to the argument
+aesi_vars following the example above. No pre-defined
+analysis is available at this moment.
+
+Adverse Events (
+
+
+Adverse Events (AET02)
+
+
+
+
++1. Adverse Events +
+-
+
- The template
aet02produces the standard adverse event +summary by MedDRA system organ class and preferred term.
+ - The template does not include the column of total as default. The
+‘All Patients’ column can be added with the argument
+
lbl_overall = "All Patients".
+ - Missing values in
"AEBODSYS", and +"AEDECOD"are labeled as +No Coding Available.
+
+run(aet02, syn_data)
+#> MedDRA System Organ Class A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one adverse event 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Overall total number of events 58 59 99
+#> cl B.2
+#> Total number of patients with at least one adverse event 11 (73.3%) 8 (53.3%) 10 (66.7%)
+#> Total number of events 18 15 20
+#> dcd B.2.2.3.1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> dcd B.2.1.2.1 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> cl D.1
+#> Total number of patients with at least one adverse event 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> Total number of events 13 9 19
+#> dcd D.1.1.1.1 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> cl A.1
+#> Total number of patients with at least one adverse event 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Total number of events 8 11 16
+#> dcd A.1.1.1.2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd A.1.1.1.1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> cl B.1
+#> Total number of patients with at least one adverse event 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Total number of events 6 6 12
+#> dcd B.1.1.1.1 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> cl C.2
+#> Total number of patients with at least one adverse event 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Total number of events 6 4 12
+#> dcd C.2.1.2.1 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> cl D.2
+#> Total number of patients with at least one adverse event 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Total number of events 3 5 10
+#> dcd D.2.1.5.3 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> cl C.1
+#> Total number of patients with at least one adverse event 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Total number of events 4 9 10
+#> dcd C.1.1.1.3 4 (26.7%) 4 (26.7%) 5 (33.3%)
+
+
++2. Adverse Events (with High-level Term) +
+The syntax below displays adverse events by MedDRA system organ +class, high-level term and preferred term.
+
+run(aet02, syn_data, row_split_var = c("AEBODSYS", "AEHLT"))
+#> MedDRA System Organ Class
+#> High Level Term A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one adverse event 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Overall total number of events 58 59 99
+#> cl B.2
+#> Total number of patients with at least one adverse event 11 (73.3%) 8 (53.3%) 10 (66.7%)
+#> Total number of events 18 15 20
+#> hlt B.2.2.3
+#> Total number of patients with at least one adverse event 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> Total number of events 9 7 13
+#> dcd B.2.2.3.1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> hlt B.2.1.2
+#> Total number of patients with at least one adverse event 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> Total number of events 9 8 7
+#> dcd B.2.1.2.1 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> cl D.1
+#> Total number of patients with at least one adverse event 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> Total number of events 13 9 19
+#> hlt D.1.1.1
+#> Total number of patients with at least one adverse event 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> Total number of events 5 7 11
+#> dcd D.1.1.1.1 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> hlt D.1.1.4
+#> Total number of patients with at least one adverse event 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> Total number of events 8 2 8
+#> dcd D.1.1.4.2 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> cl A.1
+#> Total number of patients with at least one adverse event 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Total number of events 8 11 16
+#> hlt A.1.1.1
+#> Total number of patients with at least one adverse event 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Total number of events 8 11 16
+#> dcd A.1.1.1.2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd A.1.1.1.1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> cl B.1
+#> Total number of patients with at least one adverse event 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Total number of events 6 6 12
+#> hlt B.1.1.1
+#> Total number of patients with at least one adverse event 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Total number of events 6 6 12
+#> dcd B.1.1.1.1 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> cl C.2
+#> Total number of patients with at least one adverse event 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Total number of events 6 4 12
+#> hlt C.2.1.2
+#> Total number of patients with at least one adverse event 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Total number of events 6 4 12
+#> dcd C.2.1.2.1 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> cl D.2
+#> Total number of patients with at least one adverse event 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Total number of events 3 5 10
+#> hlt D.2.1.5
+#> Total number of patients with at least one adverse event 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Total number of events 3 5 10
+#> dcd D.2.1.5.3 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> cl C.1
+#> Total number of patients with at least one adverse event 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Total number of events 4 9 10
+#> hlt C.1.1.1
+#> Total number of patients with at least one adverse event 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Total number of events 4 9 10
+#> dcd C.1.1.1.3 4 (26.7%) 4 (26.7%) 5 (33.3%)
+
+
++3. Adverse Events (Preferred Terms only) +
+The syntax below displays adverse events by preferred term only.
+
+run(aet02, syn_data, row_split_var = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one adverse event 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Overall total number of events 58 59 99
+#> dcd B.2.2.3.1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> dcd B.1.1.1.1 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd C.2.1.2.1 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> dcd A.1.1.1.2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd B.2.1.2.1 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> dcd D.1.1.1.1 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> dcd D.2.1.5.3 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> dcd C.1.1.1.3 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> dcd A.1.1.1.1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+
+Adverse Events by Greatest
+Intensity(
+
+
+Adverse Events by Greatest
+Intensity(AET03)
+
+
+
+
++1. Adverse Events by Greatest Intensity +
+This aet03 template produces the
+standard adverse event by greatest intensity summary
+run(aet03, syn_data)
+#> MedDRA System Organ Class A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————
+#> - Any Intensity - 13 (86.7%) 14 (93.3%) 15 (100%)
+#> MILD 0 1 (6.7%) 1 (6.7%)
+#> MODERATE 2 (13.3%) 3 (20.0%) 2 (13.3%)
+#> SEVERE 11 (73.3%) 10 (66.7%) 12 (80.0%)
+#> cl B.2
+#> - Any Intensity - 11 (73.3%) 8 (53.3%) 10 (66.7%)
+#> MILD 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> MODERATE 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> dcd B.2.2.3.1
+#> - Any Intensity - 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> MILD 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> dcd B.2.1.2.1
+#> - Any Intensity - 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> MODERATE 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> cl D.1
+#> - Any Intensity - 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> MODERATE 5 (33.3%) 1 (6.7%) 4 (26.7%)
+#> SEVERE 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.1.1
+#> - Any Intensity - 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> SEVERE 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2
+#> - Any Intensity - 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> MODERATE 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> cl A.1
+#> - Any Intensity - 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> MILD 2 (13.3%) 0 4 (26.7%)
+#> MODERATE 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd A.1.1.1.2
+#> - Any Intensity - 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> MODERATE 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd A.1.1.1.1
+#> - Any Intensity - 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> MILD 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> cl B.1
+#> - Any Intensity - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> SEVERE 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd B.1.1.1.1
+#> - Any Intensity - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> SEVERE 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> cl C.2
+#> - Any Intensity - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> MODERATE 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> dcd C.2.1.2.1
+#> - Any Intensity - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> MODERATE 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> cl D.2
+#> - Any Intensity - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> MILD 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> dcd D.2.1.5.3
+#> - Any Intensity - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> MILD 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> cl C.1
+#> - Any Intensity - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> SEVERE 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> dcd C.1.1.1.3
+#> - Any Intensity - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> SEVERE 4 (26.7%) 4 (26.7%) 5 (33.3%)
+
+Adverse Events by Highest
+
+
+Adverse Events by Highest NCI CTCAE Grade
+(AET04)
+
+
+
+1. Adverse Events by Highest
+
+
+
+1. Adverse Events by Highest NCI CTCAE
+Grade
+
+-
+
- The
aet04template produces the +standard adverse event by highestNCI CTCAEgrade +summary.
+ - By default, this template includes the grouped grades of ‘Grade 1-2’ +and ‘Grade 3-4’. +
- By default this template removes the rows with 0 count. +
- If a treatment group does not have any adverse event, the treatment
+group is automatically displayed providing that it is defined in
+
ADSL.
+
+run(aet04, syn_data)
+#> MedDRA System Organ Class
+#> MedDRA Preferred Term A: Drug X B: Placebo C: Combination
+#> Grade (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————
+#> - Any adverse events -
+#> - Any Grade - 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Grade 1-2 1 (6.7%) 2 (13.3%) 2 (13.3%)
+#> 1 0 1 (6.7%) 1 (6.7%)
+#> 2 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> Grade 3-4 4 (26.7%) 4 (26.7%) 3 (20.0%)
+#> 3 1 (6.7%) 2 (13.3%) 1 (6.7%)
+#> 4 3 (20.0%) 2 (13.3%) 2 (13.3%)
+#> Grade 5 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> cl B.2
+#> - Overall -
+#> - Any Grade - 11 (73.3%) 8 (53.3%) 10 (66.7%)
+#> Grade 1-2 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> 1 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> Grade 3-4 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> dcd B.2.2.3.1
+#> - Any Grade - 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> Grade 1-2 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> 1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> dcd B.2.1.2.1
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> Grade 3-4 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> cl D.1
+#> - Overall -
+#> - Any Grade - 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> Grade 3-4 5 (33.3%) 1 (6.7%) 4 (26.7%)
+#> 3 5 (33.3%) 1 (6.7%) 4 (26.7%)
+#> Grade 5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.1.1
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> Grade 5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2
+#> - Any Grade - 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> Grade 3-4 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> 3 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> cl A.1
+#> - Overall -
+#> - Any Grade - 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Grade 1-2 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> 1 2 (13.3%) 0 4 (26.7%)
+#> 2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd A.1.1.1.2
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 1-2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> 2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd A.1.1.1.1
+#> - Any Grade - 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> Grade 1-2 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> 1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> cl B.1
+#> - Overall -
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Grade 5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd B.1.1.1.1
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Grade 5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> cl C.2
+#> - Overall -
+#> - Any Grade - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 1-2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> 2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> dcd C.2.1.2.1
+#> - Any Grade - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 1-2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> 2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> cl D.2
+#> - Overall -
+#> - Any Grade - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Grade 1-2 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 1 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> dcd D.2.1.5.3
+#> - Any Grade - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Grade 1-2 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 1 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> cl C.1
+#> - Overall -
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 3-4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> dcd C.1.1.1.3
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 3-4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+
+2. Adverse Events by Highest
+
+
+
+2. Adverse Events by Highest NCI CTCAE Grade
+(Fill in of Grades)
+
+If, for some preferred terms, not all grades occur but all grades
+should be displayed, this can be achieved by specifying the argument
+prune_0 = FALSE.
+run(aet04, syn_data, prune_0 = FALSE)
+#> MedDRA System Organ Class
+#> MedDRA Preferred Term A: Drug X B: Placebo C: Combination
+#> Grade (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————
+#> - Any adverse events -
+#> - Any Grade - 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Grade 1-2 1 (6.7%) 2 (13.3%) 2 (13.3%)
+#> 1 0 1 (6.7%) 1 (6.7%)
+#> 2 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> Grade 3-4 4 (26.7%) 4 (26.7%) 3 (20.0%)
+#> 3 1 (6.7%) 2 (13.3%) 1 (6.7%)
+#> 4 3 (20.0%) 2 (13.3%) 2 (13.3%)
+#> Grade 5 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> cl B.2
+#> - Overall -
+#> - Any Grade - 11 (73.3%) 8 (53.3%) 10 (66.7%)
+#> Grade 1-2 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> 1 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> 2 0 0 0
+#> Grade 3-4 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> dcd B.2.2.3.1
+#> - Any Grade - 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> Grade 1-2 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> 1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> dcd B.2.1.2.1
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> cl D.1
+#> - Overall -
+#> - Any Grade - 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 5 (33.3%) 1 (6.7%) 4 (26.7%)
+#> 3 5 (33.3%) 1 (6.7%) 4 (26.7%)
+#> 4 0 0 0
+#> Grade 5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.1.1
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2
+#> - Any Grade - 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> 3 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> cl A.1
+#> - Overall -
+#> - Any Grade - 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Grade 1-2 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> 1 2 (13.3%) 0 4 (26.7%)
+#> 2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> dcd A.1.1.1.2
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 1-2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> 1 0 0 0
+#> 2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> dcd A.1.1.1.1
+#> - Any Grade - 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> Grade 1-2 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> 1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> cl B.1
+#> - Overall -
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd B.1.1.1.1
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> cl C.2
+#> - Overall -
+#> - Any Grade - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 1-2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> 1 0 0 0
+#> 2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> dcd C.2.1.2.1
+#> - Any Grade - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 1-2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> 1 0 0 0
+#> 2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> cl D.2
+#> - Overall -
+#> - Any Grade - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Grade 1-2 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 1 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> dcd D.2.1.5.3
+#> - Any Grade - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Grade 1-2 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 1 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 2 0 0 0
+#> Grade 3-4 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Grade 5 0 0 0
+#> cl C.1
+#> - Overall -
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 3 0 0 0
+#> 4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 5 0 0 0
+#> dcd C.1.1.1.3
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 3 0 0 0
+#> 4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 5 0 0 0
+
+3. Adverse Events by Highest
+
+
+
+3. Adverse Events by Highest NCI CTCAE Grade
+with modified grouping of grade
+
+Collapsing grade 3-4 with grade 5, can be achieved by modifying the
+definition of grade groups in the argument
+grade_groups.
+grade_groups <- list(
+ "Grade 1-2" = c("1", "2"),
+ "Grade 3-5" = c("3", "4", "5")
+)
+
+run(aet04, syn_data, grade_groups = grade_groups, prune_0 = FALSE)
+#> MedDRA System Organ Class
+#> MedDRA Preferred Term A: Drug X B: Placebo C: Combination
+#> Grade (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————
+#> - Any adverse events -
+#> - Any Grade - 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Grade 1-2 1 (6.7%) 2 (13.3%) 2 (13.3%)
+#> 1 0 1 (6.7%) 1 (6.7%)
+#> 2 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> Grade 3-5 12 (80.0%) 12 (80.0%) 13 (86.7%)
+#> 3 1 (6.7%) 2 (13.3%) 1 (6.7%)
+#> 4 3 (20.0%) 2 (13.3%) 2 (13.3%)
+#> 5 8 (53.3%) 8 (53.3%) 10 (66.7%)
+#> cl B.2
+#> - Overall -
+#> - Any Grade - 11 (73.3%) 8 (53.3%) 10 (66.7%)
+#> Grade 1-2 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> 1 6 (40.0%) 2 (13.3%) 5 (33.3%)
+#> 2 0 0 0
+#> Grade 3-5 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 4 0 0 0
+#> 5 0 0 0
+#> dcd B.2.2.3.1
+#> - Any Grade - 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> Grade 1-2 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> 1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> 2 0 0 0
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> dcd B.2.1.2.1
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> 4 0 0 0
+#> 5 0 0 0
+#> cl D.1
+#> - Overall -
+#> - Any Grade - 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 9 (60.0%) 5 (33.3%) 11 (73.3%)
+#> 3 5 (33.3%) 1 (6.7%) 4 (26.7%)
+#> 4 0 0 0
+#> 5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.1.1
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2
+#> - Any Grade - 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> 3 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> 4 0 0 0
+#> 5 0 0 0
+#> cl A.1
+#> - Overall -
+#> - Any Grade - 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Grade 1-2 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> 1 2 (13.3%) 0 4 (26.7%)
+#> 2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> dcd A.1.1.1.2
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 1-2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> 1 0 0 0
+#> 2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> dcd A.1.1.1.1
+#> - Any Grade - 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> Grade 1-2 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> 1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> 2 0 0 0
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> cl B.1
+#> - Overall -
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd B.1.1.1.1
+#> - Any Grade - 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> cl C.2
+#> - Overall -
+#> - Any Grade - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 1-2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> 1 0 0 0
+#> 2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> dcd C.2.1.2.1
+#> - Any Grade - 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 1-2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> 1 0 0 0
+#> 2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> cl D.2
+#> - Overall -
+#> - Any Grade - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Grade 1-2 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 1 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 2 0 0 0
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> dcd D.2.1.5.3
+#> - Any Grade - 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> Grade 1-2 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 1 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> 2 0 0 0
+#> Grade 3-5 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> 5 0 0 0
+#> cl C.1
+#> - Overall -
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 3 0 0 0
+#> 4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 5 0 0 0
+#> dcd C.1.1.1.3
+#> - Any Grade - 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> Grade 1-2 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> Grade 3-5 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 3 0 0 0
+#> 4 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> 5 0 0 0
+
+Adverse Event Rate Adjusted for Patient-Years at Risk -
+First Occurrence (
+
+
+Adverse Event Rate Adjusted for Patient-Years at Risk -
+First Occurrence (AET05)
+
+
+
+
++1. Adverse Event Rate Adjusted for Patient-Years at Risk - +First Occurrence +
+-
+
- The
aet05template produces the +standard adverse event rate adjusted for patient-years at risk summary +considering first occurrence only.
+ - By default, all
adsaftteparameter codes containing the +string"TTE"are included in the output. Users are expected +to filter the parameter(s) of interest from input safety time-to-event +dataset in pre-processing if needed.
+ - In the input safety time-to-event dataset, in the censoring variable
+
CNSR,0indicates the occurrence of an event +of interest and1denotes censoring.
+
+proc_data <- log_filter(syn_data, PARAMCD == "AETTE1", "adsaftte")
+
+run(aet05, proc_data)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————
+#> Time to first occurrence of any adverse event
+#> Total patient-years at risk 31.0 9.0 22.0
+#> Number of adverse events observed 5 13 8
+#> AE rate per 100 patient-years 16.13 143.75 36.30
+#> 95% CI (1.99, 30.27) (65.61, 221.89) (11.15, 61.45)
+
+
++2. Adverse Event Rate Adjusted for Patient-Years at Risk - +First Occurrence (setting type of confidence interval) +
+-
+
- The type of the confidence interval for rate can be specified by the
+argument
conf_type. Options includenormal+(default),normal_logandexact.
+ - The confidence interval can be adjusted by the argument
+
conf_level.
+
+run(aet05, syn_data, conf_level = 0.90, conf_type = "exact")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Time to first occurrence of a grade 3-5 adverse event
+#> Total patient-years at risk 10.3 6.3 8.3
+#> Number of adverse events observed 12 14 13
+#> AE rate per 100 patient-years 116.36 223.74 156.98
+#> 90% CI (67.14, 188.53) (135.27, 349.78) (92.86, 249.59)
+#> Time to first occurrence of any adverse event
+#> Total patient-years at risk 31.0 9.0 22.0
+#> Number of adverse events observed 5 13 8
+#> AE rate per 100 patient-years 16.13 143.75 36.30
+#> 90% CI (6.36, 33.91) (85.03, 228.55) (18.06, 65.50)
+#> Time to first occurrence of any serious adverse event
+#> Total patient-years at risk 32.9 7.6 9.4
+#> Number of adverse events observed 4 14 13
+#> AE rate per 100 patient-years 12.15 183.83 137.79
+#> 90% CI (4.15, 27.80) (111.14, 287.38) (81.50, 219.06)
+
+Adverse Event Rate Adjusted for Patient-Years at Risk - All
+Occurrences (
+
+
+Adverse Event Rate Adjusted for Patient-Years at Risk - All
+Occurrences (AET05_ALL)
+
+
+
+
++1. Adverse Event Rate Adjusted for Patient-Years at Risk - +All Occurrences +
+-
+
- The
aet05_alltemplate produces the +standard adverse event rate adjusted for patient-years at risk summary +considering all occurrences.
+ - By default, all
adsaftteparameter codes containing the +string"TOT"and the parameter code"AEREPTTE"+are required."TOT"parameters store the number of +occurrences of adverse event of interests. Parameter code +"AEREPTTE"stores the time to end of adverse event +reporting period in years that contribute to the summary of “total +patient-years at risk” in the output. Users are expected to filter +parameters of interest from input analysis dataset in pre-processing, if +needed.
+ - In the input safety time-to-event dataset, in the censoring variable
+
CNSR,0indicates the occurrence of an event +of interest and1denotes censoring.
+
+proc_data <- log_filter(syn_data, PARAMCD == "AETOT1" | PARAMCD == "AEREPTTE", "adsaftte")
+
+run(aet05_all, proc_data)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————
+#> Number of occurrences of any adverse event
+#> Total patient-years at risk 44.4 44.2 44.4
+#> Number of adverse events observed 29 49 56
+#> AE rate per 100 patient-years 65.32 110.76 126.15
+#> 95% CI (41.54, 89.09) (79.75, 141.77) (93.11, 159.19)
+
+
++2. Adverse Event Rate Adjusted for Patient-Years at Risk - +All Occurrences (setting type of confidence interval) +
+-
+
- The type of the confidence interval for rate can be specified by the
+argument
conf_type. Options includenormal+(default),normal_log,exact, and +byar.
+ - The confidence interval can be adjusted by the argument
+
conf_level.
+
+run(aet05_all, syn_data, conf_level = 0.90, conf_type = "exact")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Number of occurrences of a grade 3-5 adverse event
+#> Total patient-years at risk 44.4 44.2 44.4
+#> Number of adverse events observed 65 54 95
+#> AE rate per 100 patient-years 146.40 122.06 214.00
+#> 90% CI (117.86, 179.97) (96.08, 153.12) (179.22, 253.80)
+#> Number of occurrences of any adverse event
+#> Total patient-years at risk 44.4 44.2 44.4
+#> Number of adverse events observed 29 49 56
+#> AE rate per 100 patient-years 65.32 110.76 126.15
+#> 90% CI (46.73, 89.06) (86.08, 140.53) (99.76, 157.60)
+#> Number of occurrences of any serious adverse event
+#> Total patient-years at risk 44.4 44.2 44.4
+#> Number of adverse events observed 9 36 60
+#> AE rate per 100 patient-years 20.27 81.37 135.16
+#> 90% CI (10.57, 35.37) (60.42, 107.46) (107.80, 167.58)
+
+Most Common (>=5%) Adverse Events
+(
+
+
+Most Common (>=5%) Adverse Events
+(AET10)
+
+
+
+
++1. Most Common (>=5%) Adverse Events +
+-
+
- The
aet10template produces the +standard most common adverse events occurring with relative frequency +>=5% output.
+
+run(aet10, syn_data)
+#> A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————
+#> dcd B.2.2.3.1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> dcd B.1.1.1.1 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd C.2.1.2.1 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> dcd A.1.1.1.2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd B.2.1.2.1 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> dcd D.1.1.1.1 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> dcd D.2.1.5.3 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> dcd C.1.1.1.3 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> dcd A.1.1.1.1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+
+
++2. Most Common (>=8%) Adverse Events (setting +threshold) +
+To modify the threshold for displaying preferred terms, this can be
+achieved by providing the threshold to the argument
+atleast.
+run(aet10, syn_data, atleast = 0.08)
+#> A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————
+#> dcd B.2.2.3.1 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> dcd B.1.1.1.1 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> dcd C.2.1.2.1 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> dcd A.1.1.1.2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> dcd B.2.1.2.1 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> dcd D.1.1.1.1 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> dcd D.1.1.4.2 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> dcd D.2.1.5.3 2 (13.3%) 5 (33.3%) 7 (46.7%)
+#> dcd C.1.1.1.3 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> dcd A.1.1.1.1 3 (20.0%) 1 (6.7%) 6 (40.0%)
+
+Absolute Value and Change from Baseline by Visit
+(
+
+
+Absolute Value and Change from Baseline by Visit
+(CFBT01)
+
+
+
+
++1. Absolute Value and Change from Baseline by +Visit +
+-
+
- By default, the
cfbt01template displays analysis value +(AVAL) and absolute change from baseline (CHG) +for each visit.
+ - The template does not include the column of total by default. +
- Each parameter is presented on a separate page. +
- The absolute change from baseline at baseline value is not +displayed. +
+proc_data <- log_filter(
+ syn_data,
+ PARAMCD %in% c("DIABP", "SYSBP"), "advs"
+)
+run(cfbt01, proc_data, dataset = "advs")
+#> A: Drug X B: Placebo C: Combination
+#> Change from Change from Change from
+#> Value at Visit Baseline Value at Visit Baseline Value at Visit Baseline
+#> Analysis Visit (N=15) (N=15) (N=15) (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Diastolic Blood Pressure
+#> SCREENING
+#> n 15 0 15 0 15 0
+#> Mean (SD) 94.385 (17.067) NE (NE) 106.381 (20.586) NE (NE) 106.468 (12.628) NE (NE)
+#> Median 94.933 NE 111.133 NE 108.359 NE
+#> Min - Max 55.71 - 122.00 NE - NE 60.21 - 131.91 NE - NE 83.29 - 127.17 NE - NE
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 96.133 (22.458) 108.111 (15.074) 103.149 (19.752)
+#> Median 93.328 108.951 102.849
+#> Min - Max 60.58 - 136.59 83.44 - 131.62 66.05 - 136.55
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 98.977 (21.359) 2.844 (28.106) 104.110 (16.172) -4.001 (21.867) 100.826 (19.027) -2.323 (25.018)
+#> Median 92.447 -4.066 107.703 3.227 103.058 -2.476
+#> Min - Max 67.55 - 130.37 -32.82 - 47.68 70.91 - 132.89 -52.94 - 28.63 70.04 - 128.68 -55.15 - 41.81
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 99.758 (14.477) 3.626 (21.189) 97.473 (17.296) -10.638 (20.831) 94.272 (16.961) -8.877 (27.229)
+#> Median 101.498 1.731 99.501 -9.727 96.789 -10.155
+#> Min - Max 71.98 - 122.81 -39.50 - 47.57 53.80 - 125.81 -55.15 - 25.26 63.45 - 117.47 -73.10 - 46.54
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 99.101 (26.109) 2.968 (34.327) 91.984 (16.925) -16.127 (21.881) 94.586 (13.560) -8.563 (21.713)
+#> Median 101.146 -0.271 91.244 -14.384 98.398 -16.075
+#> Min - Max 47.68 - 162.22 -47.87 - 76.64 67.80 - 119.72 -53.06 - 22.52 73.50 - 115.43 -37.90 - 32.66
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 103.400 (22.273) 7.267 (30.740) 96.467 (19.451) -11.644 (25.922) 108.338 (18.417) 5.189 (21.881)
+#> Median 98.168 2.510 97.385 -16.793 107.555 7.966
+#> Min - Max 63.09 - 148.25 -38.43 - 61.90 63.35 - 131.57 -57.11 - 48.13 68.78 - 132.52 -33.96 - 41.50
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 93.222 (18.536) -2.911 (28.873) 97.890 (20.701) -10.221 (27.593) 95.317 (16.401) -7.832 (19.827)
+#> Median 90.799 -3.385 99.049 -11.319 93.876 -4.665
+#> Min - Max 63.55 - 139.11 -48.63 - 47.35 69.47 - 137.64 -54.38 - 37.85 71.91 - 138.54 -44.47 - 29.11
+#> Systolic Blood Pressure
+#> SCREENING
+#> n 15 0 15 0 15 0
+#> Mean (SD) 154.073 (33.511) NE (NE) 157.840 (34.393) NE (NE) 152.407 (22.311) NE (NE)
+#> Median 156.169 NE 161.670 NE 149.556 NE
+#> Min - Max 78.31 - 210.70 NE - NE 79.76 - 210.40 NE - NE 108.21 - 184.88 NE - NE
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 145.925 (28.231) 152.007 (28.664) 154.173 (26.317)
+#> Median 142.705 157.698 155.282
+#> Min - Max 85.21 - 195.68 98.90 - 194.62 86.65 - 192.68
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 156.509 (21.097) 10.584 (34.598) 147.480 (33.473) -4.527 (48.895) 143.319 (30.759) -10.854 (34.553)
+#> Median 160.711 5.802 155.030 2.758 145.548 -5.636
+#> Min - Max 126.84 - 185.53 -53.28 - 91.52 85.22 - 189.88 -77.34 - 90.98 90.37 - 191.58 -65.71 - 49.04
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 144.202 (33.676) -1.723 (27.067) 136.892 (30.178) -15.115 (37.794) 148.622 (27.088) -5.551 (44.670)
+#> Median 144.253 5.325 142.679 -14.083 147.102 -11.512
+#> Min - Max 62.56 - 203.66 -53.89 - 44.16 70.34 - 174.27 -83.07 - 62.39 108.82 - 200.23 -69.54 - 113.59
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 154.887 (35.374) 8.962 (38.455) 149.761 (28.944) -2.247 (44.835) 150.460 (21.352) -3.712 (37.984)
+#> Median 158.938 17.191 155.044 -1.796 156.505 -7.606
+#> Min - Max 112.32 - 218.83 -47.28 - 96.18 84.42 - 192.92 -110.20 - 94.02 94.70 - 180.41 -74.91 - 72.74
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 150.159 (32.249) 4.234 (32.965) 156.043 (22.863) 4.036 (42.494) 145.714 (22.980) -8.458 (33.175)
+#> Median 145.506 3.754 149.094 -10.000 150.797 -14.432
+#> Min - Max 69.37 - 210.43 -89.16 - 54.32 113.57 - 195.10 -71.44 - 77.75 106.91 - 188.09 -41.95 - 65.16
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 155.964 (30.945) 10.039 (42.252) 156.387 (35.274) 4.380 (51.782) 143.592 (33.170) -10.581 (44.799)
+#> Median 158.142 1.448 164.552 7.060 148.501 -2.385
+#> Min - Max 110.61 - 212.47 -53.91 - 90.45 63.28 - 198.79 -131.34 - 86.84 92.18 - 191.05 -78.77 - 64.35
+
+
++2. Absolute Value and Change from Baseline by Visit without +Screening +
+The skip arguments controls which visit values should
+not be displayed. For instance, to mask the changes from baseline during
+the “SCREENING” and “BASELINE” visits.
+run(cfbt01, proc_data, dataset = "advs", skip = list(CHG = c("SCREENING", "BASELINE")))
+#> A: Drug X B: Placebo C: Combination
+#> Change from Change from Change from
+#> Value at Visit Baseline Value at Visit Baseline Value at Visit Baseline
+#> Analysis Visit (N=15) (N=15) (N=15) (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Diastolic Blood Pressure
+#> SCREENING
+#> n 15 15 15
+#> Mean (SD) 94.385 (17.067) 106.381 (20.586) 106.468 (12.628)
+#> Median 94.933 111.133 108.359
+#> Min - Max 55.71 - 122.00 60.21 - 131.91 83.29 - 127.17
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 96.133 (22.458) 108.111 (15.074) 103.149 (19.752)
+#> Median 93.328 108.951 102.849
+#> Min - Max 60.58 - 136.59 83.44 - 131.62 66.05 - 136.55
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 98.977 (21.359) 2.844 (28.106) 104.110 (16.172) -4.001 (21.867) 100.826 (19.027) -2.323 (25.018)
+#> Median 92.447 -4.066 107.703 3.227 103.058 -2.476
+#> Min - Max 67.55 - 130.37 -32.82 - 47.68 70.91 - 132.89 -52.94 - 28.63 70.04 - 128.68 -55.15 - 41.81
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 99.758 (14.477) 3.626 (21.189) 97.473 (17.296) -10.638 (20.831) 94.272 (16.961) -8.877 (27.229)
+#> Median 101.498 1.731 99.501 -9.727 96.789 -10.155
+#> Min - Max 71.98 - 122.81 -39.50 - 47.57 53.80 - 125.81 -55.15 - 25.26 63.45 - 117.47 -73.10 - 46.54
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 99.101 (26.109) 2.968 (34.327) 91.984 (16.925) -16.127 (21.881) 94.586 (13.560) -8.563 (21.713)
+#> Median 101.146 -0.271 91.244 -14.384 98.398 -16.075
+#> Min - Max 47.68 - 162.22 -47.87 - 76.64 67.80 - 119.72 -53.06 - 22.52 73.50 - 115.43 -37.90 - 32.66
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 103.400 (22.273) 7.267 (30.740) 96.467 (19.451) -11.644 (25.922) 108.338 (18.417) 5.189 (21.881)
+#> Median 98.168 2.510 97.385 -16.793 107.555 7.966
+#> Min - Max 63.09 - 148.25 -38.43 - 61.90 63.35 - 131.57 -57.11 - 48.13 68.78 - 132.52 -33.96 - 41.50
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 93.222 (18.536) -2.911 (28.873) 97.890 (20.701) -10.221 (27.593) 95.317 (16.401) -7.832 (19.827)
+#> Median 90.799 -3.385 99.049 -11.319 93.876 -4.665
+#> Min - Max 63.55 - 139.11 -48.63 - 47.35 69.47 - 137.64 -54.38 - 37.85 71.91 - 138.54 -44.47 - 29.11
+#> Systolic Blood Pressure
+#> SCREENING
+#> n 15 15 15
+#> Mean (SD) 154.073 (33.511) 157.840 (34.393) 152.407 (22.311)
+#> Median 156.169 161.670 149.556
+#> Min - Max 78.31 - 210.70 79.76 - 210.40 108.21 - 184.88
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 145.925 (28.231) 152.007 (28.664) 154.173 (26.317)
+#> Median 142.705 157.698 155.282
+#> Min - Max 85.21 - 195.68 98.90 - 194.62 86.65 - 192.68
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 156.509 (21.097) 10.584 (34.598) 147.480 (33.473) -4.527 (48.895) 143.319 (30.759) -10.854 (34.553)
+#> Median 160.711 5.802 155.030 2.758 145.548 -5.636
+#> Min - Max 126.84 - 185.53 -53.28 - 91.52 85.22 - 189.88 -77.34 - 90.98 90.37 - 191.58 -65.71 - 49.04
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 144.202 (33.676) -1.723 (27.067) 136.892 (30.178) -15.115 (37.794) 148.622 (27.088) -5.551 (44.670)
+#> Median 144.253 5.325 142.679 -14.083 147.102 -11.512
+#> Min - Max 62.56 - 203.66 -53.89 - 44.16 70.34 - 174.27 -83.07 - 62.39 108.82 - 200.23 -69.54 - 113.59
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 154.887 (35.374) 8.962 (38.455) 149.761 (28.944) -2.247 (44.835) 150.460 (21.352) -3.712 (37.984)
+#> Median 158.938 17.191 155.044 -1.796 156.505 -7.606
+#> Min - Max 112.32 - 218.83 -47.28 - 96.18 84.42 - 192.92 -110.20 - 94.02 94.70 - 180.41 -74.91 - 72.74
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 150.159 (32.249) 4.234 (32.965) 156.043 (22.863) 4.036 (42.494) 145.714 (22.980) -8.458 (33.175)
+#> Median 145.506 3.754 149.094 -10.000 150.797 -14.432
+#> Min - Max 69.37 - 210.43 -89.16 - 54.32 113.57 - 195.10 -71.44 - 77.75 106.91 - 188.09 -41.95 - 65.16
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 155.964 (30.945) 10.039 (42.252) 156.387 (35.274) 4.380 (51.782) 143.592 (33.170) -10.581 (44.799)
+#> Median 158.142 1.448 164.552 7.060 148.501 -2.385
+#> Min - Max 110.61 - 212.47 -53.91 - 90.45 63.28 - 198.79 -131.34 - 86.84 92.18 - 191.05 -78.77 - 64.35
+
+
++3. Absolute Value by Visit +
+To display only the absolute value, specify
+summaryvars = "AVAL".
+run(cfbt01, proc_data, dataset = "advs", summaryvars = "AVAL")
+#> A: Drug X B: Placebo C: Combination
+#> Value at Visit Value at Visit Value at Visit
+#> Analysis Visit (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————
+#> Diastolic Blood Pressure
+#> SCREENING
+#> n 15 15 15
+#> Mean (SD) 94.385 (17.067) 106.381 (20.586) 106.468 (12.628)
+#> Median 94.933 111.133 108.359
+#> Min - Max 55.71 - 122.00 60.21 - 131.91 83.29 - 127.17
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 96.133 (22.458) 108.111 (15.074) 103.149 (19.752)
+#> Median 93.328 108.951 102.849
+#> Min - Max 60.58 - 136.59 83.44 - 131.62 66.05 - 136.55
+#> WEEK 1 DAY 8
+#> n 15 15 15
+#> Mean (SD) 98.977 (21.359) 104.110 (16.172) 100.826 (19.027)
+#> Median 92.447 107.703 103.058
+#> Min - Max 67.55 - 130.37 70.91 - 132.89 70.04 - 128.68
+#> WEEK 2 DAY 15
+#> n 15 15 15
+#> Mean (SD) 99.758 (14.477) 97.473 (17.296) 94.272 (16.961)
+#> Median 101.498 99.501 96.789
+#> Min - Max 71.98 - 122.81 53.80 - 125.81 63.45 - 117.47
+#> WEEK 3 DAY 22
+#> n 15 15 15
+#> Mean (SD) 99.101 (26.109) 91.984 (16.925) 94.586 (13.560)
+#> Median 101.146 91.244 98.398
+#> Min - Max 47.68 - 162.22 67.80 - 119.72 73.50 - 115.43
+#> WEEK 4 DAY 29
+#> n 15 15 15
+#> Mean (SD) 103.400 (22.273) 96.467 (19.451) 108.338 (18.417)
+#> Median 98.168 97.385 107.555
+#> Min - Max 63.09 - 148.25 63.35 - 131.57 68.78 - 132.52
+#> WEEK 5 DAY 36
+#> n 15 15 15
+#> Mean (SD) 93.222 (18.536) 97.890 (20.701) 95.317 (16.401)
+#> Median 90.799 99.049 93.876
+#> Min - Max 63.55 - 139.11 69.47 - 137.64 71.91 - 138.54
+#> Systolic Blood Pressure
+#> SCREENING
+#> n 15 15 15
+#> Mean (SD) 154.073 (33.511) 157.840 (34.393) 152.407 (22.311)
+#> Median 156.169 161.670 149.556
+#> Min - Max 78.31 - 210.70 79.76 - 210.40 108.21 - 184.88
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 145.925 (28.231) 152.007 (28.664) 154.173 (26.317)
+#> Median 142.705 157.698 155.282
+#> Min - Max 85.21 - 195.68 98.90 - 194.62 86.65 - 192.68
+#> WEEK 1 DAY 8
+#> n 15 15 15
+#> Mean (SD) 156.509 (21.097) 147.480 (33.473) 143.319 (30.759)
+#> Median 160.711 155.030 145.548
+#> Min - Max 126.84 - 185.53 85.22 - 189.88 90.37 - 191.58
+#> WEEK 2 DAY 15
+#> n 15 15 15
+#> Mean (SD) 144.202 (33.676) 136.892 (30.178) 148.622 (27.088)
+#> Median 144.253 142.679 147.102
+#> Min - Max 62.56 - 203.66 70.34 - 174.27 108.82 - 200.23
+#> WEEK 3 DAY 22
+#> n 15 15 15
+#> Mean (SD) 154.887 (35.374) 149.761 (28.944) 150.460 (21.352)
+#> Median 158.938 155.044 156.505
+#> Min - Max 112.32 - 218.83 84.42 - 192.92 94.70 - 180.41
+#> WEEK 4 DAY 29
+#> n 15 15 15
+#> Mean (SD) 150.159 (32.249) 156.043 (22.863) 145.714 (22.980)
+#> Median 145.506 149.094 150.797
+#> Min - Max 69.37 - 210.43 113.57 - 195.10 106.91 - 188.09
+#> WEEK 5 DAY 36
+#> n 15 15 15
+#> Mean (SD) 155.964 (30.945) 156.387 (35.274) 143.592 (33.170)
+#> Median 158.142 164.552 148.501
+#> Min - Max 110.61 - 212.47 63.28 - 198.79 92.18 - 191.05
+
+Concomitant Medications by Medication Class and Preferred
+Name (
+
+
+Concomitant Medications by Medication Class and Preferred
+Name (CMT01A)
+
+
+
+
++1. Concomitant Medications by Medication Class and Preferred +Name +
+-
+
- The
cmt01atemplate displays +concomitant medications byATC Level 2and Preferred Name +by default.
+ - The template does not include the column of total by default. +
- The template sort medication class and preferred name by +alphabetical order by default. +
+run(cmt01a, syn_data)
+#> ATC Level 2 Text A: Drug X B: Placebo C: Combination
+#> Other Treatment (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one treatment 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of treatments 58 59 99
+#> ATCCLAS2 A
+#> Total number of patients with at least one treatment 10 (66.7%) 11 (73.3%) 12 (80.0%)
+#> Total number of treatments 15 21 28
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> medname A_2/3 5 (33.3%) 6 (40.0%) 7 (46.7%)
+#> medname A_1/3 4 (26.7%) 3 (20.0%) 8 (53.3%)
+#> ATCCLAS2 A p2
+#> Total number of patients with at least one treatment 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> Total number of treatments 6 8 8
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> ATCCLAS2 B
+#> Total number of patients with at least one treatment 12 (80.0%) 10 (66.7%) 14 (93.3%)
+#> Total number of treatments 30 30 52
+#> medname B_3/4 8 (53.3%) 6 (40.0%) 8 (53.3%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> medname B_4/4 4 (26.7%) 5 (33.3%) 8 (53.3%)
+#> ATCCLAS2 B p2
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> Total number of treatments 18 17 25
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS2 B p3
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> Total number of treatments 18 17 25
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS2 C
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> Total number of treatments 13 8 19
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS2 C p2
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> Total number of treatments 13 8 19
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS2 C p3
+#> Total number of patients with at least one treatment 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> Total number of treatments 5 5 12
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+
+2. Concomitant Medications by Medication Class and Preferred
+Name (changing
+
+
+
+2. Concomitant Medications by Medication Class and Preferred
+Name (changing ATC class level)
+
+
+run(cmt01a, syn_data, row_split_var = "ATC1")
+#> ATC Level 1 Text A: Drug X B: Placebo C: Combination
+#> Other Treatment (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one treatment 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of treatments 58 59 99
+#> ATCCLAS1 A
+#> Total number of patients with at least one treatment 10 (66.7%) 11 (73.3%) 12 (80.0%)
+#> Total number of treatments 15 21 28
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> medname A_2/3 5 (33.3%) 6 (40.0%) 7 (46.7%)
+#> medname A_1/3 4 (26.7%) 3 (20.0%) 8 (53.3%)
+#> ATCCLAS1 A p2
+#> Total number of patients with at least one treatment 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> Total number of treatments 6 8 8
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> ATCCLAS1 B
+#> Total number of patients with at least one treatment 12 (80.0%) 10 (66.7%) 14 (93.3%)
+#> Total number of treatments 30 30 52
+#> medname B_3/4 8 (53.3%) 6 (40.0%) 8 (53.3%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> medname B_4/4 4 (26.7%) 5 (33.3%) 8 (53.3%)
+#> ATCCLAS1 B p2
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> Total number of treatments 18 17 25
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS1 B p3
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> Total number of treatments 18 17 25
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS1 C
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> Total number of treatments 13 8 19
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS1 C p2
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> Total number of treatments 13 8 19
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS1 C p3
+#> Total number of patients with at least one treatment 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> Total number of treatments 5 5 12
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+
+
++3. Concomitant Medications by Medication Class and Preferred +Name (classes sorted by frequency) +
+The argument sort_by_freq = TRUE sort medication class
+by frequency.
+run(cmt01a, syn_data, sort_by_freq = TRUE)
+#> ATC Level 2 Text A: Drug X B: Placebo C: Combination
+#> Other Treatment (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one treatment 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of treatments 58 59 99
+#> ATCCLAS2 B
+#> Total number of patients with at least one treatment 12 (80.0%) 10 (66.7%) 14 (93.3%)
+#> Total number of treatments 30 30 52
+#> medname B_3/4 8 (53.3%) 6 (40.0%) 8 (53.3%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> medname B_4/4 4 (26.7%) 5 (33.3%) 8 (53.3%)
+#> ATCCLAS2 A
+#> Total number of patients with at least one treatment 10 (66.7%) 11 (73.3%) 12 (80.0%)
+#> Total number of treatments 15 21 28
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> medname A_2/3 5 (33.3%) 6 (40.0%) 7 (46.7%)
+#> medname A_1/3 4 (26.7%) 3 (20.0%) 8 (53.3%)
+#> ATCCLAS2 B p2
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> Total number of treatments 18 17 25
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS2 B p3
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> Total number of treatments 18 17 25
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS2 C
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> Total number of treatments 13 8 19
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS2 C p2
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> Total number of treatments 13 8 19
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS2 A p2
+#> Total number of patients with at least one treatment 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> Total number of treatments 6 8 8
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> ATCCLAS2 C p3
+#> Total number of patients with at least one treatment 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> Total number of treatments 5 5 12
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+
+
++4. Concomitant Medications by Medication Class and Preferred +Name (total number of treatments per medication class +suppressed) +
+The cmt01a template includes the
+analysis of ‘total number of treatments’ by default, modify the argument
+summary_labels to change it.
+run(cmt01a, syn_data, summary_labels = list(TOTAL = cmt01_label, ATC2 = cmt01_label[1]))
+#> ATC Level 2 Text A: Drug X B: Placebo C: Combination
+#> Other Treatment (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one treatment 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of treatments 58 59 99
+#> ATCCLAS2 A
+#> Total number of patients with at least one treatment 10 (66.7%) 11 (73.3%) 12 (80.0%)
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> medname A_2/3 5 (33.3%) 6 (40.0%) 7 (46.7%)
+#> medname A_1/3 4 (26.7%) 3 (20.0%) 8 (53.3%)
+#> ATCCLAS2 A p2
+#> Total number of patients with at least one treatment 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> ATCCLAS2 B
+#> Total number of patients with at least one treatment 12 (80.0%) 10 (66.7%) 14 (93.3%)
+#> medname B_3/4 8 (53.3%) 6 (40.0%) 8 (53.3%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> medname B_4/4 4 (26.7%) 5 (33.3%) 8 (53.3%)
+#> ATCCLAS2 B p2
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS2 B p3
+#> Total number of patients with at least one treatment 10 (66.7%) 8 (53.3%) 12 (80.0%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> ATCCLAS2 C
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS2 C p2
+#> Total number of patients with at least one treatment 9 (60.0%) 7 (46.7%) 12 (80.0%)
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+#> ATCCLAS2 C p3
+#> Total number of patients with at least one treatment 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+
+Concomitant Medications by Preferred Name
+(
+
+
+Concomitant Medications by Preferred Name
+(CMT02_PT)
+
+
+
+
++1. Concomitant Medications by Preferred Name +
+-
+
- The
cmt02_pttemplate displays +concomitant medications by Preferred Name by default.
+ - The template does not include the column of total by default. +
- The template sorts preferred name by alphabetical order by default.
+Set the argument
sort_by_freq = TRUEto sort preferred +names by frequency.
+
+run(cmt02_pt, syn_data)
+#> A: Drug X B: Placebo C: Combination
+#> Other Treatment (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one treatment 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of treatments 58 59 99
+#> medname B_3/4 8 (53.3%) 6 (40.0%) 8 (53.3%)
+#> medname B_2/4 6 (40.0%) 5 (33.3%) 10 (66.7%)
+#> medname A_3/3 5 (33.3%) 8 (53.3%) 6 (40.0%)
+#> medname B_1/4 7 (46.7%) 6 (40.0%) 6 (40.0%)
+#> medname A_2/3 5 (33.3%) 6 (40.0%) 7 (46.7%)
+#> medname B_4/4 4 (26.7%) 5 (33.3%) 8 (53.3%)
+#> medname C_2/2 4 (26.7%) 5 (33.3%) 7 (46.7%)
+#> medname A_1/3 4 (26.7%) 3 (20.0%) 8 (53.3%)
+#> medname C_1/2 6 (40.0%) 2 (13.3%) 6 (40.0%)
+
+Cox Regression (
+
+
+Cox Regression (COXT01)
+
+
+
+
++1. Cox Regression +
+-
+
- The
coxt01template produces the +standard Cox regression output.
+ - Users are expected to pre-process the input analysis data by +selecting a time-to-event parameter to be analyzed. The example below is +based on the time-to-event parameter “Duration of Confirmed Response by +Investigator”. +
- The time variable in the model is specified through the
+
time_varargument. By default,time_varis set +to"AVAL", which comes fromADTTE.AVAL.
+ - The event variable in the model is specified through the
+
event_varargument. By default,event_varis +set to"EVENT", which is derived based on the censoring +indicatorADTTE.CNSRin the pre-processing function +coxt01_pre.
+ - If there are more than two treatment groups present in the input
+analysis data, users are also expected to select only two treatment
+groups. The example below is based on treatment groups
+
"Arm A"and"Arm B".
+
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+proc_data <- log_filter(proc_data, ARMCD != "ARM C", "adsl")
+run(coxt01, proc_data, time_var = "AVAL", event_var = "EVENT")
+#> Treatment Effect Adjusted for Covariate
+#> Effect/Covariate Included in the Model n Hazard Ratio 95% CI p-value
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> B: Placebo vs control (A: Drug X) 30 2.71 (0.93, 7.88) 0.0666
+#> Covariate:
+#> Sex 30 2.91 (0.97, 8.73) 0.0567
+#> RACE 30 3.09 (1.01, 9.50) 0.0487
+#> Age (yr) 30 2.89 (0.97, 8.59) 0.0566
+
+
++2. Cox Regression (with interaction term) +
+To add the interaction term to the model,
+interaction = TRUE, which is passed to
+tern::control_coxreg(), needs to be specified.
+run(coxt01, proc_data, covariates = "AAGE", interaction = TRUE)
+#> Treatment Effect Adjusted for Covariate
+#> Effect/Covariate Included in the Model n Hazard Ratio 95% CI p-value Interaction p-value
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> B: Placebo vs control (A: Drug X) 30 2.71 (0.93, 7.88) 0.0666
+#> Covariate:
+#> Age (yr) 30 0.3666
+#> 32 2.87 (0.98, 8.41)
+
+
++3. Cox Regression (specifying covariates) +
+-
+
- By default,
"SEX","RACE"and +"AAGE"are used as the covariates for the model.
+ - Users can specify a different set of covariates through the
+
covariatesargument. In the example below, +"RACE"and"AAGE"are used as covariates.
+
+run(coxt01, proc_data, covariates = c("RACE", "AAGE"))
+#> Treatment Effect Adjusted for Covariate
+#> Effect/Covariate Included in the Model n Hazard Ratio 95% CI p-value
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> B: Placebo vs control (A: Drug X) 30 2.71 (0.93, 7.88) 0.0666
+#> Covariate:
+#> RACE 30 3.09 (1.01, 9.50) 0.0487
+#> Age (yr) 30 2.89 (0.97, 8.59) 0.0566
+
+
++4. Cox Regression (setting strata, ties, and alpha +level) +
+-
+
- By default,
strata = NULL(no stratification), +ties = "exact"(equivalent toDISCRETEin +SAS), andconf_level = 0.95are applied.
+ - Users can specify one or more stratification variables via the
+
strataargument.
+ - Other tie handling methods, i.e.,
"efron"or +"breslow", can be specified in thetie+argument, which is passed totern::control_coxreg().
+ - Users can also customize the alpha level for the confidence
+intervals through the
conf_levelargument, which is passed +totern::control_coxreg().
+
+run(coxt01, proc_data, covariates = c("SEX", "AAGE"), strata = c("RACE"), conf_level = 0.90)
+#> Treatment Effect Adjusted for Covariate
+#> Effect/Covariate Included in the Model n Hazard Ratio 90% CI p-value
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> B: Placebo vs control (A: Drug X) 30 2.69 (1.07, 6.76) 0.0785
+#> Covariate:
+#> Sex 30 2.90 (1.12, 7.54) 0.0668
+#> Age (yr) 30 2.72 (1.08, 6.85) 0.0755
+
+Multi-variable Cox Regression
+(
+
+
+Multi-variable Cox Regression
+(COXT02)
+
+
+
+
++1. Multi-variable Cox Regression +
+-
+
- The
coxt02template produces the +standard multi-variable cox regression output.
+ - Users are expected to pre-process the input analysis data by +selecting a time-to-event parameter to be analyzed. The example below is +based on the time-to-event parameter “Duration of Confirmed Response by +Investigator”. +
- The time variable in the model is specified through the
+
time_varargument. By default,time_varis set +to"AVAL", which comes fromADTTE.AVAL.
+ - The event variable in the model is specified through the
+
event_varargument. By default,event_varis +set to"EVENT", which is derived based on the censoring +indicatorADTTE.CNSRin the pre-processing function +coxt01_pre.
+
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(coxt02, proc_data, time_var = "AVAL", event_var = "EVENT")
+#> Effect/Covariate Included in the Model Hazard Ratio 95% CI p-value
+#> —————————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> Description of Planned Arm (reference = A: Drug X) 0.1630
+#> B: Placebo 2.92 (0.93, 9.17) 0.0672
+#> C: Combination 1.56 (0.47, 5.10) 0.4659
+#> Covariate:
+#> Sex (reference = F)
+#> M 1.03 (0.41, 2.55) 0.9549
+#> RACE (reference = AMERICAN INDIAN OR ALASKA NATIVE) 0.8498
+#> ASIAN 1.22 (0.27, 5.55) 0.7967
+#> BLACK OR AFRICAN AMERICAN 0.81 (0.12, 5.70) 0.8340
+#> WHITE 1.57 (0.26, 9.67) 0.6258
+#> Age (yr)
+#> All 0.99 (0.93, 1.05) 0.6650
+
+
++2. Multi-variable Cox Regression (specifying +covariates) +
+-
+
- By default,
"SEX","RACE"and +"AAGE"are used as the covariates for the model.
+ - Users can specify a different set of covariates through the
+
covariatesargument. In the example below, +"RACE"and"AAGE"are used as covariates.
+
+run(coxt02, proc_data, covariates = c("RACE", "AAGE"))
+#> Effect/Covariate Included in the Model Hazard Ratio 95% CI p-value
+#> —————————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> Description of Planned Arm (reference = A: Drug X) 0.1390
+#> B: Placebo 2.94 (0.97, 8.92) 0.0570
+#> C: Combination 1.56 (0.48, 5.09) 0.4605
+#> Covariate:
+#> RACE (reference = AMERICAN INDIAN OR ALASKA NATIVE) 0.8504
+#> ASIAN 1.22 (0.27, 5.54) 0.7972
+#> BLACK OR AFRICAN AMERICAN 0.81 (0.12, 5.65) 0.8306
+#> WHITE 1.56 (0.26, 9.53) 0.6279
+#> Age (yr)
+#> All 0.99 (0.93, 1.05) 0.6633
+
+
++3. Multi-variable Cox Regression (setting strata, ties, and +alpha level) +
+-
+
- By default,
strata = NULL(no stratification), +ties = "exact"(equivalent toDISCRETEin +SAS), andconf_level = 0.95are applied.
+ - Users can specify one or more stratification variables via the
+
strataargument.
+ - Other tie handling methods, i.e.,
"efron"or +"breslow", can be specified in thetie+argument, which is passed totern::control_coxreg().
+ - Users can also customize the alpha level for the confidence
+intervals through the
conf_levelargument, which is passed +totern::control_coxreg().
+
+run(coxt02, proc_data, covariates = c("SEX", "AAGE"), strata = c("RACE"), conf_level = 0.90, ties = "efron")
+#> Effect/Covariate Included in the Model Hazard Ratio 90% CI p-value
+#> ————————————————————————————————————————————————————————————————————————————————————————————
+#> Treatment:
+#> Description of Planned Arm (reference = A: Drug X) 0.1680
+#> B: Placebo 2.85 (1.09, 7.46) 0.0743
+#> C: Combination 1.47 (0.54, 4.02) 0.5254
+#> Covariate:
+#> Sex (reference = F)
+#> M 0.98 (0.45, 2.13) 0.9700
+#> Age (yr)
+#> All 0.99 (0.94, 1.04) 0.6571
+
+Demographics and Baseline Characteristics
+(
+
+
+Demographics and Baseline Characteristics
+(DMT01)
+
+
+
+
++1. Demographics and Baseline Characteristics with All +Patients +
+-
+
- The
dmt01template produces the +standard demographics and baseline characteristics summary.
+ - This template includes the column of total by default. +
+run(dmt01, syn_data)
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> ————————————————————————————————————————————————————————————————————————————————————————————
+#> Age (yr)
+#> n 15 15 15 45
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4) 34.3 (7.3)
+#> Median 31.0 35.0 35.0 34.0
+#> Min - Max 24 - 40 24 - 57 24 - 49 24 - 57
+#> Age Group
+#> n 15 15 15 45
+#> <65 15 (100%) 15 (100%) 15 (100%) 45 (100%)
+#> Sex
+#> n 15 15 15 45
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%) 15 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%) 30 (66.7%)
+#> Ethnicity
+#> n 15 15 15 45
+#> HISPANIC OR LATINO 2 (13.3%) 0 0 2 (4.4%)
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%) 41 (91.1%)
+#> NOT REPORTED 0 0 2 (13.3%) 2 (4.4%)
+#> RACE
+#> n 15 15 15 45
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 2 (13.3%) 1 (6.7%) 3 (6.7%)
+#> ASIAN 8 (53.3%) 10 (66.7%) 8 (53.3%) 26 (57.8%)
+#> BLACK OR AFRICAN AMERICAN 4 (26.7%) 1 (6.7%) 4 (26.7%) 9 (20.0%)
+#> WHITE 3 (20.0%) 2 (13.3%) 2 (13.3%) 7 (15.6%)
+
+
++2. Demographics and Baseline Characteristics without All +Patients +
+To remove the column of total, set the argument
+lbl_overall to NULL.
+run(dmt01, syn_data, lbl_overall = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————
+#> Age (yr)
+#> n 15 15 15
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4)
+#> Median 31.0 35.0 35.0
+#> Min - Max 24 - 40 24 - 57 24 - 49
+#> Age Group
+#> n 15 15 15
+#> <65 15 (100%) 15 (100%) 15 (100%)
+#> Sex
+#> n 15 15 15
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%)
+#> Ethnicity
+#> n 15 15 15
+#> HISPANIC OR LATINO 2 (13.3%) 0 0
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%)
+#> NOT REPORTED 0 0 2 (13.3%)
+#> RACE
+#> n 15 15 15
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 2 (13.3%) 1 (6.7%)
+#> ASIAN 8 (53.3%) 10 (66.7%) 8 (53.3%)
+#> BLACK OR AFRICAN AMERICAN 4 (26.7%) 1 (6.7%) 4 (26.7%)
+#> WHITE 3 (20.0%) 2 (13.3%) 2 (13.3%)
+
+
++3. Demographics and Baseline Characteristics with an +additional study specific continuous variable +
+-
+
- Study specific continuous variables can be added to the standard
+demographics and baseline characteristics summary by editing the
+argument
summaryvars. To add or remove analyses, you need +to pass all variables you would like to include to the argument.
+ - CHEVRON performs the analysis based on the type of variable as +defined in the input data. +
+run(dmt01, syn_data, summaryvars = c("AGE", "AGEGR1", "SEX", "ETHNIC", "RACE", "BBMISI"), lbl_overall = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————
+#> Age
+#> n 15 15 15
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4)
+#> Median 31.0 35.0 35.0
+#> Min - Max 24 - 40 24 - 57 24 - 49
+#> Age Group
+#> n 15 15 15
+#> <65 15 (100%) 15 (100%) 15 (100%)
+#> Sex
+#> n 15 15 15
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%)
+#> Ethnicity
+#> n 15 15 15
+#> HISPANIC OR LATINO 2 (13.3%) 0 0
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%)
+#> NOT REPORTED 0 0 2 (13.3%)
+#> RACE
+#> n 15 15 15
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 2 (13.3%) 1 (6.7%)
+#> ASIAN 8 (53.3%) 10 (66.7%) 8 (53.3%)
+#> BLACK OR AFRICAN AMERICAN 4 (26.7%) 1 (6.7%) 4 (26.7%)
+#> WHITE 3 (20.0%) 2 (13.3%) 2 (13.3%)
+#> Baseline BMI
+#> n 15 15 15
+#> Mean (SD) 29.75 (15.10) 41.08 (26.65) 33.90 (15.39)
+#> Median 37.00 33.70 37.80
+#> Min - Max 6.4 - 47.9 5.3 - 117.9 -3.5 - 59.0
+
+
++4. Demographics and Baseline Characteristics with an +additional study specific categorical variable +
+-
+
- Study specific categorical variables can be added to the standard
+demographics and baseline characteristics summary by editing the
+argument
summaryvars.
+ - To display the values within a categorical variable in pre-specified +order, the categorical variable need to be factorized with pre-specified +order provided as levels. +
+proc_data <- syn_data
+proc_data$adsl <- proc_data$adsl %>%
+ mutate(
+ SEX = reformat(.data$SEX, rule(Male = "M", Female = "F")),
+ BBMIGR1 = factor(case_when(
+ BBMISI < 15 ~ "Very severely underweight",
+ BBMISI >= 15 & BBMISI < 16 ~ "Severely underweight",
+ BBMISI >= 16 & BBMISI < 18.5 ~ "Underweight",
+ BBMISI >= 18.5 & BBMISI < 25 ~ "Normal (healthy weight)",
+ BBMISI >= 25 & BBMISI < 30 ~ "Overweight",
+ BBMISI >= 30 & BBMISI < 35 ~ "Obese Class I (Moderately obese)",
+ BBMISI >= 35 & BBMISI < 40 ~ "Obese Class II (Severely obese)",
+ BBMISI >= 40 ~ "Obese Class III (Very severely obese)"
+ ), levels = c(
+ "Very severely underweight",
+ "Severely underweight",
+ "Underweight",
+ "Normal (healthy weight)",
+ "Overweight",
+ "Obese Class I (Moderately obese)",
+ "Obese Class II (Severely obese)",
+ "Obese Class III (Very severely obese)"
+ ))
+ )
+
+run(dmt01, proc_data, summaryvars = c("AGE", "AGEGR1", "SEX", "ETHNIC", "RACE", "BBMIGR1"), auto_pre = FALSE)
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————
+#> Age
+#> n 15 15 15 45
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4) 34.3 (7.3)
+#> Median 31.0 35.0 35.0 34.0
+#> Min - Max 24 - 40 24 - 57 24 - 49 24 - 57
+#> Age Group
+#> n 15 15 15 45
+#> <65 15 (100%) 15 (100%) 15 (100%) 45 (100%)
+#> Sex
+#> n 15 15 15 45
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%) 15 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%) 30 (66.7%)
+#> Ethnicity
+#> n 15 15 15 45
+#> HISPANIC OR LATINO 2 (13.3%) 0 0 2 (4.4%)
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%) 41 (91.1%)
+#> NOT REPORTED 0 0 2 (13.3%) 2 (4.4%)
+#> RACE
+#> n 15 15 15 45
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 2 (13.3%) 1 (6.7%) 3 (6.7%)
+#> ASIAN 8 (53.3%) 10 (66.7%) 8 (53.3%) 26 (57.8%)
+#> BLACK OR AFRICAN AMERICAN 4 (26.7%) 1 (6.7%) 4 (26.7%) 9 (20.0%)
+#> WHITE 3 (20.0%) 2 (13.3%) 2 (13.3%) 7 (15.6%)
+#> BBMIGR1
+#> n 15 15 15 45
+#> Very severely underweight 4 (26.7%) 1 (6.7%) 1 (6.7%) 6 (13.3%)
+#> Underweight 1 (6.7%) 0 0 1 (2.2%)
+#> Normal (healthy weight) 1 (6.7%) 3 (20.0%) 4 (26.7%) 8 (17.8%)
+#> Overweight 0 1 (6.7%) 1 (6.7%) 2 (4.4%)
+#> Obese Class I (Moderately obese) 0 3 (20.0%) 0 3 (6.7%)
+#> Obese Class II (Severely obese) 4 (26.7%) 1 (6.7%) 3 (20.0%) 8 (17.8%)
+#> Obese Class III (Very severely obese) 5 (33.3%) 6 (40.0%) 6 (40.0%) 17 (37.8%)
+
+5. Demographics and Baseline Characteristics with additional
+vital signs baseline values from
+
+
+
+5. Demographics and Baseline Characteristics with additional
+vital signs baseline values from ADVS or
+ADSUB
+
+To add baseline vital signs or other baseline characteristics to the
+demographics and baseline characteristics summary, manual preprocess of
+input adsl dataset is expected and merge the vital signs
+baseline values from advs (where
+ADVS.ABLFL == "Y") or adsub with
+adsl by unique subject identifier.
+proc_data <- syn_data
+diabpbl <- proc_data$advs %>%
+ filter(ABLFL == "Y" & PARAMCD == "DIABP") %>%
+ mutate(DIABPBL = AVAL) %>%
+ select("STUDYID", "USUBJID", "DIABPBL")
+
+proc_data$adsl <- proc_data$adsl %>%
+ mutate(SEX = reformat(.data$SEX, rule(Male = "M", Female = "F"))) %>%
+ left_join(diabpbl, by = c("STUDYID", "USUBJID"))
+
+run(dmt01, proc_data, summaryvars = c("AGE", "AGEGR1", "SEX", "ETHNIC", "RACE", "DIABPBL"), auto_pre = FALSE)
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Age
+#> n 15 15 15 45
+#> Mean (SD) 31.3 (5.3) 35.1 (9.0) 36.6 (6.4) 34.3 (7.3)
+#> Median 31.0 35.0 35.0 34.0
+#> Min - Max 24 - 40 24 - 57 24 - 49 24 - 57
+#> Age Group
+#> n 15 15 15 45
+#> <65 15 (100%) 15 (100%) 15 (100%) 45 (100%)
+#> Sex
+#> n 15 15 15 45
+#> Male 3 (20.0%) 7 (46.7%) 5 (33.3%) 15 (33.3%)
+#> Female 12 (80.0%) 8 (53.3%) 10 (66.7%) 30 (66.7%)
+#> Ethnicity
+#> n 15 15 15 45
+#> HISPANIC OR LATINO 2 (13.3%) 0 0 2 (4.4%)
+#> NOT HISPANIC OR LATINO 13 (86.7%) 15 (100%) 13 (86.7%) 41 (91.1%)
+#> NOT REPORTED 0 0 2 (13.3%) 2 (4.4%)
+#> RACE
+#> n 15 15 15 45
+#> AMERICAN INDIAN OR ALASKA NATIVE 0 2 (13.3%) 1 (6.7%) 3 (6.7%)
+#> ASIAN 8 (53.3%) 10 (66.7%) 8 (53.3%) 26 (57.8%)
+#> BLACK OR AFRICAN AMERICAN 4 (26.7%) 1 (6.7%) 4 (26.7%) 9 (20.0%)
+#> WHITE 3 (20.0%) 2 (13.3%) 2 (13.3%) 7 (15.6%)
+#> Analysis Value
+#> n 15 15 15 45
+#> Mean (SD) 96.132511 (22.458204) 108.110944 (15.074451) 103.148818 (19.751687) 102.464091 (19.534945)
+#> Median 93.328321 108.951358 102.849019 102.396129
+#> Min - Max 60.58490 - 136.59343 83.44277 - 131.61501 66.05223 - 136.55256 60.58490 - 136.59343
+
+Patient Disposition (
+
+
+Patient Disposition (DST01)
+
+
+
+
++1. Patient Disposition +
+-
+
- The
dst01template produces the +standard patient disposition summary.
+ - The template includes the column of total by default. Use
+
lbl_overall = NULLto suppress the default.
+
+run(dst01, syn_data, lbl_overall = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————
+#> Completed 10 (66.7%) 10 (66.7%) 10 (66.7%)
+#> Discontinued 5 (33.3%) 5 (33.3%) 5 (33.3%)
+#> ADVERSE EVENT 0 0 1 (6.7%)
+#> DEATH 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> LACK OF EFFICACY 2 (13.3%) 0 0
+#> PHYSICIAN DECISION 0 0 1 (6.7%)
+#> PROTOCOL VIOLATION 0 1 (6.7%) 0
+#> WITHDRAWAL BY PARENT/GUARDIAN 1 (6.7%) 0 0
+
+
++2. Patient Disposition (with grouping of +reasons) +
+-
+
- The syntax below produces the standard patient disposition summary +with grouping of the discontinuation reasons. +
- The variable [
ADSL.DCSREASGP] that groups the +discontinuation reasons needs to be derived manually and provided in the +inputadsldataset.
+
+run(dst01, syn_data, detail_vars = list(Discontinued = c("DCSREASGP", "DCSREAS")), lbl_overall = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————
+#> Completed 10 (66.7%) 10 (66.7%) 10 (66.7%)
+#> Discontinued 5 (33.3%) 5 (33.3%) 5 (33.3%)
+#> Safety
+#> ADVERSE EVENT 0 0 1 (6.7%)
+#> DEATH 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> Non-Safety
+#> LACK OF EFFICACY 2 (13.3%) 0 0
+#> PHYSICIAN DECISION 0 0 1 (6.7%)
+#> PROTOCOL VIOLATION 0 1 (6.7%) 0
+#> WITHDRAWAL BY PARENT/GUARDIAN 1 (6.7%) 0 0
+
+
++3. Patient Disposition (adding end of treatment +status) +
+The syntax below adds the end of treatment status to the standard
+patient disposition summary by providing the end of treatment status
+variable to the argument trt_status_var.
+run(dst01, syn_data, trt_status_var = "EOTSTT", lbl_overall = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————
+#> Completed 10 (66.7%) 10 (66.7%) 10 (66.7%)
+#> Discontinued 5 (33.3%) 5 (33.3%) 5 (33.3%)
+#> ADVERSE EVENT 0 0 1 (6.7%)
+#> DEATH 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> LACK OF EFFICACY 2 (13.3%) 0 0
+#> PHYSICIAN DECISION 0 0 1 (6.7%)
+#> PROTOCOL VIOLATION 0 1 (6.7%) 0
+#> WITHDRAWAL BY PARENT/GUARDIAN 1 (6.7%) 0 0
+#> Completed Treatment 8 (53.3%) 4 (26.7%) 5 (33.3%)
+#> Ongoing Treatment 4 (26.7%) 6 (40.0%) 4 (26.7%)
+#> Discontinued Treatment 3 (20.0%) 5 (33.3%) 6 (40.0%)
+
+
++4. Patient Disposition (adding details of study ongoing +status) +
+The syntax adds the details of study ongoing/alive status to the
+standard patient disposition summary by modifying the argument
+detail_vars.
+run(dst01, syn_data, detail_vars = list(Discontinued = "DCSREAS", Ongoing = "STDONS"))
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#> Completed 10 (66.7%) 10 (66.7%) 10 (66.7%) 30 (66.7%)
+#> Discontinued 5 (33.3%) 5 (33.3%) 5 (33.3%) 15 (33.3%)
+#> ADVERSE EVENT 0 0 1 (6.7%) 1 (2.2%)
+#> DEATH 2 (13.3%) 4 (26.7%) 3 (20.0%) 9 (20.0%)
+#> LACK OF EFFICACY 2 (13.3%) 0 0 2 (4.4%)
+#> PHYSICIAN DECISION 0 0 1 (6.7%) 1 (2.2%)
+#> PROTOCOL VIOLATION 0 1 (6.7%) 0 1 (2.2%)
+#> WITHDRAWAL BY PARENT/GUARDIAN 1 (6.7%) 0 0 1 (2.2%)
+
+Deaths (
+
+
+Deaths (DTHT01)
+
+
+
+
++1. Deaths +
+The dtht01 template produces the
+standard deaths output.
+run(dst01, syn_data)
+#> A: Drug X B: Placebo C: Combination All Patients
+#> (N=15) (N=15) (N=15) (N=45)
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#> Completed 10 (66.7%) 10 (66.7%) 10 (66.7%) 30 (66.7%)
+#> Discontinued 5 (33.3%) 5 (33.3%) 5 (33.3%) 15 (33.3%)
+#> ADVERSE EVENT 0 0 1 (6.7%) 1 (2.2%)
+#> DEATH 2 (13.3%) 4 (26.7%) 3 (20.0%) 9 (20.0%)
+#> LACK OF EFFICACY 2 (13.3%) 0 0 2 (4.4%)
+#> PHYSICIAN DECISION 0 0 1 (6.7%) 1 (2.2%)
+#> PROTOCOL VIOLATION 0 1 (6.7%) 0 1 (2.2%)
+#> WITHDRAWAL BY PARENT/GUARDIAN 1 (6.7%) 0 0 1 (2.2%)
+
+
++2. Deaths (adding “Primary Cause of Death” details for +‘Other’ category) +
+
+run(dtht01, syn_data, other_category = TRUE)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————
+#> Total number of deaths 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> Primary Cause of Death
+#> n 2 4 3
+#> Adverse Event 1 (50.0%) 2 (50.0%) 1 (33.3%)
+#> Progressive Disease 1 (50.0%) 0 2 (66.7%)
+#> Other 0 2 (50.0%) 0
+#> LOST TO FOLLOW UP 0 1 (50%) 0
+#> SUICIDE 0 1 (50%) 0NOTE: In order to avoid the warning above and display ‘Other’ as the
+last category under “Primary Cause of Death” right above the detailed
+reasons for “Other”, the user is expected to manually provide levels to
+ADSL.DTHCAT based on categories available in the
+dataset.
+
+
++3. Deaths (adding summary by days from last study drug +administration) +
+Setting time_since_last_dose to TRUE, the
+syntax produces the count of deaths by days from last study drug
+administration as well as the count of deaths by primary cause and days
+from last study drug administration.
+run(dtht01, syn_data, time_since_last_dose = TRUE)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of deaths 2 (13.3%) 4 (26.7%) 3 (20.0%)
+#> Days from last drug administration
+#> n 2 4 3
+#> <=30 2 (100%) 1 (25.0%) 2 (66.7%)
+#> >30 0 3 (75.0%) 1 (33.3%)
+#> Primary cause by days from last study drug administration
+#> <=30
+#> n 2 1 2
+#> Adverse Event 1 (50.0%) 0 1 (50.0%)
+#> Progressive Disease 1 (50.0%) 0 1 (50.0%)
+#> Other 0 1 (100%) 0
+#> >30
+#> n 0 3 1
+#> Adverse Event 0 2 (66.7%) 0
+#> Progressive Disease 0 0 1 (100%)
+#> Other 0 1 (33.3%) 0
+
+ECG Results and Change from Baseline by Visit
+(
+
+
+ECG Results and Change from Baseline by Visit
+(EGT01)
+
+
+
+
++1. ECG Results and Change from Baseline by +Visit +
+The egt01 template produces the
+standard ECG results and change from baseline by visit summary.
+run(egt01, syn_data)
+#> A: Drug X B: Placebo C: Combination
+#> Change from Change from Change from
+#> Value at Visit Baseline Value at Visit Baseline Value at Visit Baseline
+#> Analysis Visit (N=15) (N=15) (N=15) (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Heart Rate
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 76.594 (17.889) 69.899 (18.788) 70.492 (18.175)
+#> Median 77.531 77.174 74.111
+#> Min - Max 46.50 - 106.68 26.42 - 97.69 45.37 - 115.49
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 71.140 (23.441) -5.454 (25.128) 70.958 (14.877) 1.059 (23.345) 67.450 (18.932) -3.043 (23.753)
+#> Median 77.210 -2.152 70.033 -8.403 68.471 0.181
+#> Min - Max 8.53 - 102.63 -50.97 - 36.54 44.85 - 93.79 -25.34 - 60.50 38.90 - 100.05 -52.20 - 33.13
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 69.350 (16.083) -7.244 (28.960) 76.096 (14.958) 6.198 (29.319) 63.694 (12.920) -6.799 (23.949)
+#> Median 65.746 -11.369 75.323 0.255 61.076 -4.954
+#> Min - Max 47.22 - 101.44 -49.59 - 42.91 47.50 - 111.40 -37.51 - 69.34 43.25 - 86.13 -52.70 - 40.76
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 73.894 (24.576) -2.700 (32.079) 67.635 (19.114) -2.263 (29.989) 72.054 (19.308) 1.562 (27.494)
+#> Median 69.296 5.492 68.468 -2.093 68.686 -5.848
+#> Min - Max 44.15 - 131.73 -62.53 - 38.19 31.89 - 108.87 -52.26 - 66.81 32.16 - 109.86 -49.61 - 35.23
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 73.241 (19.256) -3.353 (29.170) 66.524 (25.487) -3.374 (36.024) 66.600 (22.839) -3.892 (24.140)
+#> Median 68.689 0.232 66.397 -11.730 64.969 -6.827
+#> Min - Max 33.71 - 111.54 -55.14 - 65.04 19.66 - 111.29 -60.39 - 61.00 10.35 - 100.88 -50.72 - 26.77
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 61.690 (22.182) -14.904 (30.330) 60.712 (20.025) -9.187 (24.587) 72.683 (23.495) 2.191 (26.654)
+#> Median 57.925 -12.660 60.454 -16.100 77.585 14.635
+#> Min - Max 23.89 - 103.74 -60.00 - 57.24 32.53 - 102.02 -52.56 - 50.96 31.21 - 105.05 -42.90 - 34.64
+#> QT Duration
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 335.294 (123.231) 363.104 (68.160) 347.311 (86.236)
+#> Median 372.731 386.316 348.254
+#> Min - Max 121.28 - 554.97 214.65 - 445.53 170.80 - 508.54
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 357.361 (85.688) 22.067 (144.166) 415.225 (105.425) 52.121 (144.259) 321.078 (107.553) -26.233 (129.135)
+#> Median 344.797 49.432 421.950 62.762 307.962 -17.006
+#> Min - Max 241.22 - 517.39 -207.23 - 245.36 234.11 - 604.72 -190.70 - 364.94 118.36 - 480.29 -363.11 - 163.67
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 344.883 (106.793) 9.589 (174.797) 370.548 (80.862) 7.444 (91.301) 354.129 (95.133) 6.818 (142.397)
+#> Median 312.236 -9.264 388.515 -9.429 365.292 39.930
+#> Min - Max 187.77 - 501.87 -278.91 - 372.71 204.55 - 514.43 -190.58 - 173.87 200.19 - 493.40 -279.46 - 265.56
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 342.062 (92.568) 6.768 (151.505) 326.684 (116.421) -36.420 (145.415) 366.245 (99.106) 18.935 (168.417)
+#> Median 352.930 -22.771 298.353 -78.409 329.688 -21.584
+#> Min - Max 199.40 - 476.04 -230.25 - 303.00 151.05 - 561.23 -205.30 - 293.76 249.42 - 580.81 -252.73 - 410.01
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 371.650 (44.805) 36.356 (139.308) 333.697 (110.377) -29.407 (125.592) 333.181 (96.466) -14.130 (107.622)
+#> Median 375.412 58.958 308.020 -40.987 330.911 -25.820
+#> Min - Max 302.32 - 451.62 -214.07 - 258.04 183.09 - 531.08 -241.72 - 134.12 126.95 - 488.57 -234.92 - 152.49
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 345.504 (130.543) 10.210 (198.224) 309.919 (84.624) -53.185 (105.730) 322.931 (67.801) -24.380 (117.331)
+#> Median 355.730 -23.213 306.219 -12.373 341.988 -26.952
+#> Min - Max 88.38 - 661.12 -271.06 - 539.84 189.01 - 448.58 -256.52 - 91.57 217.51 - 427.16 -291.03 - 171.19
+#> RR Duration
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 1086.908 (363.811) 1050.034 (390.444) 1102.659 (310.359)
+#> Median 1116.849 1089.193 1250.037
+#> Min - Max 626.19 - 1653.12 414.61 - 1721.89 385.51 - 1430.81
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 968.499 (287.811) -118.409 (546.796) 1041.186 (211.201) -8.848 (435.281) 948.491 (213.746) -154.168 (442.882)
+#> Median 961.296 -147.460 1013.786 24.754 965.429 -224.054
+#> Min - Max 358.92 - 1593.51 -1014.82 - 911.82 714.44 - 1417.52 -618.80 - 847.31 513.35 - 1229.09 -736.69 - 843.58
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 932.717 (259.634) -154.191 (331.884) 1139.332 (454.231) 89.298 (582.750) 1021.283 (233.529) -81.376 (415.781)
+#> Median 950.533 -205.949 1068.007 -5.449 964.616 -142.180
+#> Min - Max 409.68 - 1269.35 -649.69 - 473.09 486.51 - 2048.73 -846.72 - 1148.61 667.36 - 1367.25 -647.47 - 616.15
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 1068.865 (319.540) -18.043 (513.412) 1110.882 (259.523) 60.848 (432.700) 1105.918 (306.185) 3.259 (516.734)
+#> Median 1201.998 -65.085 1163.690 51.200 1187.130 30.318
+#> Min - Max 380.49 - 1551.65 -832.86 - 703.74 621.41 - 1453.29 -887.06 - 822.18 446.02 - 1648.32 -984.79 - 816.30
+#> WEEK 4 DAY 29
+#> n 15 15 15 15 15 15
+#> Mean (SD) 1087.915 (205.940) 1.008 (403.039) 1161.681 (293.257) 111.647 (460.979) 992.134 (283.177) -110.525 (334.932)
+#> Median 1084.658 146.611 1055.223 191.008 1028.997 -112.599
+#> Min - Max 697.59 - 1499.17 -801.16 - 402.97 722.35 - 1762.04 -528.27 - 1191.83 497.14 - 1382.12 -597.95 - 757.99
+#> WEEK 5 DAY 36
+#> n 15 15 15 15 15 15
+#> Mean (SD) 1016.880 (424.428) -70.027 (505.078) 1135.131 (224.684) 85.097 (497.679) 1089.527 (238.909) -13.132 (362.606)
+#> Median 962.584 -142.925 1158.815 -9.553 1081.015 16.706
+#> Min - Max 352.97 - 1843.86 -894.83 - 1162.79 714.34 - 1436.68 -843.41 - 992.34 699.72 - 1611.38 -696.03 - 561.53
+
+ECG Abnormalities (Regardless of Abnormality at Baseline)
+(
+
+
+ECG Abnormalities (Regardless of Abnormality at Baseline)
+(EGT02_1)
+
+
+
+
++1. ECG Abnormalities (Regardless of Abnormality at +Baseline) +
+The egt02_1 template produces the
+standard ECG abnormalities summary where the abnormalities are
+summarized regardless of the abnormality at baseline.
+run(egt02_1, syn_data)
+#> Assessment A: Drug X B: Placebo C: Combination
+#> Abnormality (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————
+#> Heart Rate
+#> Low 4/15 (26.7%) 4/15 (26.7%) 4/15 (26.7%)
+#> High 4/15 (26.7%) 3/15 (20%) 3/15 (20%)
+#> QT Duration
+#> Low 2/15 (13.3%) 5/15 (33.3%) 3/15 (20%)
+#> High 3/15 (20%) 6/15 (40%) 2/15 (13.3%)
+#> RR Duration
+#> Low 6/15 (40%) 2/15 (13.3%) 4/15 (26.7%)
+#> High 4/15 (26.7%) 5/15 (33.3%) 2/15 (13.3%)
+
+ECG Abnormalities (Among Subject Without Abnormality at
+Baseline) (
+
+
+ECG Abnormalities (Among Subject Without Abnormality at
+Baseline) (EGT02_2)
+
+
+
+
++1. ECG Abnormalities (Among Subject Without Abnormality at +Baseline) +
+The egt02_2 template produces the
+standard ECG abnormalities summary where the abnormalities are
+summarized among subject without abnormality at baseline.
+run(egt02_2, syn_data)
+#> Assessment A: Drug X B: Placebo C: Combination
+#> Abnormality (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————
+#> Heart Rate
+#> Low 4/15 (26.7%) 4/14 (28.6%) 4/15 (26.7%)
+#> High 3/13 (23.1%) 3/15 (20%) 2/14 (14.3%)
+#> QT Duration
+#> Low 2/12 (16.7%) 5/15 (33.3%) 3/14 (21.4%)
+#> High 3/14 (21.4%) 6/15 (40%) 2/14 (14.3%)
+#> RR Duration
+#> Low 6/15 (40%) 2/13 (15.4%) 4/14 (28.6%)
+#> High 4/13 (30.8%) 5/13 (38.5%) 2/15 (13.3%)
+
+Shift Table of ECG Interval Data - Baseline versus
+Minimum/Maximum Post-Baseline (
+
+
+Shift Table of ECG Interval Data - Baseline versus
+Minimum/Maximum Post-Baseline (EGT03)
+
+
+
+
+
++1. Shift Table of ECG Interval Data - Baseline versus +Minimum Post-Baseline +
+The egt03 template produces the
+standard shift table of ECG interval data - baseline versus minimum
+post-baseline summary.
+proc_data <- log_filter(syn_data, PARAMCD == "HR", "adeg")
+run(egt03, proc_data)
+#> Actual Arm Code Minimum Post-Baseline Assessment
+#> Baseline Reference Range Indicator LOW NORMAL HIGH Missing
+#> ————————————————————————————————————————————————————————————————————————————————
+#> Heart Rate
+#> ARM A (N=15)
+#> LOW 0 0 0 0
+#> NORMAL 4 (26.7%) 9 (60.0%) 0 0
+#> HIGH 0 2 (13.3%) 0 0
+#> Missing 0 0 0 0
+#> ARM B (N=15)
+#> LOW 0 1 (6.7%) 0 0
+#> NORMAL 4 (26.7%) 10 (66.7%) 0 0
+#> HIGH 0 0 0 0
+#> Missing 0 0 0 0
+#> ARM C (N=15)
+#> LOW 0 0 0 0
+#> NORMAL 4 (26.7%) 10 (66.7%) 0 0
+#> HIGH 0 1 (6.7%) 0 0
+#> Missing 0 0 0 0
+
+ECG Actual Values and Changes from Baseline by Visit
+(
+
+
+ECG Actual Values and Changes from Baseline by Visit
+(EGT05_QTCAT)
+
+
+
+
++1. ECG Actual Values and Changes from Baseline by +Visit +
+The egt05_qtcat template produces the
+standard ECG actual values and changes from baseline by visit
+summary.
+run(egt05_qtcat, syn_data)
+#> Parameter
+#> Analysis Visit A: Drug X B: Placebo C: Combination
+#> Category (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————
+#> QT Duration
+#> BASELINE
+#> Value at Visit
+#> n 15 15 15
+#> <=450 msec 13 (86.7%) 15 (100%) 13 (86.7%)
+#> >450 to <=480 msec 1 (6.7%) 0 0
+#> >480 to <=500 msec 0 0 1 (6.7%)
+#> >500 msec 1 (6.7%) 0 1 (6.7%)
+#> WEEK 1 DAY 8
+#> Value at Visit
+#> n 15 15 15
+#> <=450 msec 12 (80.0%) 9 (60.0%) 13 (86.7%)
+#> >450 to <=480 msec 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> >480 to <=500 msec 1 (6.7%) 3 (20.0%) 1 (6.7%)
+#> >500 msec 1 (6.7%) 2 (13.3%) 0
+#> Change from Baseline
+#> n 15 15 15
+#> <=30 msec 7 (46.7%) 6 (40.0%) 9 (60.0%)
+#> >30 to <=60 msec 2 (13.3%) 1 (6.7%) 1 (6.7%)
+#> >60 msec 6 (40.0%) 8 (53.3%) 5 (33.3%)
+#> WEEK 2 DAY 15
+#> Value at Visit
+#> n 15 15 15
+#> <=450 msec 11 (73.3%) 14 (93.3%) 12 (80.0%)
+#> >450 to <=480 msec 2 (13.3%) 0 2 (13.3%)
+#> >480 to <=500 msec 1 (6.7%) 0 1 (6.7%)
+#> >500 msec 1 (6.7%) 1 (6.7%) 0
+#> Change from Baseline
+#> n 15 15 15
+#> <=30 msec 9 (60.0%) 12 (80.0%) 7 (46.7%)
+#> >30 to <=60 msec 2 (13.3%) 0 3 (20.0%)
+#> >60 msec 4 (26.7%) 3 (20.0%) 5 (33.3%)
+#> WEEK 3 DAY 22
+#> Value at Visit
+#> n 15 15 15
+#> <=450 msec 12 (80.0%) 12 (80.0%) 12 (80.0%)
+#> >450 to <=480 msec 3 (20.0%) 1 (6.7%) 1 (6.7%)
+#> >500 msec 0 2 (13.3%) 2 (13.3%)
+#> Change from Baseline
+#> n 15 15 15
+#> <=30 msec 9 (60.0%) 11 (73.3%) 9 (60.0%)
+#> >30 to <=60 msec 1 (6.7%) 1 (6.7%) 0
+#> >60 msec 5 (33.3%) 3 (20.0%) 6 (40.0%)
+#> WEEK 4 DAY 29
+#> Value at Visit
+#> n 15 15 15
+#> <=450 msec 14 (93.3%) 12 (80.0%) 13 (86.7%)
+#> >450 to <=480 msec 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> >480 to <=500 msec 0 0 1 (6.7%)
+#> >500 msec 0 2 (13.3%) 0
+#> Change from Baseline
+#> n 15 15 15
+#> <=30 msec 6 (40.0%) 9 (60.0%) 9 (60.0%)
+#> >30 to <=60 msec 2 (13.3%) 1 (6.7%) 2 (13.3%)
+#> >60 msec 7 (46.7%) 5 (33.3%) 4 (26.7%)
+#> WEEK 5 DAY 36
+#> Value at Visit
+#> n 15 15 15
+#> <=450 msec 12 (80.0%) 15 (100%) 15 (100%)
+#> >450 to <=480 msec 2 (13.3%) 0 0
+#> >500 msec 1 (6.7%) 0 0
+#> Change from Baseline
+#> n 15 15 15
+#> <=30 msec 9 (60.0%) 11 (73.3%) 9 (60.0%)
+#> >30 to <=60 msec 0 3 (20.0%) 2 (13.3%)
+#> >60 msec 6 (40.0%) 1 (6.7%) 4 (26.7%)
+
+
++2. ECG Actual Values and Changes from Baseline by Visit +(removing default analyses) +
+The template have two default analyses of ADEG.AVALCAT1
+and ADEG.CHGCAT1. To keep only the analyses needed, this
+can be achieved by modifying the parameter summaryvars.
+run(egt05_qtcat, syn_data, summaryvars = c("AVALCAT1"))
+#> Parameter
+#> Analysis Visit A: Drug X B: Placebo C: Combination
+#> Category (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————
+#> QT Duration
+#> BASELINE
+#> n 15 15 15
+#> <=450 msec 13 (86.7%) 15 (100%) 13 (86.7%)
+#> >450 to <=480 msec 1 (6.7%) 0 0
+#> >480 to <=500 msec 0 0 1 (6.7%)
+#> >500 msec 1 (6.7%) 0 1 (6.7%)
+#> WEEK 1 DAY 8
+#> n 15 15 15
+#> <=450 msec 12 (80.0%) 9 (60.0%) 13 (86.7%)
+#> >450 to <=480 msec 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> >480 to <=500 msec 1 (6.7%) 3 (20.0%) 1 (6.7%)
+#> >500 msec 1 (6.7%) 2 (13.3%) 0
+#> WEEK 2 DAY 15
+#> n 15 15 15
+#> <=450 msec 11 (73.3%) 14 (93.3%) 12 (80.0%)
+#> >450 to <=480 msec 2 (13.3%) 0 2 (13.3%)
+#> >480 to <=500 msec 1 (6.7%) 0 1 (6.7%)
+#> >500 msec 1 (6.7%) 1 (6.7%) 0
+#> WEEK 3 DAY 22
+#> n 15 15 15
+#> <=450 msec 12 (80.0%) 12 (80.0%) 12 (80.0%)
+#> >450 to <=480 msec 3 (20.0%) 1 (6.7%) 1 (6.7%)
+#> >500 msec 0 2 (13.3%) 2 (13.3%)
+#> WEEK 4 DAY 29
+#> n 15 15 15
+#> <=450 msec 14 (93.3%) 12 (80.0%) 13 (86.7%)
+#> >450 to <=480 msec 1 (6.7%) 1 (6.7%) 1 (6.7%)
+#> >480 to <=500 msec 0 0 1 (6.7%)
+#> >500 msec 0 2 (13.3%) 0
+#> WEEK 5 DAY 36
+#> n 15 15 15
+#> <=450 msec 12 (80.0%) 15 (100%) 15 (100%)
+#> >450 to <=480 msec 2 (13.3%) 0 0
+#> >500 msec 1 (6.7%) 0 0
+
+Study Drug Exposure (
+
+
+Study Drug Exposure (EXT01)
+
+
+
+
++1. Study Drug Exposure +
+-
+
- The
ext01template displays total +number of doses administered and total dose administered by default
+ - The template does not include the column of total by default +
+run(ext01, syn_data)
+#> A: Drug X B: Placebo C: Combination
+#> PARCAT2 (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————
+#> Drug A
+#> Overall duration (days)
+#> n 11 7 7
+#> Mean (SD) 157.5 (67.4) 115.4 (62.8) 98.6 (68.8)
+#> Median 174.0 119.0 89.0
+#> Min - Max 53.0 - 239.0 22.0 - 219.0 1.0 - 182.0
+#> Total dose administered
+#> n 11 7 7
+#> Mean (SD) 6567.3 (1127.1) 7028.6 (1626.1) 6377.1 (863.7)
+#> Median 6720.0 7200.0 6480.0
+#> Min - Max 4800.0 - 8400.0 5280.0 - 9360.0 5280.0 - 7440.0
+#> Drug B
+#> Overall duration (days)
+#> n 4 8 8
+#> Mean (SD) 142.2 (100.3) 105.9 (60.0) 158.2 (96.2)
+#> Median 160.0 95.0 203.0
+#> Min - Max 17.0 - 232.0 37.0 - 211.0 27.0 - 249.0
+#> Total dose administered
+#> n 4 8 8
+#> Mean (SD) 7020.0 (1148.9) 5250.0 (864.7) 5940.0 (1187.9)
+#> Median 6960.0 5160.0 5880.0
+#> Min - Max 5760.0 - 8400.0 4080.0 - 6480.0 4320.0 - 7680.0
+
+Laboratory Test Results and Change from Baseline by Visit
+(
+
+
+Laboratory Test Results and Change from Baseline by Visit
+(LBT01)
+
+
+
+
+
++1. Laboratory Test Results and Change from Baseline by +Visit +
+-
+
- The
lbt01template produces the +standard laboratory test results and change from baseline by visit.
+ - To select the SI/CV/LS results and the panel +(chemistry/hematology/urinalysis/coagulation etc.) to display, user +defines individual filters and apply to input datasets prior to running +CHEVRON. +
+t_lb_chg <- run(lbt01, syn_data)
+head(t_lb_chg, 20)
+#> A: Drug X B: Placebo C: Combination
+#> Change from Change from Change from
+#> Value at Visit Baseline Value at Visit Baseline Value at Visit Baseline
+#> (N=15) (N=15) (N=15) (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 18.655 (12.455) 16.835 (11.080) 22.385 (9.452)
+#> Median 16.040 17.453 25.250
+#> Min - Max 2.43 - 44.06 1.48 - 31.99 0.57 - 37.23
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 16.308 (10.850) -2.348 (17.558) 22.055 (7.537) 5.220 (16.359) 19.574 (9.876) -2.811 (10.902)
+#> Median 14.664 -5.369 22.476 7.252 19.425 -0.995
+#> Min - Max 0.10 - 36.30 -30.18 - 22.66 9.72 - 33.81 -16.82 - 32.33 1.03 - 36.28 -19.61 - 18.45
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 16.646 (10.528) -2.010 (15.773) 20.758 (9.578) 3.923 (14.084) 10.911 (7.721) -11.474 (11.002)
+#> Median 15.470 -6.427 18.499 6.248 9.850 -8.657
+#> Min - Max 0.40 - 35.29 -29.99 - 32.86 1.56 - 42.84 -24.92 - 29.85 0.35 - 25.01 -27.38 - 2.52
+#> WEEK 3 DAY 22
+#> n 15 15 15 15 15 15
+#> Mean (SD) 17.488 (10.679) -1.167 (15.759) 20.055 (8.086) 3.219 (16.285) 18.413 (9.513) -3.973 (9.966)
+#> Median 14.224 1.355 21.852 5.345 19.529 -7.194
+
+Laboratory Abnormalities (
+
+
+Laboratory Abnormalities (LBT04)
+
+
+
+
++1. Laboratory Abnormalities +
+-
+
- The
lbt04template produces the +standard laboratory abnormalities summary.
+ - The template subsets to SI results by default. +
- The laboratory tests and directions of abnormality in this template +is data-driven. Table entries provide the number of patients with a +during treatment laboratory value abnormality in the direction specified +among patients without this abnormality at baseline. +
+run(lbt04, syn_data)
+#> Laboratory Test A: Drug X B: Placebo C: Combination
+#> Direction of Abnormality (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————
+#> CHEMISTRY
+#> Alanine Aminotransferase Measurement
+#> Low 0/7 0/2 1/7 (14.3%)
+#> High 0/7 0/3 0/8
+#> C-Reactive Protein Measurement
+#> Low 0/8 1/2 (50.0%) 0/6
+#> High 3/8 (37.5%) 0/2 0/7
+#> Immunoglobulin A Measurement
+#> Low 0/5 0/8 0/7
+#> High 1/3 (33.3%) 1/8 (12.5%) 0/6
+#> COAGULATION
+#> Alanine Aminotransferase Measurement
+#> Low 0/3 0/6 0/4
+#> High 0/5 0/7 0/4
+#> C-Reactive Protein Measurement
+#> Low 0/5 0/5 1/3 (33.3%)
+#> High 0/5 1/6 (16.7%) 1/4 (25.0%)
+#> Immunoglobulin A Measurement
+#> Low 0/8 0/9 0/6
+#> High 0/8 0/9 1/6 (16.7%)
+#> HEMATOLOGY
+#> Alanine Aminotransferase Measurement
+#> Low 0/4 0/5 0/4
+#> High 0/6 0/5 0/4
+#> C-Reactive Protein Measurement
+#> Low 0/5 0/4 0/3
+#> High 0/5 0/4 0/5
+#> Immunoglobulin A Measurement
+#> Low 0/3 0/4 0/8
+#> High 0/3 0/4 0/7
+
+Laboratory Abnormalities with Single and Replicated Marked
+(
+
+
+Laboratory Abnormalities with Single and Replicated Marked
+(LBT05)
+
+
+
+
+
+
++1. Laboratory Abnormalities with Single and Replicated +Marked +
+-
+
- The
lbt05template produces the +standard laboratory abnormalities summary for marked abnormalities.
+ - The laboratory tests and directions of abnormality in this template +is currently data-driven. The standard metadata for Safety Lab +Standardization will be incorporated in future release. +
+run(lbt05, syn_data)
+#> Laboratory Test A: Drug X B: Placebo C: Combination
+#> Direction of Abnormality (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement (n) 15 14 14
+#> Low
+#> Single, not last 1 (6.7%) 0 4 (28.6%)
+#> Last or replicated 5 (33.3%) 4 (28.6%) 4 (28.6%)
+#> Any Abnormality 6 (40.0%) 4 (28.6%) 8 (57.1%)
+#> High
+#> Single, not last 0 0 0
+#> Last or replicated 0 0 0
+#> Any Abnormality 0 0 0
+#> C-Reactive Protein Measurement (n) 15 15 15
+#> Low
+#> Single, not last 4 (26.7%) 0 3 (20.0%)
+#> Last or replicated 3 (20.0%) 5 (33.3%) 6 (40.0%)
+#> Any Abnormality 7 (46.7%) 5 (33.3%) 9 (60.0%)
+#> High
+#> Single, not last 1 (6.7%) 3 (20.0%) 0
+#> Last or replicated 4 (26.7%) 3 (20.0%) 6 (40.0%)
+#> Any Abnormality 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> Immunoglobulin A Measurement (n) 13 14 14
+#> Low
+#> Single, not last 0 0 0
+#> Last or replicated 0 0 0
+#> Any Abnormality 0 0 0
+#> High
+#> Single, not last 6 (46.2%) 1 (7.1%) 2 (14.3%)
+#> Last or replicated 3 (23.1%) 4 (28.6%) 3 (21.4%)
+#> Any Abnormality 9 (69.2%) 5 (35.7%) 5 (35.7%)
+
+Laboratory Abnormalities by Visit and Baseline Status
+(
+
+
+Laboratory Abnormalities by Visit and Baseline Status
+(LBT06)
+
+
+
+
++1. Laboratory Abnormalities by Visit and Baseline +Status +
+-
+
- The
lbt06template produces the +standard laboratory abnormalities by visit and baseline status +summary.
+
+run(lbt06, syn_data)
+#> Visit
+#> Abnormality at Visit A: Drug X B: Placebo C: Combination
+#> Baseline Status (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> WEEK 1 DAY 8
+#> Low
+#> Not low 0/1 0/6 0/1
+#> Low 0/1 0/1 0/1
+#> Total 0/2 0/7 0/2
+#> High
+#> Not high 0/2 0/7 0/2
+#> High 0/0 0/0 0/0
+#> Total 0/2 0/7 0/2
+#> WEEK 2 DAY 15
+#> Low
+#> Not low 0/3 0/2 0/2
+#> Low 0/0 0/0 0/0
+#> Total 0/3 0/2 0/2
+#> High
+#> Not high 0/3 0/2 0/2
+#> High 0/0 0/0 0/0
+#> Total 0/3 0/2 0/2
+#> WEEK 3 DAY 22
+#> Low
+#> Not low 0/5 0/3 1/6 (16.7%)
+#> Low 0/0 0/0 0/0
+#> Total 0/5 0/3 1/6 (16.7%)
+#> High
+#> Not high 0/5 0/3 0/6
+#> High 0/0 0/0 0/0
+#> Total 0/5 0/3 0/6
+#> WEEK 4 DAY 29
+#> Low
+#> Not low 0/3 0/1 0/1
+#> Low 0/3 0/2 0/0
+#> Total 0/6 0/3 0/1
+#> High
+#> Not high 0/6 0/3 0/1
+#> High 0/0 0/0 0/0
+#> Total 0/6 0/3 0/1
+#> WEEK 5 DAY 36
+#> Low
+#> Not low 0/2 0/2 0/5
+#> Low 0/1 0/1 0/0
+#> Total 0/3 0/3 0/5
+#> High
+#> Not high 0/3 0/3 0/5
+#> High 0/0 0/0 0/0
+#> Total 0/3 0/3 0/5
+#> C-Reactive Protein Measurement
+#> WEEK 1 DAY 8
+#> Low
+#> Not low 0/5 0/3 0/3
+#> Low 0/0 0/1 0/0
+#> Total 0/5 0/4 0/3
+#> High
+#> Not high 0/5 0/3 1/3 (33.3%)
+#> High 0/0 0/1 0/0
+#> Total 0/5 0/4 1/3 (33.3%)
+#> WEEK 2 DAY 15
+#> Low
+#> Not low 0/8 0/2 0/0
+#> Low 0/0 0/0 0/1
+#> Total 0/8 0/2 0/1
+#> High
+#> Not high 1/8 (12.5%) 0/1 0/1
+#> High 0/0 0/1 0/0
+#> Total 1/8 (12.5%) 0/2 0/1
+#> WEEK 3 DAY 22
+#> Low
+#> Not low 0/5 0/4 0/4
+#> Low 0/0 1/1 (100%) 0/2
+#> Total 0/5 1/5 (20%) 0/6
+#> High
+#> Not high 1/5 (20%) 1/5 (20%) 0/6
+#> High 0/0 0/0 0/0
+#> Total 1/5 (20%) 1/5 (20%) 0/6
+#> WEEK 4 DAY 29
+#> Low
+#> Not low 0/2 1/2 (50%) 1/3 (33.3%)
+#> Low 0/0 0/0 0/0
+#> Total 0/2 1/2 (50%) 1/3 (33.3%)
+#> High
+#> Not high 0/2 0/2 0/3
+#> High 0/0 0/0 0/0
+#> Total 0/2 0/2 0/3
+#> WEEK 5 DAY 36
+#> Low
+#> Not low 0/2 0/2 0/5
+#> Low 0/0 1/1 (100%) 0/1
+#> Total 0/2 1/3 (33.3%) 0/6
+#> High
+#> Not high 1/2 (50%) 0/3 0/6
+#> High 0/0 0/0 0/0
+#> Total 1/2 (50%) 0/3 0/6
+#> Immunoglobulin A Measurement
+#> WEEK 1 DAY 8
+#> Low
+#> Not low 0/6 0/6 0/2
+#> Low 0/0 0/0 0/0
+#> Total 0/6 0/6 0/2
+#> High
+#> Not high 0/5 1/6 (16.7%) 0/2
+#> High 0/1 0/0 0/0
+#> Total 0/6 1/6 (16.7%) 0/2
+#> WEEK 2 DAY 15
+#> Low
+#> Not low 0/3 0/7 0/4
+#> Low 0/0 0/0 0/0
+#> Total 0/3 0/7 0/4
+#> High
+#> Not high 0/3 0/7 1/4 (25%)
+#> High 0/0 0/0 0/0
+#> Total 0/3 0/7 1/4 (25%)
+#> WEEK 3 DAY 22
+#> Low
+#> Not low 0/4 0/5 0/9
+#> Low 0/0 0/0 0/0
+#> Total 0/4 0/5 0/9
+#> High
+#> Not high 0/3 0/5 0/8
+#> High 0/1 0/0 0/1
+#> Total 0/4 0/5 0/9
+#> WEEK 4 DAY 29
+#> Low
+#> Not low 0/2 0/6 0/4
+#> Low 0/0 0/0 0/0
+#> Total 0/2 0/6 0/4
+#> High
+#> Not high 1/1 (100%) 0/6 0/3
+#> High 0/1 0/0 0/1
+#> Total 1/2 (50%) 0/6 0/4
+#> WEEK 5 DAY 36
+#> Low
+#> Not low 0/6 0/5 0/5
+#> Low 0/0 0/0 0/0
+#> Total 0/6 0/5 0/5
+#> High
+#> Not high 0/5 0/5 0/5
+#> High 0/1 0/0 0/0
+#> Total 0/6 0/5 0/5
+
+Laboratory Test Results with Highest
+
+
+Laboratory Test Results with Highest NCI CTCAE
+Grade Post-Baseline (LBT07)
+
+
+
+1. Laboratory Test Results with Highest
+
+
+
+
+1. Laboratory Test Results with Highest
+NCI CTCAE Grade Post-Baseline
+
+-
+
- The
lbt07template produces the +standard laboratory test results with highestNCI CTCAE+grade post-baseline summary.
+ - The laboratory tests and grades in this template is currently
+data-driven. The standard metadata for possible lab tests and
+corresponding
NCI CTCAEgrade will be incorporated in +future release.
+
+run(lbt07, syn_data)
+#> Parameter
+#> Direction of Abnormality A: Drug X B: Placebo C: Combination
+#> Highest NCI CTCAE Grade (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement (n) 15 15 15
+#> LOW
+#> 1 3 (20.0%) 0 0
+#> 2 2 (13.3%) 1 (6.7%) 1 (6.7%)
+#> 3 1 (6.7%) 1 (6.7%) 6 (40.0%)
+#> 4 3 (20.0%) 2 (13.3%) 3 (20.0%)
+#> Any 9 (60.0%) 4 (26.7%) 10 (66.7%)
+#> C-Reactive Protein Measurement (n) 15 15 15
+#> LOW
+#> 1 2 (13.3%) 1 (6.7%) 2 (13.3%)
+#> 2 5 (33.3%) 2 (13.3%) 5 (33.3%)
+#> 3 3 (20.0%) 4 (26.7%) 3 (20.0%)
+#> 4 0 1 (6.7%) 0
+#> Any 10 (66.7%) 8 (53.3%) 10 (66.7%)
+#> HIGH
+#> 1 3 (20.0%) 1 (6.7%) 1 (6.7%)
+#> 2 4 (26.7%) 4 (26.7%) 2 (13.3%)
+#> 3 1 (6.7%) 2 (13.3%) 4 (26.7%)
+#> 4 0 1 (6.7%) 0
+#> Any 8 (53.3%) 8 (53.3%) 7 (46.7%)
+#> Immunoglobulin A Measurement (n) 15 15 15
+#> HIGH
+#> 1 3 (20.0%) 1 (6.7%) 1 (6.7%)
+#> 2 5 (33.3%) 4 (26.7%) 2 (13.3%)
+#> 3 3 (20.0%) 3 (20.0%) 2 (13.3%)
+#> 4 0 0 1 (6.7%)
+#> Any 11 (73.3%) 8 (53.3%) 6 (40.0%)
+
+Laboratory Test Results Shift Table - Highest
+
+
+
+Laboratory Test Results Shift Table - Highest
+NCI-CTCAE Grade Post-Baseline by Baseline
+NCI-CTCAE Grade (LBT14)
+
+
+
+1. Laboratory Test Results Shift Table - Highest
+
+
+
+
+1. Laboratory Test Results Shift Table - Highest
+NCI-CTCAE Grade Post-Baseline by Baseline
+NCI-CTCAE Grade (High)
+
+To produce the standard laboratory test results shift table - highest
+NCI-CTCAE grade post-baseline by baseline
+NCI-CTCAE grade summary for high abnormalities, use the
+lbt14 template and set the parameter
+direction to high.
+run(lbt14, syn_data, direction = "high")
+#> Baseline Toxicity Grade A: Drug X B: Placebo C: Combination
+#> Post-baseline NCI-CTCAE Grade (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> Not High 15 15 15
+#> Not High 15 (100%) 15 (100%) 15 (100%)
+#> C-Reactive Protein Measurement
+#> Not High 15 13 14
+#> Not High 7 (46.7%) 7 (53.8%) 8 (57.1%)
+#> 1 3 (20.0%) 1 (7.7%) 1 (7.1%)
+#> 2 4 (26.7%) 3 (23.1%) 1 (7.1%)
+#> 3 1 (6.7%) 1 (7.7%) 4 (28.6%)
+#> 4 0 1 (7.7%) 0
+#> 1 0 0 1
+#> 2 0 0 1 (100%)
+#> 3 0 1 0
+#> 2 0 1 (100%) 0
+#> 4 0 1 0
+#> 3 0 1 (100%) 0
+#> Immunoglobulin A Measurement
+#> Not High 12 14 13
+#> Not High 3 (25.0%) 7 (50.0%) 8 (61.5%)
+#> 1 3 (25.0%) 1 (7.1%) 1 (7.7%)
+#> 2 3 (25.0%) 3 (21.4%) 2 (15.4%)
+#> 3 3 (25.0%) 3 (21.4%) 2 (15.4%)
+#> 1 2 0 1
+#> Not High 1 (50.0%) 0 1 (100%)
+#> 2 1 (50.0%) 0 0
+#> 3 0 0 1
+#> 4 0 0 1 (100%)
+#> 4 1 1 0
+#> 2 1 (100%) 1 (100%) 0
+
+2. Laboratory Test Results Shift Table - Highest
+
+
+
+
+2. Laboratory Test Results Shift Table - Highest
+NCI-CTCAE Grade Post-Baseline by Baseline
+NCI-CTCAE Grade (Low)
+
+To produce the standard laboratory test results shift table - highest
+NCI-CTCAE grade post-baseline by baseline
+NCI-CTCAE grade summary for high abnormalities, use the
+lbt14 template and the argument
+direction is low by default.
+run(lbt14, syn_data)
+#> Baseline Toxicity Grade A: Drug X B: Placebo C: Combination
+#> Post-baseline NCI-CTCAE Grade (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> Not Low 12 12 14
+#> Not Low 5 (41.7%) 8 (66.7%) 5 (35.7%)
+#> 1 3 (25.0%) 0 0
+#> 2 2 (16.7%) 1 (8.3%) 1 (7.1%)
+#> 3 0 1 (8.3%) 5 (35.7%)
+#> 4 2 (16.7%) 2 (16.7%) 3 (21.4%)
+#> 1 1 2 0
+#> Not Low 1 (100%) 2 (100%) 0
+#> 2 1 1 0
+#> Not Low 0 1 (100%) 0
+#> 4 1 (100%) 0 0
+#> 3 1 0 1
+#> 3 1 (100%) 0 1 (100%)
+#> C-Reactive Protein Measurement
+#> Not Low 14 13 12
+#> Not Low 5 (35.7%) 7 (53.8%) 4 (33.3%)
+#> 1 2 (14.3%) 0 2 (16.7%)
+#> 2 5 (35.7%) 2 (15.4%) 4 (33.3%)
+#> 3 2 (14.3%) 3 (23.1%) 2 (16.7%)
+#> 4 0 1 (7.7%) 0
+#> 1 0 0 2
+#> Not Low 0 0 1 (50.0%)
+#> 2 0 0 1 (50.0%)
+#> 2 0 1 0
+#> 1 0 1 (100%) 0
+#> 3 1 1 1
+#> 3 1 (100%) 1 (100%) 1 (100%)
+#> Immunoglobulin A Measurement
+#> Not Low 15 15 15
+#> Not Low 15 (100%) 15 (100%) 15 (100%)
+
+3. Laboratory Test Results Shift Table - Highest
+
+
+
+
+3. Laboratory Test Results Shift Table - Highest
+NCI-CTCAE Grade Post-Baseline by Baseline
+NCI-CTCAE Grade (High) Without Patients with Missing
+Baseline
+
+To exclude patients with missing baseline grade, set the argument
+gr_missing to excl.
+run(lbt14, syn_data, direction = "high", gr_missing = "excl")
+#> Baseline Toxicity Grade A: Drug X B: Placebo C: Combination
+#> Post-baseline NCI-CTCAE Grade (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> Not High 15 15 15
+#> Not High 15 (100%) 15 (100%) 15 (100%)
+#> C-Reactive Protein Measurement
+#> Not High 15 13 14
+#> Not High 7 (46.7%) 7 (53.8%) 8 (57.1%)
+#> 1 3 (20.0%) 1 (7.7%) 1 (7.1%)
+#> 2 4 (26.7%) 3 (23.1%) 1 (7.1%)
+#> 3 1 (6.7%) 1 (7.7%) 4 (28.6%)
+#> 4 0 1 (7.7%) 0
+#> 1 0 0 1
+#> 2 0 0 1 (100%)
+#> 3 0 1 0
+#> 2 0 1 (100%) 0
+#> 4 0 1 0
+#> 3 0 1 (100%) 0
+#> Immunoglobulin A Measurement
+#> Not High 12 14 13
+#> Not High 3 (25.0%) 7 (50.0%) 8 (61.5%)
+#> 1 3 (25.0%) 1 (7.1%) 1 (7.7%)
+#> 2 3 (25.0%) 3 (21.4%) 2 (15.4%)
+#> 3 3 (25.0%) 3 (21.4%) 2 (15.4%)
+#> 1 2 0 1
+#> Not High 1 (50.0%) 0 1 (100%)
+#> 2 1 (50.0%) 0 0
+#> 3 0 0 1
+#> 4 0 0 1 (100%)
+#> 4 1 1 0
+#> 2 1 (100%) 1 (100%) 0
+
+4. Laboratory Test Results Shift Table - Highest
+
+
+
+
+4. Laboratory Test Results Shift Table - Highest
+NCI-CTCAE Grade Post-Baseline by Baseline
+NCI-CTCAE Grade (Low) with Missing Baseline Considered as
+Grade 0
+
+To count patients with missing baseline grade as grade 0, set the
+argument gr_missing to gr_0.
+run(lbt14, syn_data, gr_missing = "gr_0")
+#> Baseline Toxicity Grade A: Drug X B: Placebo C: Combination
+#> Post-baseline NCI-CTCAE Grade (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> 1 1 2 0
+#> Not Low 1 (100%) 2 (100%) 0
+#> 2 1 1 0
+#> Not Low 0 1 (100%) 0
+#> 4 1 (100%) 0 0
+#> 3 1 0 1
+#> 3 1 (100%) 0 1 (100%)
+#> Not Low 12 12 14
+#> Not Low 5 (41.7%) 8 (66.7%) 5 (35.7%)
+#> 1 3 (25.0%) 0 0
+#> 2 2 (16.7%) 1 (8.3%) 1 (7.1%)
+#> 3 0 1 (8.3%) 5 (35.7%)
+#> 4 2 (16.7%) 2 (16.7%) 3 (21.4%)
+#> C-Reactive Protein Measurement
+#> 1 0 0 2
+#> 1 0 0 1 (50.0%)
+#> 3 0 0 1 (50.0%)
+#> 2 0 1 0
+#> 2 0 1 (100%) 0
+#> 3 1 1 1
+#> 3 1 (100%) 1 (100%) 1 (100%)
+#> Not Low 14 13 12
+#> Not Low 5 (35.7%) 7 (53.8%) 4 (33.3%)
+#> 1 2 (14.3%) 0 2 (16.7%)
+#> 2 5 (35.7%) 2 (15.4%) 4 (33.3%)
+#> 3 2 (14.3%) 3 (23.1%) 2 (16.7%)
+#> 4 0 1 (7.7%) 0
+#> Immunoglobulin A Measurement
+#> Not Low 15 15 15
+#> Not Low 15 (100%) 15 (100%) 15 (100%)
+
+4. Laboratory Test Results Shift Table - Highest
+
+
+
+
+4. Laboratory Test Results Shift Table - Highest
+NCI-CTCAE Grade Post-Baseline by Baseline
+NCI-CTCAE Grade (with fill in of grades)
+
+To display all possible grades even if they do not occur in the data,
+set the argument prune_0 to FALSE.
+run(lbt14, syn_data, direction = "high", prune_0 = FALSE)
+#> Baseline Toxicity Grade A: Drug X B: Placebo C: Combination
+#> Post-baseline NCI-CTCAE Grade (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————
+#> Alanine Aminotransferase Measurement
+#> Not High 15 15 15
+#> Not High 15 (100%) 15 (100%) 15 (100%)
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 1 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 2 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 3 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 4 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> Missing 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> C-Reactive Protein Measurement
+#> Not High 15 13 14
+#> Not High 7 (46.7%) 7 (53.8%) 8 (57.1%)
+#> 1 3 (20.0%) 1 (7.7%) 1 (7.1%)
+#> 2 4 (26.7%) 3 (23.1%) 1 (7.1%)
+#> 3 1 (6.7%) 1 (7.7%) 4 (28.6%)
+#> 4 0 1 (7.7%) 0
+#> Missing 0 0 0
+#> 1 0 0 1
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 1 (100%)
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 2 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 3 0 1 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 1 (100%) 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 4 0 1 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 1 (100%) 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> Missing 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> Immunoglobulin A Measurement
+#> Not High 12 14 13
+#> Not High 3 (25.0%) 7 (50.0%) 8 (61.5%)
+#> 1 3 (25.0%) 1 (7.1%) 1 (7.7%)
+#> 2 3 (25.0%) 3 (21.4%) 2 (15.4%)
+#> 3 3 (25.0%) 3 (21.4%) 2 (15.4%)
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 1 2 0 1
+#> Not High 1 (50.0%) 0 1 (100%)
+#> 1 0 0 0
+#> 2 1 (50.0%) 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 2 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> 3 0 0 1
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 1 (100%)
+#> Missing 0 0 0
+#> 4 1 1 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 1 (100%) 1 (100%) 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+#> Missing 0 0 0
+#> Not High 0 0 0
+#> 1 0 0 0
+#> 2 0 0 0
+#> 3 0 0 0
+#> 4 0 0 0
+#> Missing 0 0 0
+
+Medical History (
+
+
+Medical History (MHT01)
+
+
+
+
++1. Medical History +
+-
+
- The
mht01template displays medical +conditions by MedDRA system organ class and Preferred Name by +default.
+ - The default treatment variable is
"ADSL.ARM".
+ - The user is expected to use filter to subset medical conditions +prior to or on entering study. +
- By default, the template produces the overall ‘total number of +conditions’ as well as the ‘total number of conditions’ per body system +after the summary of patients. 5）This template currently does not +support sorting MedDRA system organ class and preferred names by order +of frequency. +
+run(mht01, syn_data)
+#> MedDRA System Organ Class A: Drug X B: Placebo C: Combination
+#> MedDRA Preferred Term (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one condition 13 (86.7%) 14 (93.3%) 15 (100%)
+#> Total number of conditions 58 59 99
+#> cl A
+#> Total number of patients with at least one condition 7 (46.7%) 6 (40.0%) 10 (66.7%)
+#> Total number of conditions 8 11 16
+#> trm A_2/2 5 (33.3%) 6 (40.0%) 6 (40.0%)
+#> trm A_1/2 3 (20.0%) 1 (6.7%) 6 (40.0%)
+#> cl B
+#> Total number of patients with at least one condition 12 (80.0%) 11 (73.3%) 12 (80.0%)
+#> Total number of conditions 24 21 32
+#> trm B_3/3 8 (53.3%) 6 (40.0%) 7 (46.7%)
+#> trm B_1/3 5 (33.3%) 6 (40.0%) 8 (53.3%)
+#> trm B_2/3 5 (33.3%) 6 (40.0%) 5 (33.3%)
+#> cl C
+#> Total number of patients with at least one condition 8 (53.3%) 6 (40.0%) 11 (73.3%)
+#> Total number of conditions 10 13 22
+#> trm C_2/2 6 (40.0%) 4 (26.7%) 8 (53.3%)
+#> trm C_1/2 4 (26.7%) 4 (26.7%) 5 (33.3%)
+#> cl D
+#> Total number of patients with at least one condition 10 (66.7%) 7 (46.7%) 13 (86.7%)
+#> Total number of conditions 16 14 29
+#> trm D_1/3 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> trm D_2/3 6 (40.0%) 2 (13.3%) 7 (46.7%)
+#> trm D_3/3 2 (13.3%) 5 (33.3%) 7 (46.7%)
+
+
++2. Medical History showing additional column ‘All +Patients’ +
+
+run(mht01, syn_data, lbl_overall = "All Patients")
+#> MedDRA System Organ Class A: Drug X B: Placebo C: Combination All Patients
+#> MedDRA Preferred Term (N=15) (N=15) (N=15) (N=45)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one condition 13 (86.7%) 14 (93.3%) 15 (100%) 42 (93.3%)
+#> Total number of conditions 58 59 99 216
+#> cl A
+#> Total number of patients with at least one condition 7 (46.7%) 6 (40.0%) 10 (66.7%) 23 (51.1%)
+#> Total number of conditions 8 11 16 35
+#> trm A_2/2 5 (33.3%) 6 (40.0%) 6 (40.0%) 17 (37.8%)
+#> trm A_1/2 3 (20.0%) 1 (6.7%) 6 (40.0%) 10 (22.2%)
+#> cl B
+#> Total number of patients with at least one condition 12 (80.0%) 11 (73.3%) 12 (80.0%) 35 (77.8%)
+#> Total number of conditions 24 21 32 77
+#> trm B_3/3 8 (53.3%) 6 (40.0%) 7 (46.7%) 21 (46.7%)
+#> trm B_1/3 5 (33.3%) 6 (40.0%) 8 (53.3%) 19 (42.2%)
+#> trm B_2/3 5 (33.3%) 6 (40.0%) 5 (33.3%) 16 (35.6%)
+#> cl C
+#> Total number of patients with at least one condition 8 (53.3%) 6 (40.0%) 11 (73.3%) 25 (55.6%)
+#> Total number of conditions 10 13 22 45
+#> trm C_2/2 6 (40.0%) 4 (26.7%) 8 (53.3%) 18 (40.0%)
+#> trm C_1/2 4 (26.7%) 4 (26.7%) 5 (33.3%) 13 (28.9%)
+#> cl D
+#> Total number of patients with at least one condition 10 (66.7%) 7 (46.7%) 13 (86.7%) 30 (66.7%)
+#> Total number of conditions 16 14 29 59
+#> trm D_1/3 4 (26.7%) 4 (26.7%) 7 (46.7%) 15 (33.3%)
+#> trm D_2/3 6 (40.0%) 2 (13.3%) 7 (46.7%) 15 (33.3%)
+#> trm D_3/3 2 (13.3%) 5 (33.3%) 7 (46.7%) 14 (31.1%)
+
+Major Protocol Deviations (
+
+
+Major Protocol Deviations (PDT01)
+
+
+
+
++1. Major Protocol Deviations +
+-
+
- The
pdt01template produces the +standard major protocol deviations output.
+ - Users are expected to filter
addvto only include +records whereDVCAT == "MAJOR"in pre-processing.
+
+proc_data <- syn_data
+proc_data$addv <- proc_data$addv %>%
+ filter(DVCAT == "MAJOR")
+
+run(pdt01, proc_data)
+#> Category A: Drug X B: Placebo C: Combination
+#> Description (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one major protocol deviation 2 (13.3%) 4 (26.7%) 0
+#> Total number of major protocol deviations 2 5 0
+#> EXCLUSION CRITERIA
+#> Active or untreated or other excluded cns metastases 0 1 (6.7%) 0
+#> Pregnancy criteria 0 1 (6.7%) 0
+#> INCLUSION CRITERIA
+#> Ineligible cancer type or current cancer stage 1 (6.7%) 0 0
+#> MEDICATION
+#> Discontinued study drug for unspecified reason 0 1 (6.7%) 0
+#> Received prohibited concomitant medication 0 1 (6.7%) 0
+#> PROCEDURAL
+#> Eligibility-related test not done/out of window 0 1 (6.7%) 0
+#> Failure to sign updated ICF within two visits 1 (6.7%) 0 0
+
+Reasons for Major Protocol Deviations Related to
+Epidemic/Pandemic (
+
+
+Reasons for Major Protocol Deviations Related to
+Epidemic/Pandemic (PDT02)
+
+
+
+
++1. Reasons for Major Protocol Deviations Related to +Epidemic/Pandemic +
+-
+
- The
pdt02template produces the +reasons for major protocol deviations related to epidemic/pandemic +summary.
+ - By default,
ADDV.DVREASprovides the reason and +ADDV.DVTERMprovides the description.
+ - By default,
addvhas been filtered to include only +records that meet the condition +AEPRELFL == "Y" & DVCAT == "MAJOR".
+
+run(pdt02, syn_data)
+#> Primary Reason A: Drug X B: Placebo C: Combination
+#> Description (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Total number of patients with at least one major protocol deviation related to epidemic/pandemic 1 (6.7%) 0 0
+#> Total number of major protocol deviations related to epidemic/pandemic 1 0 0
+#> Site action due to epidemic/pandemic 1 (6.7%) 0 0
+#> Failure to sign updated ICF within two visits 1 (6.7%) 0 0
+
+Duration of Exposure for Risk Management Plan
+(
+
+
+Duration of Exposure for Risk Management Plan
+(RMPT01)
+
+
+
+
++1. Duration of Exposure for Risk Management +Plan +
+The rmpt01 template produces the
+standard duration of exposure output for the Risk Management Plan
+(RMP).
Person time is the sum of exposure across all patients in days.
+
+run(rmpt01, syn_data)
+#> Patients Person time
+#> Duration of exposure (N=45) (N=45)
+#> —————————————————————————————————————————————————————————————
+#> < 1 month 4 (8.9%) 67
+#> 1 to <3 months 13 (28.9%) 837
+#> 3 to <6 months 13 (28.9%) 1728
+#> >=6 months 15 (33.3%) 3281
+#> Total patients number/person time 45 (100.0%) 5913
+
+Extent of Exposure by Age Group and Gender for Risk
+Management Plan (
+
+
+Extent of Exposure by Age Group and Gender for Risk
+Management Plan (RMPT03)
+
+
+
+
+
++1. Extent of Exposure by Age Group and Gender for Risk +Management Plan +
+The rmpt03 template produces the
+standard extent of exposure by age group and gender output for the Risk
+Management Plan (RMP).
By default, the AGEGR1 variable is used as the age
+group. If AGEGR1 is available in ADSL only but
+not in ADEX, it needs to be added to ADEX
+first.
+proc_data <- syn_data
+proc_data <- propagate(proc_data, "adsl", "AGEGR1", "USUBJID")
+#>
+#> Updating: adae with: AGEGR1
+#> Updating: adsaftte with: AGEGR1
+#> Updating: adcm with: AGEGR1
+#> Updating: addv with: AGEGR1
+#> Updating: adeg with: AGEGR1
+#> Updating: adex with: AGEGR1
+#> Updating: adlb with: AGEGR1
+#> Updating: admh with: AGEGR1
+#> Skipping: adrs
+#> Updating: adsub with: AGEGR1
+#> Skipping: adtte
+#> Updating: advs with: AGEGR1
+run(rmpt03, proc_data)
+#> F M All Genders
+#> Patients Person time Patients Person time Patients Person time
+#> Age Group (N=30) (N=30) (N=15) (N=15) (N=45) (N=45)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> <65 30 (100.0%) 4088 15 (100.0%) 1825 45 (100.0%) 5913
+#> Total patients number/person time 30 (100.0%) 4088 15 (100.0%) 1825 45 (100.0%) 5913Any other study specific age group can be used by editing the
+parameter summaryvars. For all RMP tables, if
+the variable specified per summaryvars is unavailable in
+ADEX, it needs to be added to ADEX first.
+proc_data <- syn_data
+proc_data$adsl <- proc_data$adsl %>%
+ mutate(
+ AGEGR2 = with_label(
+ factor(case_when(
+ AAGE < 18 ~ "<18",
+ AAGE >= 18 & AAGE <= 65 ~ "18 - 65",
+ AAGE > 65 ~ ">65",
+ ), levels = c("<18", "18 - 65", ">65")),
+ "Age Group 2"
+ )
+ )
+proc_data <- propagate(proc_data, "adsl", "AGEGR2", "USUBJID")
+#>
+#> Updating: adae with: AGEGR2
+#> Updating: adsaftte with: AGEGR2
+#> Updating: adcm with: AGEGR2
+#> Updating: addv with: AGEGR2
+#> Updating: adeg with: AGEGR2
+#> Updating: adex with: AGEGR2
+#> Updating: adlb with: AGEGR2
+#> Updating: admh with: AGEGR2
+#> Updating: adrs with: AGEGR2
+#> Updating: adsub with: AGEGR2
+#> Updating: adtte with: AGEGR2
+#> Updating: advs with: AGEGR2
+run(rmpt03, proc_data, summaryvars = "AGEGR2")
+#> F M All Genders
+#> Patients Person time Patients Person time Patients Person time
+#> Age Group 2 (N=30) (N=30) (N=15) (N=15) (N=45) (N=45)
+#> —————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> 18 - 65 30 (100.0%) 4088 15 (100.0%) 1825 45 (100.0%) 5913
+#> Total patients number/person time 30 (100.0%) 4088 15 (100.0%) 1825 45 (100.0%) 5913
+
+Extent of Exposure by Ethnic Origin for Risk Management Plan
+(
+
+
+Extent of Exposure by Ethnic Origin for Risk Management Plan
+(RMPT04)
+
+
+
+
++1. Extent of Exposure by Ethnic Origin for Risk Management +Plan +
+The rmpt04 template produces the
+standard extent of exposure by ethnic origin output for the Risk
+Management Plan (RMP).
+run(rmpt04, syn_data)
+#> Patients Person time
+#> ETHNIC (N=45) (N=45)
+#> —————————————————————————————————————————————————————————————
+#> HISPANIC OR LATINO 2 (4.4%) 309
+#> NOT HISPANIC OR LATINO 41 (91.1%) 5555
+#> NOT REPORTED 2 (4.4%) 49
+#> Total patients number/person time 45 (100.0%) 5913
+
+Extent of Exposure by Race for Risk Management Plan
+(
+
+
+Extent of Exposure by Race for Risk Management Plan
+(RMPT05)
+
+
+
+
++1. Extent of Exposure by Race for Risk Management +Plan +
+The rmpt05 template produces the
+standard extent of exposure by race output for the Risk Management Plan
+(RMP).
+run(rmpt05, syn_data)
+#> Patients Person time
+#> RACE (N=45) (N=45)
+#> —————————————————————————————————————————————————————————————
+#> ASIAN 26 (57.8%) 3309
+#> BLACK OR AFRICAN AMERICAN 9 (20.0%) 1139
+#> WHITE 7 (15.6%) 1231
+#> AMERICAN INDIAN OR ALASKA NATIVE 3 (6.7%) 234
+#> Total patients number/person time 45 (100.0%) 5913
+
+Best Overall Response (
+
+
+Best Overall Response (RSPT01)
+
+
+
+
++1. Best Overall Response +
+-
+
- The
rspt01template produces the +standard best overall response output.
+ - The template syntax is built based on
RECIST 1.1. By +default, the subjects with response results of"CR"or +"PR"are considered as responders.
+ - Users are expected to pre-process the input analysis data and select
+the parameter to be analyzed, i.e., best overall response by
+investigator or best overall response by
BICR.
+ - Unstratified analysis is provided by default. +
+proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI", "adrs")
+
+run(rspt01, proc_data, ref_group = NULL, perform_analysis = "unstrat", strata = NULL)
+#> Warning in stats::prop.test(tbl, correct = FALSE): Chi-squared approximation
+#> may be incorrect
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————————
+#> Responders 10 (66.7%) 9 (60.0%) 11 (73.3%)
+#> 95% CI (Wald, with correction) (39.5, 93.9) (31.9, 88.1) (47.6, 99.0)
+#> Unstratified Analysis
+#> Difference in Response rate (%) -6.7 6.7
+#> 95% CI (Wald, with correction) (-47.7, 34.4) (-32.7, 46.0)
+#> p-value (Chi-Squared Test) 0.7048 0.6903
+#> Odds Ratio (95% CI) 0.75 (0.17 - 3.33) 1.37 (0.29 - 6.60)
+#> Complete Response (CR) 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 95% CI (Wald, with correction) (0.95, 52.38) (0.95, 52.38) (18.09, 75.25)
+#> Partial Response (PR) 6 (40.0%) 5 (33.3%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (11.87, 68.13) (6.14, 60.52) (0.95, 52.38)
+#> Stable Disease (SD) 5 (33.3%) 6 (40.0%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (6.14, 60.52) (11.87, 68.13) (0.95, 52.38)
+
+
+
++2. Best Overall Response (Ordering of treatment +groups) +
+-
+
- By default, the first level or value of
arm_var+(default to"ADSL.ARM"unless specified) is treated as the +reference group without specification.
+ - To apply user-defined reference group, please provide the value from
+the treatment variable to the argument
ref_group, e.g., +ref_group = "PLACEBO".
+ - Since
rtablesdisplays the reference group at the very +left column, the order of displayed treatment groups may not be exactly +the same as the order factorized, depending on which group is selected +as the reference group. See below for examples:
+
Factorized trt order |
+ref_group |
+Displayed trt order |
+Reference group used in analysis | +
|---|---|---|---|
| ARM C, ARM B, ARM A | +NULL | +ARM C, ARM B, ARM A | +ARM C | +
| NULL | +ARM B | +ARM B, ARM A, ARM C | +ARM B | +
| ARM C, ARM B, ARM A | +ARM B | +ARM B, ARM C, ARM A | +ARM B | +
+
+
++3. Best Overall Response (selecting sections to +display) +
+-
+
- The section of
Odds Ratiocan be suppressed with the +argumentodds_ratio = FALSE.
+ - The section of
Difference in response ratecan be +suppressed with the argumentperform_analysis = NULL.
+
+proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI", "adrs")
+
+run(rspt01, proc_data, odds_ratio = FALSE, perform_analysis = NULL)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————
+#> Responders 10 (66.7%) 9 (60.0%) 11 (73.3%)
+#> 95% CI (Wald, with correction) (39.5, 93.9) (31.9, 88.1) (47.6, 99.0)
+#> Complete Response (CR) 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 95% CI (Wald, with correction) (0.95, 52.38) (0.95, 52.38) (18.09, 75.25)
+#> Partial Response (PR) 6 (40.0%) 5 (33.3%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (11.87, 68.13) (6.14, 60.52) (0.95, 52.38)
+#> Stable Disease (SD) 5 (33.3%) 6 (40.0%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (6.14, 60.52) (11.87, 68.13) (0.95, 52.38)
+
+
++4. Best Overall Response (with stratified +analysis) +
+-
+
- A stratified analysis can be added by specifying the argument
+
perform_analysis = "strat"and providing the stratification +variable to the argumentstrata. The argument +stratais expected ifperform_analysisis set +to include stratified analysis.
+ - The stratification variables are expected to be available in
+
adrs.
+ - If both unstratified and stratified analysis are required, use
+
perform_analysis = c("unstrat", "strat")+
+
+proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI", "adrs")
+
+run(rspt01, proc_data, perform_analysis = "strat", strata = c("STRATA1", "STRATA2"))
+#> Warning in prop_diff_cmh(rsp, grp, strata, conf_level): Less than 5
+#> observations in some strata.
+#> Warning in prop_diff_cmh(rsp, grp, strata, conf_level): Less than 5
+#> observations in some strata.
+#> Warning in prop_cmh(tbl): <5 data points in some strata. CMH test may be
+#> incorrect.
+#> Warning in prop_cmh(tbl): <5 data points in some strata. CMH test may be
+#> incorrect.
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————————————————————
+#> Responders 10 (66.7%) 9 (60.0%) 11 (73.3%)
+#> 95% CI (Wald, with correction) (39.5, 93.9) (31.9, 88.1) (47.6, 99.0)
+#> Stratified Analysis
+#> Difference in Response rate (%) -11.0 22.5
+#> 95% CI (CMH, without correction) (-42.7, 20.7) (-3.5, 48.5)
+#> p-value (Cochran-Mantel-Haenszel Test) 0.5731 0.3088
+#> Odds Ratio (95% CI) 0.75 (0.17 - 3.33) 1.37 (0.29 - 6.60)
+#> Complete Response (CR) 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 95% CI (Wald, with correction) (0.95, 52.38) (0.95, 52.38) (18.09, 75.25)
+#> Partial Response (PR) 6 (40.0%) 5 (33.3%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (11.87, 68.13) (6.14, 60.52) (0.95, 52.38)
+#> Stable Disease (SD) 5 (33.3%) 6 (40.0%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (6.14, 60.52) (11.87, 68.13) (0.95, 52.38)
+
+
+
+
+
+
+
+
+
+
++5. Best Overall Response (modifying analysis details like +type of confidence interval, alpha level, test for +p-value) +
+-
+
- The level of the confidence intervals is defined by the argument
+
conf_level.
+ - The methods to construct confidence interval and p-value are
+controlled by the argument
methods. It is a named list with +five optional sub-arguments. For example, +methods = list(prop_conf_method = "wald", diff_conf_method = "wald", strat_diff_conf_method = "ha", diff_pval_method = "fisher", strat_diff_pval_method = "schouten")+
+
See table below for what each argument controls and the available +method options:
+| Arguments | +Methods Controlled | +Methods Options | +
|---|---|---|
prop_conf_method |
+proportion confidence interval | +
+"waldcc" (default), "wald",
+etc. |
+
diff_conf_method |
+unstratified difference confidence interval | +
+"waldcc" (default), "wald",
+etc. |
+
diff_pval_method |
+unstratified p-value for odds ratio | +
+"chisq" (default),
+"fisher"
+ |
+
strat_diff_conf_method |
+stratified difference confidence interval | +
+"cmh" (default), "ha"
+ |
+
strat_diff_pval_method |
+stratified p-value for odds ratio | +
+"cmh" (default),
+"schouten"
+ |
+
See in the table below the method options for estimates of +proportions and the associated statistical methods:
+| Method Options | +Statistical Methods | +
|---|---|
"clopper-pearson" |
+Clopper-Pearson | +
"wald" |
+Wald, without correction | +
"waldcc" |
+Wald, with correction | +
"wilson" |
+Wilson, without correction | +
"strat_wilson" |
+Stratified Wilson, without correction | +
"wilsonc" |
+Wilson, with correction | +
"strat_wilsonc" |
+Stratified Wilson, with correction | +
"agresti-coull" |
+Agresti-Coull | +
"jeffreys" |
+Jeffreys | +
See in the table below the method options for estimates of proportion +difference and the associated statistical methods:
+| Method Options | +Statistical Methods | +
|---|---|
"cmh" |
+
+CMH, without correction |
+
"wald" |
+Wald, with correction | +
"waldcc" |
+Wald, without correction | +
"ha" |
+Anderson-Hauck | +
"newcombe" |
+Newcombe, without correction | +
"newcombecc" |
+Newcombe, with correction | +
"strat_wilsonc" |
+Stratified Wilson, with correction | +
"strat_newcombe" |
+Stratified Newcombe, without correction | +
"strat_newcombecc" |
+Stratified Newcombe, with correction | +
See in the table below the method options for testing proportion +difference and the associated statistical methods:
+| Method Options | +Statistical Methods | +
|---|---|
"chisq" |
+Chi-Squared test | +
"fisher" |
+the Fisher’s exact test | +
"cmh" |
+stratified Cochran-Mantel-Haenszel test | +
"shouten" |
+Chi-Squared test with Schouten correction | +
An example:
+
+proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI", "adrs")
+
+run(rspt01, proc_data,
+ conf_level = 0.90,
+ methods = list(
+ prop_conf_method = "wald",
+ diff_conf_method = "wald",
+ diff_pval_method = "fisher"
+ )
+)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————————————
+#> Responders 10 (66.7%) 9 (60.0%) 11 (73.3%)
+#> 90% CI (Wald, without correction) (46.6, 86.7) (39.2, 80.8) (54.6, 92.1)
+#> Unstratified Analysis
+#> Difference in Response rate (%) -6.7 6.7
+#> 90% CI (Wald, without correction) (-35.5, 22.2) (-20.8, 34.1)
+#> p-value (Fisher's Exact Test) 1.0000 1.0000
+#> Odds Ratio (95% CI) 0.75 (0.17 - 3.33) 1.37 (0.29 - 6.60)
+#> Complete Response (CR) 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 90% CI (Wald, without correction) (7.89, 45.45) (7.89, 45.45) (25.48, 67.85)
+#> Partial Response (PR) 6 (40.0%) 5 (33.3%) 4 (26.7%)
+#> 90% CI (Wald, without correction) (19.19, 60.81) (13.31, 53.35) (7.89, 45.45)
+#> Stable Disease (SD) 5 (33.3%) 6 (40.0%) 4 (26.7%)
+#> 90% CI (Wald, without correction) (13.31, 53.35) (19.19, 60.81) (7.89, 45.45)
+
+
++6. Best Overall Response (modifying the definition of +overall response) +
+The following example shows how to customize the definition of +responder, e.g, consider only complete response as response.
+
+proc_data <- log_filter(syn_data, PARAMCD == "BESRSPI", "adrs")
+
+preprocess(rspt01) <- function(adam_db, ...) {
+ adam_db$adrs <- adam_db$adrs %>%
+ mutate(RSP_LAB = tern::d_onco_rsp_label(.data$AVALC)) %>%
+ mutate(IS_RSP = .data$AVALC %in% c("CR"))
+ adam_db
+}
+
+run(rspt01, proc_data)
+#> Warning in stats::prop.test(tbl, correct = FALSE): Chi-squared approximation
+#> may be incorrect
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————————————————————————
+#> Responders 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 95% CI (Wald, with correction) (1.0, 52.4) (1.0, 52.4) (18.1, 75.2)
+#> Unstratified Analysis
+#> Difference in Response rate (%) 0.0 20.0
+#> 95% CI (Wald, with correction) (-38.3, 38.3) (-20.4, 60.4)
+#> p-value (Chi-Squared Test) 1.0000 0.2557
+#> Odds Ratio (95% CI) 1.00 (0.20 - 5.04) 2.41 (0.52 - 11.10)
+#> Complete Response (CR) 4 (26.7%) 4 (26.7%) 7 (46.7%)
+#> 95% CI (Wald, with correction) (0.95, 52.38) (0.95, 52.38) (18.09, 75.25)
+#> Partial Response (PR) 6 (40.0%) 5 (33.3%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (11.87, 68.13) (6.14, 60.52) (0.95, 52.38)
+#> Stable Disease (SD) 5 (33.3%) 6 (40.0%) 4 (26.7%)
+#> 95% CI (Wald, with correction) (6.14, 60.52) (11.87, 68.13) (0.95, 52.38)
+
+Time-to-event Summary (
+
+
+Time-to-event Summary (TTET01)
+
+
+
+
++1. Time-to-event Summary +
+-
+
- The
ttet01template produces the +standard time-to-event summary.
+ - Users are expected to subset the parameter of interest
+(e.g.
PARAMCD == "PFS") in pre-processing.
+ - Please see the section of Best Overall Response +(Ordering of treatment groups) to find out more about the ordering +of treatment groups and reference group. +
- Unstratified analysis is provided by default. +
- Survival estimations and difference in survival are both provided by +default. +
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (MONTHS)
+#> Median 8.6 6.2 8.4
+#> 95% CI (7.3, NE) (4.8, 7.6) (7.0, NE)
+#> 25% and 75%-ile 3.8, NE 4.7, 8.4 5.8, NE
+#> Range 1.2 to 9.5 {1} 0.9 to 9.1 0.9 to 9.5 {1}
+#> Unstratified Analysis
+#> p-value (log-rank) 0.0973 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 95% CI (0.85, 5.60) (0.38, 2.94)
+#> 6 MONTHS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 95% CI (50.95, 95.71) (28.09, 78.58) (50.95, 95.71)
+#> Difference in Event Free Rate -20.00 0.00
+#> 95% CI (-53.74, 13.74) (-31.65, 31.65)
+#> p-value (Z-test) 0.2453 1.0000
+#> ————————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> ————————————————————————————————————————————————————————————————————————————————————
+
+
+
++2. Time-to-event Summary (selecting sections to +display) +
+To suspend the section of earliest contributing events, use
+summarize_event = FALSE.
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data, summarize_event = FALSE)
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (MONTHS)
+#> Median 8.6 6.2 8.4
+#> 95% CI (7.3, NE) (4.8, 7.6) (7.0, NE)
+#> 25% and 75%-ile 3.8, NE 4.7, 8.4 5.8, NE
+#> Range 1.2 to 9.5 {1} 0.9 to 9.1 0.9 to 9.5 {1}
+#> Unstratified Analysis
+#> p-value (log-rank) 0.0973 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 95% CI (0.85, 5.60) (0.38, 2.94)
+#> 6 MONTHS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 95% CI (50.95, 95.71) (28.09, 78.58) (50.95, 95.71)
+#> Difference in Event Free Rate -20.00 0.00
+#> 95% CI (-53.74, 13.74) (-31.65, 31.65)
+#> p-value (Z-test) 0.2453 1.0000
+#> ————————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> ————————————————————————————————————————————————————————————————————————————————————To select either survival estimations or difference in survival or
+both, please specify in the argument method. -
+surv calls out the analysis of patients remaining at risk,
+event free rate and corresponding 95% confidence interval of the rates.
+- surv_diff calls out the analysis of difference in event
+free rate, the 95% confidence interval of the difference and its
+corresponding p-value. - both calls out both.
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data, method = "surv")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (MONTHS)
+#> Median 8.6 6.2 8.4
+#> 95% CI (7.3, NE) (4.8, 7.6) (7.0, NE)
+#> 25% and 75%-ile 3.8, NE 4.7, 8.4 5.8, NE
+#> Range 1.2 to 9.5 {1} 0.9 to 9.1 0.9 to 9.5 {1}
+#> Unstratified Analysis
+#> p-value (log-rank) 0.0973 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 95% CI (0.85, 5.60) (0.38, 2.94)
+#> 6 MONTHS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 95% CI (50.95, 95.71) (28.09, 78.58) (50.95, 95.71)
+#> ————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> ————————————————————————————————————————————————————————————————————————————————
+
+
++3. Time-to-event Summary (modifying analysis details like +confidence interval type, ties, and alpha level) +
+-
+
- The level of the confidence intervals is defined by the argument
+
conf_level.
+ - The type of confidence interval is defined in the argument
+
conf_type. Options are"plain"(default), +"log"and"log-log".
+ - Handling of ties is specified in the argument
ties. +Options are"efron"(default),"breslow"or +"exact".
+
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data, conf_level = 0.90, conf_type = "log-log", ties = "efron")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (MONTHS)
+#> Median 8.6 6.2 8.4
+#> 90% CI (3.8, NE) (4.7, 7.6) (5.8, NE)
+#> 25% and 75%-ile 3.8, NE 4.7, 8.4 5.8, NE
+#> Range 1.2 to 9.5 {1} 0.9 to 9.1 0.9 to 9.5 {1}
+#> Unstratified Analysis
+#> p-value (log-rank) 0.0973 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 90% CI (0.99, 4.81) (0.45, 2.50)
+#> 6 MONTHS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 90% CI (49.25, 87.30) (30.65, 71.60) (49.25, 87.30)
+#> Difference in Event Free Rate -20.00 0.00
+#> 90% CI (-48.31, 8.31) (-26.56, 26.56)
+#> p-value (Z-test) 0.2453 1.0000
+#> ———————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> ———————————————————————————————————————————————————————————————————————————————————
+
+
++4. Time-to-event Summary (with stratified +analysis) +
+-
+
- A stratified analysis can be added by specifying the argument
+
perform_analysis = "strat"and providing the stratification +variable to the argumentstrata. The argument +stratais expected ifperform_analysisis set +to include stratified analysis.
+ - The stratification variables are expected to be available in
+
adrs.
+ - If unstratified and stratified analysis are both required, users can
+use
perform_analysis = c("unstrat", "strat").
+
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data, perform_analysis = "strat", strata = "STRATA1")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (MONTHS)
+#> Median 8.6 6.2 8.4
+#> 95% CI (7.3, NE) (4.8, 7.6) (7.0, NE)
+#> 25% and 75%-ile 3.8, NE 4.7, 8.4 5.8, NE
+#> Range 1.2 to 9.5 {1} 0.9 to 9.1 0.9 to 9.5 {1}
+#> Stratified Analysis
+#> p-value (log-rank) 0.0649 0.8901
+#> Hazard Ratio 2.52 1.08
+#> 95% CI (0.92, 6.93) (0.36, 3.22)
+#> 6 MONTHS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 95% CI (50.95, 95.71) (28.09, 78.58) (50.95, 95.71)
+#> Difference in Event Free Rate -20.00 0.00
+#> 95% CI (-53.74, 13.74) (-31.65, 31.65)
+#> p-value (Z-test) 0.2453 1.0000
+#> ————————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> ————————————————————————————————————————————————————————————————————————————————————
+
+
+
++5. Time-to-event Summary (modifying time point for the +“survival at xx months” analysis) +
+The time point for the “survival at xx months” analysis can be
+modified by specifying the argument time_point. By default,
+the function takes AVAL from adtte in days and
+converts it to months. The survival estimates are then summarized in
+month, and the numeric values should be provided in months to
+time_point.
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data, perform_analysis = "unstrat", time_point = c(3, 6))
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (MONTHS)
+#> Median 8.6 6.2 8.4
+#> 95% CI (7.3, NE) (4.8, 7.6) (7.0, NE)
+#> 25% and 75%-ile 3.8, NE 4.7, 8.4 5.8, NE
+#> Range 1.2 to 9.5 {1} 0.9 to 9.1 0.9 to 9.5 {1}
+#> Unstratified Analysis
+#> p-value (log-rank) 0.0973 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 95% CI (0.85, 5.60) (0.38, 2.94)
+#> 3 MONTHS
+#> Patients remaining at risk 12 12 13
+#> Event Free Rate (%) 80.00 80.00 86.67
+#> 95% CI (59.76, 100.00) (59.76, 100.00) (69.46, 100.00)
+#> Difference in Event Free Rate 0.00 6.67
+#> 95% CI (-28.63, 28.63) (-19.90, 33.23)
+#> p-value (Z-test) 1.0000 0.6228
+#> 6 MONTHS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 95% CI (50.95, 95.71) (28.09, 78.58) (50.95, 95.71)
+#> Difference in Event Free Rate -20.00 0.00
+#> 95% CI (-53.74, 13.74) (-31.65, 31.65)
+#> p-value (Z-test) 0.2453 1.0000
+#> —————————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> —————————————————————————————————————————————————————————————————————————————————————The following example shows how to specify the time point in +user-defined unit.
+
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+preprocess(ttet01) <- function(adam_db, dataset = "adtte",
+ ...) {
+ adam_db[[dataset]] <- adam_db[[dataset]] %>%
+ mutate(
+ AVALU = "DAYS",
+ IS_EVENT = .data$CNSR == 0,
+ IS_NOT_EVENT = .data$CNSR == 1,
+ EVNT1 = factor(
+ case_when(
+ IS_EVENT == TRUE ~ render_safe("{Patient_label} with event (%)"),
+ IS_EVENT == FALSE ~ render_safe("{Patient_label} without event (%)")
+ ),
+ levels = render_safe(c("{Patient_label} with event (%)", "{Patient_label} without event (%)"))
+ ),
+ EVNTDESC = factor(.data$EVNTDESC)
+ )
+
+ adam_db
+}
+
+run(ttet01, proc_data, perform_analysis = "unstrat", time_point = c(91, 183))
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (DAYS)
+#> Median 261.9 187.7 256.3
+#> 95% CI (221.9, NE) (144.7, 232.2) (212.0, NE)
+#> 25% and 75%-ile 114.9, NE 141.9, 254.4 175.0, NE
+#> Range 37.2 to 288.3 {1} 28.0 to 276.6 26.4 to 288.1 {1}
+#> Unstratified Analysis
+#> p-value (log-rank) 0.0973 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 95% CI (0.85, 5.60) (0.38, 2.94)
+#> 91 DAYS
+#> Patients remaining at risk 12 12 13
+#> Event Free Rate (%) 80.00 80.00 86.67
+#> 95% CI (59.76, 100.00) (59.76, 100.00) (69.46, 100.00)
+#> Difference in Event Free Rate 0.00 6.67
+#> 95% CI (-28.63, 28.63) (-19.90, 33.23)
+#> p-value (Z-test) 1.0000 0.6228
+#> 183 DAYS
+#> Patients remaining at risk 11 8 11
+#> Event Free Rate (%) 73.33 53.33 73.33
+#> 95% CI (50.95, 95.71) (28.09, 78.58) (50.95, 95.71)
+#> Difference in Event Free Rate -20.00 0.00
+#> 95% CI (-53.74, 13.74) (-31.65, 31.65)
+#> p-value (Z-test) 0.2453 1.0000
+#> —————————————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> —————————————————————————————————————————————————————————————————————————————————————————
+
+
++6. Time-to-event Summary (modifying the p-value method for +testing hazard ratio) +
+The default p-value method for testing hazard ratio is “log-rank”.
+Alternative methods can be requested by specifying the argument
+pval_method and options include, log-rank
+(default), wald or likelihood. The syntax
+currently does not allow requesting more than one p-value.
Note that ttet01 has been modified in the previous
+example (i.e., preprocess(ttet01) has been overridden); to
+access the default template, try chevron::ttet01.
+proc_data <- log_filter(syn_data, PARAMCD == "PFS", "adtte")
+
+run(ttet01, proc_data, pval_method = "wald")
+#> A: Drug X B: Placebo C: Combination
+#> (N=15) (N=15) (N=15)
+#> ————————————————————————————————————————————————————————————————————————————————————————
+#> Patients with event (%) 7 (46.7%) 12 (80%) 8 (53.3%)
+#> Earliest contributing event
+#> Death 5 11 7
+#> Disease Progression 2 1 1
+#> Patients without event (%) 8 (53.3%) 3 (20%) 7 (46.7%)
+#> Time to Event (DAYS)
+#> Median 261.9 187.7 256.3
+#> 95% CI (221.9, NE) (144.7, 232.2) (212.0, NE)
+#> 25% and 75%-ile 114.9, NE 141.9, 254.4 175.0, NE
+#> Range 37.2 to 288.3 {1} 28.0 to 276.6 26.4 to 288.1 {1}
+#> Unstratified Analysis
+#> p-value (wald) 0.1053 0.9111
+#> Hazard Ratio 2.18 1.06
+#> 95% CI (0.85, 5.60) (0.38, 2.94)
+#> 6 DAYS
+#> Patients remaining at risk 15 15 15
+#> Event Free Rate (%) 100.00 100.00 100.00
+#> 95% CI (100.00, 100.00) (100.00, 100.00) (100.00, 100.00)
+#> 12 DAYS
+#> Patients remaining at risk 15 15 15
+#> Event Free Rate (%) 100.00 100.00 100.00
+#> 95% CI (100.00, 100.00) (100.00, 100.00) (100.00, 100.00)
+#> ————————————————————————————————————————————————————————————————————————————————————————
+#>
+#> {1} - Censored observation: range maximum
+#> ————————————————————————————————————————————————————————————————————————————————————————
+
+Vital Signs (
+
+
+Vital Signs (VST01)
+
+
+
+
++1. Vital Sign Results and Change from Baseline by +Visit +
+
+t_vs_chg <- run(vst01, syn_data)
+head(t_vs_chg, 20)
+#> A: Drug X B: Placebo C: Combination
+#> Change from Change from Change from
+#> Value at Visit Baseline Value at Visit Baseline Value at Visit Baseline
+#> (N=15) (N=15) (N=15) (N=15) (N=15) (N=15)
+#> ——————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————————
+#> Diastolic Blood Pressure
+#> SCREENING
+#> n 15 0 15 0 15 0
+#> Mean (SD) 94.385 (17.067) NE (NE) 106.381 (20.586) NE (NE) 106.468 (12.628) NE (NE)
+#> Median 94.933 NE 111.133 NE 108.359 NE
+#> Min - Max 55.71 - 122.00 NE - NE 60.21 - 131.91 NE - NE 83.29 - 127.17 NE - NE
+#> BASELINE
+#> n 15 15 15
+#> Mean (SD) 96.133 (22.458) 108.111 (15.074) 103.149 (19.752)
+#> Median 93.328 108.951 102.849
+#> Min - Max 60.58 - 136.59 83.44 - 131.62 66.05 - 136.55
+#> WEEK 1 DAY 8
+#> n 15 15 15 15 15 15
+#> Mean (SD) 98.977 (21.359) 2.844 (28.106) 104.110 (16.172) -4.001 (21.867) 100.826 (19.027) -2.323 (25.018)
+#> Median 92.447 -4.066 107.703 3.227 103.058 -2.476
+#> Min - Max 67.55 - 130.37 -32.82 - 47.68 70.91 - 132.89 -52.94 - 28.63 70.04 - 128.68 -55.15 - 41.81
+#> WEEK 2 DAY 15
+#> n 15 15 15 15 15 15
+#> Mean (SD) 99.758 (14.477) 3.626 (21.189) 97.473 (17.296) -10.638 (20.831) 94.272 (16.961) -8.877 (27.229)
+#> Median 101.498 1.731 99.501 -9.727 96.789 -10.155
+
+Vital Signs Abnormalities (Regardless of Abnormality at
+Baseline) (
+
+
+Vital Signs Abnormalities (Regardless of Abnormality at
+Baseline) (VST02_1)
+
+
+
+
++1. Vital Sign Abnormalities (Regardless of Abnormality at +Baseline) +
+
+run(vst02_1, syn_data)
+#> Assessment A: Drug X B: Placebo C: Combination
+#> Abnormality (N=15) (N=15) (N=15)
+#> —————————————————————————————————————————————————————————————————————————
+#> Diastolic Blood Pressure
+#> Low 8/15 (53.3%) 9/15 (60%) 8/15 (53.3%)
+#> High 10/15 (66.7%) 5/15 (33.3%) 8/15 (53.3%)
+#> Pulse Rate
+#> Low 9/15 (60%) 3/15 (20%) 5/15 (33.3%)
+#> High 2/15 (13.3%) 6/15 (40%) 5/15 (33.3%)
+#> Respiratory Rate
+#> Low 13/15 (86.7%) 10/15 (66.7%) 13/15 (86.7%)
+#> High 7/15 (46.7%) 10/15 (66.7%) 11/15 (73.3%)
+#> Systolic Blood Pressure
+#> Low 7/15 (46.7%) 9/15 (60%) 11/15 (73.3%)
+#> High 10/15 (66.7%) 9/15 (60%) 9/15 (60%)
+#> Temperature
+#> Low 12/15 (80%) 13/15 (86.7%) 11/15 (73.3%)
+#> High 14/15 (93.3%) 12/15 (80%) 14/15 (93.3%)
+#> Weight
+#> Low 3/15 (20%) 3/15 (20%) 4/15 (26.7%)
+#> High 4/15 (26.7%) 4/15 (26.7%) 5/15 (33.3%)
+
+Vital Signs Abnormalities (Among Subject Without Abnormality
+at Baseline) (
+
+
+Vital Signs Abnormalities (Among Subject Without Abnormality
+at Baseline) (VST02_2)
+
+
+
+
++1. Vital Sign Abnormalities (Among Subject Without +Abnormality at Baseline) +
+
+run(vst02_2, syn_data)
+#> Assessment A: Drug X B: Placebo C: Combination
+#> Abnormality (N=15) (N=15) (N=15)
+#> ———————————————————————————————————————————————————————————————————————
+#> Diastolic Blood Pressure
+#> Low 6/11 (54.5%) 9/15 (60%) 6/12 (50%)
+#> High 8/12 (66.7%) 4/11 (36.4%) 7/13 (53.8%)
+#> Pulse Rate
+#> Low 9/15 (60%) 3/15 (20%) 5/13 (38.5%)
+#> High 2/14 (14.3%) 4/12 (33.3%) 5/15 (33.3%)
+#> Respiratory Rate
+#> Low 7/9 (77.8%) 7/11 (63.6%) 11/12 (91.7%)
+#> High 6/14 (42.9%) 7/11 (63.6%) 9/13 (69.2%)
+#> Systolic Blood Pressure
+#> Low 5/13 (38.5%) 8/12 (66.7%) 10/14 (71.4%)
+#> High 8/13 (61.5%) 8/13 (61.5%) 8/13 (61.5%)
+#> Temperature
+#> Low 8/10 (80%) 7/9 (77.8%) 8/10 (80%)
+#> High 8/8 (100%) 7/8 (87.5%) 12/13 (92.3%)
+#> Weight
+#> Low 3/15 (20%) 3/15 (20%) 3/14 (21.4%)
+#> High 4/14 (28.6%) 4/15 (26.7%) 5/14 (35.7%)
+
++LISTINGS +
+
+
+Glossary of Adverse Event Preferred Terms and
+Investigator-Specified Terms (
+
+
+Glossary of Adverse Event Preferred Terms and
+Investigator-Specified Terms (AEL01_NOLLT)
+
+
+
+
++1. Glossary of Adverse Event Preferred Terms and +Investigator-Specified Terms +
+-
+
- The
ael01_nollttemplate produces the +standard glossary of adverse event preferred terms and +investigator-specified terms.
+ - The example below uses
headfunction to print only the +first 10 lines of the output.
+
+l_ae_nollt <- run(ael01_nollt, syn_data)
+head(l_ae_nollt, 10)
+#> MedDRA System Organ Class MedDRA Preferred Term Reported Term for the Adverse Event
+#> ———————————————————————————————————————————————————————————————————————————————————————
+#> cl A.1 dcd A.1.1.1.1 trm A.1.1.1.1
+#> dcd A.1.1.1.2 trm A.1.1.1.2
+#> cl B.1 dcd B.1.1.1.1 trm B.1.1.1.1
+#> cl B.2 dcd B.2.1.2.1 trm B.2.1.2.1
+#> dcd B.2.2.3.1 trm B.2.2.3.1
+#> cl C.1 dcd C.1.1.1.3 trm C.1.1.1.3
+#> cl C.2 dcd C.2.1.2.1 trm C.2.1.2.1
+#> cl D.1 dcd D.1.1.1.1 trm D.1.1.1.1
+#> dcd D.1.1.4.2 trm D.1.1.4.2
+#> cl D.2 dcd D.2.1.5.3 trm D.2.1.5.3
+
+ +Graphics +
+
+
+Forest Plot for Odds Ratio
+(
+
+
+Forest Plot for Odds Ratio
+(FSTG01)
+
+
+
+
++1. Forest Plot for Odds Ratio (with subgroup +analysis) +
+-
+
- The
fstg01template produces the +standard forest plot for odds ratio.
+ - Users are expected to subset the parameter of interest
+(e.g.
PARAMCD == "BESRSPI") in pre-processing.
+ - Users are expected to subset the arm variable to keep only the two
+arms to compare
+(e.g.
ARM %in% c("A: Drug X", "B: Placebo")).
+ - By default, the plots displays a subgroup analysis for
+
"SEX","AGEGR1"and"RACE".
+ - Unstratified analysis is provided by default. +
- The plots displays by default the Total number of subjects, the odd +ratio and the 95% confidence interval, and, for each arm, the number of +subject, the number of responders and the proportion of responders. +
+proc_data <- log_filter(
+ syn_data,
+ PARAMCD == "BESRSPI" & ARM %in% c("A: Drug X", "B: Placebo"), "adrs"
+)
+run(fstg01, proc_data)
+
+
++2. Forest Plot for Odds Ratio (with a user-defined +confidence level) +
+The confidence level of the confidence interval can be adjusted by
+the conf_level argument.
+run(fstg01, proc_data, conf_level = 0.90)
+
++3. Forest Plot for Odds Ratio (with p-values and/or +different statistics) +
+The interaction p-values and a different set of statistics can be
+displayed using the stat_var argument. Note that the users
+are expected to select a method for p-value computation. see
+[tern::prop_diff_test].
+
+
++4. Forest Plot for Odds Ratio (with user-defined subgroup +analysis) +
+The subgroups arguments controls which variables are
+used for subgroup analysis. If NULLthe subgroup analysis is
+removed.
+run(fstg01, proc_data, subgroups = NULL)
+
+
++5. Forest Plot for Odds Ratio (with stratified +analysis) +
+The strata_var argument is used to pass the columns used
+for stratified analysis.
+run(fstg01, proc_data, strata_var = "STRATA1")
+#> Warning in coxexact.fit(X, Y, istrat, offset, init, control, weights = weights,
+#> : Ran out of iterations and did not converge
+#> Warning in s_odds_ratio(df = l_df[[2]], .var = "rsp", .ref_group = l_df[[1]], :
+#> Unable to compute the odds ratio estimate. Please try re-running the function
+#> with parameter `method` set to "approximate".
+#> Warning in coxexact.fit(X, Y, istrat, offset, init, control, weights = weights,
+#> : Ran out of iterations and did not converge
+
+
++6. Forest Plot for Odds Ratio (without proportional sizing +of the odds ratio symbol) +
+The col_symbol_size argument controls the size of the
+odds ratio symbols which are by default proportional in size to the
+sample size of the subgroup. If NULL the same symbol size
+is used for all subgroups.
+run(fstg01, proc_data, col_symbol_size = NULL)
+
+Forest Plot for Hazard Ratio
+(
+
+
+Forest Plot for Hazard Ratio
+(FSTG02)
+
+
+
+
++1. Forest Plot for Hazard Ratio (with subgroup +analysis) +
+-
+
- The
fstg02template produces the +standard forest plot for hazard ratio.
+ - Users are expected to subset the parameter of interest
+(e.g.
PARAMCD == "OS") in pre-processing.
+ - Users are expected to subset the arm variable to keep only the two
+arms to compare
+(e.g.
ARM %in% c("A: Drug X", "B: Placebo")).
+ - By default, the plots displays a subgroup analysis for
+
"SEX","AGEGR1"and"RACE".
+ - Unstratified analysis is provided by default. +
- The plots displays by default the Total number of events, the hazard +ratio and the 95% confidence interval, and, for each arm, the number of +events and the median time to event in month. +
+proc_data <- log_filter(
+ syn_data,
+ PARAMCD == "OS" & ARM %in% c("A: Drug X", "B: Placebo"), "adtte"
+)
+run(fstg02, proc_data)
+
+
++2. Forest Plot for Hazard Ratio (with p-values and/or +different statistics) +
+The interaction p-values and a different set of statistics can be
+displayed using the control argument. More details about
+the control options are available in
+[tern::extract_survival_subgroups]
+run(
+ fstg02,
+ proc_data,
+ stat_var = c("n_tot", "n", "ci", "hr", "pval"),
+ control = list(conf_level = 0.9, pval_method = "likelihood")
+)
+
+
++3. Forest Plot for Hazard Ratio (with user-defined subgroup +analysis) +
+The subgroups arguments controls which variables are
+used for subgroup analysis. If NULLthe subgroup analysis is
+removed.
+run(fstg02, proc_data, subgroups = NULL)
+
+
++4. Forest Plot for Hazard Ratio (with stratified +analysis) +
+The strata_var argument is used to pass the columns used
+for stratified analysis.
+run(fstg02, proc_data, strata_var = "STRATA1")
+#> Warning in coxph.fit(X, Y, istrat, offset, init, control, weights = weights, :
+#> Loglik converged before variable 1 ; coefficient may be infinite.
+
+
++5. Forest Plot for Hazard Ratio (without proportional sizing +of the hazard ratio symbol) +
+The col_symbol_size argument controls the size of the
+hazard ratio symbols which are by default proportional in size to the
+number of events in the subgroup. If NULL the same symbol
+size is used for all subgroups.
+run(fstg02, proc_data, col_symbol_size = NULL)
+
+Kaplan-Meier Plot (
+
+
+Kaplan-Meier Plot (KMG01)
+
+
+
+
++1. Kaplan-Meier Plot (without comparative +statistics) +
+-
+
- The
kmg01template produces the +standard Kaplan-Meier Plot.
+ - Users are expected to select a particular parameter for +analysis. +
- Users are expected to select the treatment groups to compare, +otherwise, all treatment groups available in the input datasets will be +plotted. +
- The comparative statistics are not included by default. +
- The estimation of median survival time per treatment group by +default. +
- More arguments in the
g_kmand +control_coxphfunctions can be passed through, please use +the Help to find out more information.
+
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(kmg01, proc_data, dataset = "adtte")
+
+
++2. Kaplan-Meier Plot (with comparative +statistics) +
+To enable the comparative statistics (hazard ratio and p-value), the
+argument annot_coxph needs to be set to TRUE. The compare
+group is determined by the levels in the factorized variable of
+treatment group and the first level is used as reference group in the
+statistics.
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(
+ kmg01,
+ proc_data,
+ dataset = "adtte",
+ annot_coxph = TRUE,
+ control_annot_coxph = tern::control_coxph_annot(x = 0.33, y = 0.42)
+)
+
+
++3. Kaplan-Meier Plot (without censoring marks) +
+To suppress the censoring marks, set the argument
+cencor_show to FALSE.
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(kmg01, proc_data, dataset = "adtte", censor_show = FALSE)
+
+
++4. Kaplan-Meier Plot (without estimation of median survival +time) +
+
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(kmg01, proc_data, dataset = "adtte", annot_surv_med = FALSE)
+
+
++5. Kaplan-Meier Plot (with statistical annotation of either +median or min of survival time) +
+To add the statistics annotation, use the function
+annot_stats. Options are min or
+median.
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(kmg01, proc_data, dataset = "adtte", annot_stats = "median")
+
+
++6. Kaplan-Meier Plot (without the table of patients at +risk) +
+
+proc_data <- log_filter(syn_data, PARAMCD == "OS", "adtte")
+run(kmg01, proc_data, dataset = "adtte", annot_at_risk = FALSE)
+
+Mean Plot (
+
+
+Mean Plot (MNG01)
+
+
+
+
++1. Plot of Mean and Confidence Interval (with Table +Section) +
+-
+
- The
mng01template produces the +standard mean plot.
+ - Note that the template
mng01is quite general. The +users are expected to specify the analysis dataset and the visit +variable in therunfunction, and select the parameters +prior to therunfunction.
+ - The table of summary statistics is included by default. +
- The variable Analysis Value
AVALis used for plotting +by default.
+ - If the input dataset contains results of the same analyses in
+multiple units,(e.g. SI/CV units in
ADLB), please make sure +that the parameters in appropriate units are selected in advance.
+
+proc_data <- log_filter(syn_data, PARAMCD == "DIABP", "advs")
+run(mng01, proc_data, dataset = "advs", x_var = c("AVISIT", "AVISITN"))
+#> $`Diastolic Blood Pressure`
+
+
++2. Plot of Mean and Confidence Interval of Change from +Baseline of Vital Signs +
+
+proc_data <- log_filter(syn_data, PARAMCD == "DIABP", "advs")
+run(mng01, proc_data, dataset = "advs", x_var = c("AVISIT", "AVISITN"), y_var = "CHG")
+#> `geom_line()`: Each group consists of only one observation.
+#> ℹ Do you need to adjust the group aesthetic?
+#> $`Diastolic Blood Pressure`
+
+
++3. Plot of Mean (+/-SD) (Changing the +Statistics) +
+To change the statistics, use the argument interval_fun.
+Options are mean_ci, mean_sei,
+mean_sdi, median_ci,
+quantiles,range.
+proc_data <- log_filter(syn_data, PARAMCD == "DIABP", "advs")
+run(mng01, proc_data, dataset = "advs", x_var = c("AVISIT", "AVISITN"), interval_fun = "mean_sdi")
+#> $`Diastolic Blood Pressure`
+
+
++4. Plot of Mean and Confidence Interval (Modify Alpha +Level) +
+To change the alpha level of the confidence interval, use the
+argument
+control = control_analyze_vars(conf_level = <0.xx>).
+Note that this is only in effect when interval_fun is set
+to mean_ci.
+proc_data <- log_filter(syn_data, PARAMCD == "DIABP", "advs")
+run(
+ mng01, proc_data,
+ dataset = "advs", x_var = c("AVISIT", "AVISITN"),
+ interval_fun = "mean_ci", control = tern::control_analyze_vars(conf_level = 0.80)
+)
+#> $`Diastolic Blood Pressure`
+
+
++5. Plot of Mean and Confidence Interval （With Number of +Patients Only) +
+
+proc_data <- log_filter(syn_data, PARAMCD == "DIABP", "advs")
+run(mng01, proc_data, dataset = "advs", x_var = c("AVISIT", "AVISITN"), table = "n")
+#> $`Diastolic Blood Pressure`
+
+
+
++6. Plot of Mean and Confidence Interval (without Table +Section) +
+
+proc_data <- log_filter(syn_data, PARAMCD == "DIABP", "advs")
+run(mng01, proc_data, dataset = "advs", x_var = c("AVISIT", "AVISITN"), table = NULL)
+#> $`Diastolic Blood Pressure`
A new argument has been added to control the theme (e.g. setting the +angle of the axis); see an example below:
+
+ggtheme <- ggplot2::theme(
+ panel.grid = ggplot2::element_line(colour = "black", linetype = 3),
+ panel.background = ggplot2::element_rect(fill = "white"),
+ legend.position = "top",
+ axis.text.x = ggplot2::element_text(angle = 22, hjust = 1, vjust = 1)
+)
+run(mng01, syn_data, dataset = "adlb", ggtheme = ggtheme)
+#> $`Alanine Aminotransferase Measurement`
#>
+#> $`C-Reactive Protein Measurement`
#>
+#> $`Immunoglobulin A Measurement`