Generate ADSL in R

library(glue)
library(tidyverse)
library(haven)
library(assertthat)
library(huxtable)
library(data.table)
library(lubridate)
library(pharmaRTF)

load("Data_Need_forADSL.RData")
ls()

'dm'
'ds'
'suppdm'
'vs'

Merge DM and SUPPDM

Transponse SUPPDM data such that each QNAM becomes a variable

suppdm01 <- suppdm %>%
    mutate(qnam=str_to_lower(qnam)) %>%
    group_by(studyid, usubjid) %>%
    pivot_wider(id_cols=c(studyid,usubjid),names_from = qnam, values_from = qval)

dm01 <- left_join(dm, suppdm01, by = c("studyid", "usubjid"))

dm01

Create variables that are directly based on input variables

adsl01 <- dm01 %>%

    # Planned and actual treatment values;

mutate(trt01p = if_else(armcd == "PBO", "Placebo", if_else(armcd == "ACTIVE", "Active", "")),
       trt01a = if_else(actarmcd == "PBO", "Placebo", if_else(actarmcd == "ACTIVE", "Active", "")),
       trt01pn = if_else(armcd == "PBO", 1, if_else(armcd == "ACTIVE", 2, NA)),
       trt01an = if_else(actarmcd == "PBO", 1, if_else(actarmcd == "ACTIVE", 2, NA))) %>%

    # Date conversions

mutate(tr01sdt = as.Date(rfxstdtc),
tr01edt = as.Date(rfxendtc),
rficdt = as.Date(rficdtc),
lstalvdt = as.Date(rfpendtc),
dthdt = as.Date(dthdtc),
trtsdt = tr01sdt,
trtedt = tr01edt) %>%

    # Grouping variables
mutate(agegr1 = if_else(!is.na(age) & age < 60, "< 60 Years",
if_else(age >= 60, ">= 60 Years", "")),
agegr1n = if_else(!is.na(age) & age < 60, 1, if_else(age >= 60, 2,NA)))

 select(adsl01, c('usubjid', 'trt01p','trt01a','trt01pn', 'trt01an','agegr1','agegr1n', 'ethnic'))

A tibble: 8 × 8
usubjid	trt01p	trt01a	trt01pn	trt01an	agegr1	agegr1n	ethnic
<chr>	<chr>	<chr>	<dbl>	<dbl>	<chr>	<dbl>	<chr>
CSG001-1001			NA	NA	< 60 Years	1	HISPANIC OR LATINO
CSG001-1002			NA	NA	< 60 Years	1	NOT HISPANIC OR LATINO
CSG001-1003	Placebo		1	NA	< 60 Years	1	HISPANIC OR LATINO
CSG001-1004	Active	Active	2	2	< 60 Years	1	HISPANIC OR LATINO
CSG001-1005	Active	Placebo	2	1	>= 60 Years	2	NOT HISPANIC OR LATINO
CSG001-1006	Placebo	Placebo	1	1	>= 60 Years	2	NOT HISPANIC OR LATINO
CSG001-1007	Placebo	Placebo	1	1	< 60 Years	1	NOT HISPANIC OR LATINO
CSG001-1008	Active	Active	2	2	>= 60 Years	2	NOT HISPANIC OR LATINO

Process disposition data for treatment and study status

Enrollment

enrl01 <- ds %>%
filter(dsterm == "ENROLLED") %>%
mutate(enrldt = as.Date(dsstdtc)) %>%
select(studyid, usubjid, enrldt)

Randomization

rand01 <- ds %>%
filter(dsterm == "RANDOMIZED") %>%
mutate(randdt = as.Date(dsstdtc)) %>%
select(studyid, usubjid, randdt)

End of treatment

eot01 <- ds %>%
 filter(dsscat == "END OF TREATMENT") %>%
 mutate(
 eotstt = case_when(
 dsdecod == "COMPLETED" ~ "COMPLETED",
 dsdecod != "" ~ "DISCONTINUED",
 TRUE ~ NA
 ),
 dctreas = if_else(dsdecod != "COMPLETED", dsdecod, NA),
 ineot = 1
 ) %>%
 select(studyid, usubjid, eotstt, dctreas, ineot)

End of study;

eos01 <- ds %>%
 filter(dsscat == "END OF STUDY") %>%
 mutate(
 eosstt = case_when(
 dsdecod == "COMPLETED" ~ "COMPLETED",
 dsdecod != "" ~ "DISCONTINUED",
 TRUE ~ NA
 ),
 dcsreas = if_else(dsdecod != "COMPLETED", dsdecod, NA),
 eosdt = as.Date(dsstdtc),
 ineos = 1
 ) %>%
 select(studyid, usubjid, eosstt, dcsreas, eosdt, ineos)

Baseline variables from vital signs;

heightbl <- vs %>%
 filter(vsblfl == "Y" & vstestcd == "HEIGHT") %>%
 select(studyid, usubjid, vsstresn) %>%
 rename(heightbl = vsstresn)

weightbl <- vs %>%
 filter(vsblfl == "Y" & vstestcd == "WEIGHT") %>%
 select(studyid, usubjid, vsstresn) %>%
 rename(weightbl = vsstresn)

Bring disposition and vital signs related info into parent dataset;

library(purrr)

data_frames <- list(adsl01, eot01, eos01, enrl01, rand01, heightbl, weightbl)

adsl02 <- reduce(data_frames, left_join, by = c("studyid", "usubjid"))

Create variables/assign values to existing variables which are dependent on their variables;


adsl03 <- adsl02 %>%
 mutate(
 saffl = if_else(!is.na(trtsdt), "Y", "N"),
 randfl = if_else(!is.na(randdt), "Y", "N"),
 enrlfl = if_else(!is.na(enrldt), "Y", "N"),
 complfl = if_else(eosstt == "COMPLETED", "Y", "N", "N"),
 eotstt = if_else((eotstt == "" | is.na(eotstt))  & is.na(ineot) & saffl == "Y", "ONGOING", eotstt),
 eosstt = if_else((eosstt == "" | is.na(eosstt)) & is.na(ineos) & saffl == "Y", "ONGOING", eosstt),
 trtdurd = if_else(!is.na(trtsdt) & !is.na(trtedt), trtedt - trtsdt + 1, NA),
 trtdurd = as.numeric(trtdurd)
 )

adsl03 <- adsl03 %>%
 mutate(across(where(is.character), ~if_else(is.na(.), "", .)))

Keep only required variables;

varlist <- c("STUDYID", "USUBJID", "SUBJID", "SITEID", "AGE", "AGEU", "AGEGR1", "AGEGR1N", "SEX", "RACE", "RACE1", "RACE2", "RACESP", "SAFFL", "COMPLFL", "RANDFL", "ENRLFL", "ARM", "ACTARM", "TRT01P", "TRT01PN", "TRT01A", "TRT01AN", "TRTSDT", "TRTEDT", "TR01SDT", "TR01EDT", "EOSSTT", "EOSDT", "DCSREAS", "EOTSTT", "DCTREAS", "RFICDT", "ENRLDT", "RANDDT", "LSTALVDT", "TRTDURD", "DTHDT", "HEIGHTBL", "WEIGHTBL")

adsl <- adsl03 %>%
 rename_all(toupper) %>%
 select(all_of(varlist))

output<-adsl

output

A tibble: 8 × 40
STUDYID	USUBJID	SUBJID	SITEID	AGE	AGEU	AGEGR1	AGEGR1N	SEX	RACE	⋯	EOTSTT	DCTREAS	RFICDT	ENRLDT	RANDDT	LSTALVDT	TRTDURD	DTHDT	HEIGHTBL	WEIGHTBL
<chr>	<chr>	<chr>	<chr>	<dbl>	<chr>	<chr>	<dbl>	<chr>	<chr>	⋯	<chr>	<chr>	<date>	<date>	<date>	<date>	<dbl>	<date>	<dbl>	<dbl>
CSG001	CSG001-1001	1001	10	35	YEARS	< 60 Years	1	M	WHITE	⋯			2010-01-01	NA	NA	2010-01-01	NA	NA	NA	NA
CSG001	CSG001-1002	1002	10	40	YEARS	< 60 Years	1	F	MULTIPLE	⋯			2010-01-01	2010-01-04	NA	2010-01-05	NA	NA	NA	NA
CSG001	CSG001-1003	1003	10	40	YEARS	< 60 Years	1	M	OTHER	⋯			2010-01-01	2010-01-03	2010-01-03	2010-01-05	NA	2010-01-05	NA	NA
CSG001	CSG001-1004	1004	10	38	YEARS	< 60 Years	1	M	WHITE	⋯	COMPLETED		2010-01-01	2010-01-04	2010-01-05	2010-02-28	21	NA	177.00	87.3
CSG001	CSG001-1005	1005	10	64	YEARS	>= 60 Years	2	M	AMERICAN INDIAN OR ALASKA NATIVE	⋯	ONGOING		2010-01-15	2010-02-01	2010-02-05	2020-02-20	8	NA	66.14	76.1
CSG001	CSG001-1006	1006	10	75	YEARS	>= 60 Years	2	F	NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER	⋯	DISCONTINUED	ADVERSE EVENT	2010-02-18	2010-03-01	2010-03-01	2010-03-25	9	NA	160.00	60.9
CSG001	CSG001-1007	1007	10	32	YEARS	< 60 Years	1	M	UNKNOWN	⋯	COMPLETED		2010-04-04	2010-04-14	2010-04-14	2010-06-12	22	NA	178.00	85.4
CSG001	CSG001-1008	1008	10	83	YEARS	>= 60 Years	2	F	NOT REPORTED	⋯	DISCONTINUED	SUBJECT REQUEST	2010-06-20	2010-06-26	2010-06-27	2010-08-18	15	NA	NA	NA

save(adsl, file = "C:/Users/Waraba/Desktop/Ckinical Trial Training Materiels/ADaM_withR/ADaM_ADSL_withR/ADaM_ADSL_L1101/adsl.RData")

adsl

A tibble: 8 × 40
STUDYID	USUBJID	SUBJID	SITEID	AGE	AGEU	AGEGR1	AGEGR1N	SEX	RACE	⋯	EOTSTT	DCTREAS	RFICDT	ENRLDT	RANDDT	LSTALVDT	TRTDURD	DTHDT	HEIGHTBL	WEIGHTBL
<chr>	<chr>	<chr>	<chr>	<dbl>	<chr>	<chr>	<dbl>	<chr>	<chr>	⋯	<chr>	<chr>	<date>	<date>	<date>	<date>	<dbl>	<date>	<dbl>	<dbl>
CSG001	CSG001-1001	1001	10	35	YEARS	< 60 Years	1	M	WHITE	⋯			2010-01-01	NA	NA	2010-01-01	NA	NA	NA	NA
CSG001	CSG001-1002	1002	10	40	YEARS	< 60 Years	1	F	MULTIPLE	⋯			2010-01-01	2010-01-04	NA	2010-01-05	NA	NA	NA	NA
CSG001	CSG001-1003	1003	10	40	YEARS	< 60 Years	1	M	OTHER	⋯			2010-01-01	2010-01-03	2010-01-03	2010-01-05	NA	2010-01-05	NA	NA
CSG001	CSG001-1004	1004	10	38	YEARS	< 60 Years	1	M	WHITE	⋯	COMPLETED		2010-01-01	2010-01-04	2010-01-05	2010-02-28	21	NA	177.00	87.3
CSG001	CSG001-1005	1005	10	64	YEARS	>= 60 Years	2	M	AMERICAN INDIAN OR ALASKA NATIVE	⋯	ONGOING		2010-01-15	2010-02-01	2010-02-05	2020-02-20	8	NA	66.14	76.1
CSG001	CSG001-1006	1006	10	75	YEARS	>= 60 Years	2	F	NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER	⋯	DISCONTINUED	ADVERSE EVENT	2010-02-18	2010-03-01	2010-03-01	2010-03-25	9	NA	160.00	60.9
CSG001	CSG001-1007	1007	10	32	YEARS	< 60 Years	1	M	UNKNOWN	⋯	COMPLETED		2010-04-04	2010-04-14	2010-04-14	2010-06-12	22	NA	178.00	85.4
CSG001	CSG001-1008	1008	10	83	YEARS	>= 60 Years	2	F	NOT REPORTED	⋯	DISCONTINUED	SUBJECT REQUEST	2010-06-20	2010-06-26	2010-06-27	2010-08-18	15	NA	NA	NA

colnames(adsl)

'STUDYID'
'USUBJID'
'SUBJID'
'SITEID'
'AGE'
'AGEU'
'AGEGR1'
'AGEGR1N'
'SEX'
'RACE'
'RACE1'
'RACE2'
'RACESP'
'SAFFL'
'COMPLFL'
'RANDFL'
'ENRLFL'
'ARM'
'ACTARM'
'TRT01P'
'TRT01PN'
'TRT01A'
'TRT01AN'
'TRTSDT'
'TRTEDT'
'TR01SDT'
'TR01EDT'
'EOSSTT'
'EOSDT'
'DCSREAS'
'EOTSTT'
'DCTREAS'
'RFICDT'
'ENRLDT'
'RANDDT'
'LSTALVDT'
'TRTDURD'
'DTHDT'
'HEIGHTBL'
'WEIGHTBL'