Merge branch 'devel' into 26_rerun_admiraltest_dev

# Conflicts:
#	data-raw/ex_ophtha.R
#	data-raw/qs_ophtha.R

NEWS.md

@@ -2,7 +2,7 @@
 
 ## New Features
 
- - New `renv` lock files were setup (#ISSUE-NUMBER)
+ - Ophthalmology variants of `ex` and `qs` SDTM datasets added. (#15)
 
 ## Updates of Existing Functions
 

R/data.R

@@ -54,6 +54,13 @@
 #' @source \url{https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/ex.xpt?raw=true} # nolint
 "admiral_ex"
 
+#' Ophthalmology Exposure Dataset
+#'
+#' An example Exposure SDTM dataset with ophthalmology-specific variables such as `EXLOC` and `EXLAT`
+#'
+#' @source Constructed using `ex` from the `{pharmaversesdtm}` package # nolint
+"ex_ophtha"
+
 #' Laboratory Measurements Dataset
 #'
 #' An updated SDTM LB dataset that uses data from the CDISC pilot project
@@ -121,6 +128,13 @@
 #' @source \url{https://github.com/pharmaverse/admiral.test/blob/main/data/admiral_qs.rda} # nolint
 "admiral_qs"
 
+#' Ophthalmology Questionnaire Dataset
+#'
+#' An example Questionnaires SDTM dataset with ophthalmology-specific questionnaire of NEI VFQ-25
+#'
+#' @source Constructed using `qs` from the `{pharmaversesdtm}` package # nolint
+"qs_ophtha"
+
 #' Subject Characteristic Dataset
 #'
 #' A SDTM SC dataset simulated by Ophthalmology team

data-raw/ex_ophtha.R

@@ -0,0 +1,34 @@
+library(dplyr)
+library(tidyselect)
+library(pharmaversesdtm)
+
+# Make ex_ophtha dataset
+ex_ophtha <- admiral_dm %>%
+  # Start by merging on ophtha_dm to use the SUBJID variable
+  select(USUBJID, SUBJID) %>%
+  right_join(admiral_ex, by = c("USUBJID"), multiple = "all") %>%
+  # Create EXLOC & EXLAT, change EXROUTE & EXDOSFRM to something eye-related
+  mutate(
+    EXLOC = "EYE",
+    EXDOSFRM = "INJECTION",
+    EXDOSFRQ = "ONCE",
+    EXLAT = ifelse(as.integer(SUBJID) %% 2 == 0, "LEFT", "RIGHT"),
+    EXROUTE = "INTRAVITREAL"
+  ) %>%
+  # Drop SUBJID and reorder variables
+  select(
+    "USUBJID", "STUDYID", "DOMAIN", "EXSEQ", "EXTRT", "EXDOSE",
+    "EXDOSU", "EXDOSFRM", "EXDOSFRQ", "EXROUTE", "EXLOC",
+    "EXLAT", "VISITNUM", "VISIT", "VISITDY", "EXSTDTC",
+    "EXENDTC", "EXSTDY", "EXENDY"
+  )
+
+# Label new variables
+attr(ex_ophtha$EXLOC, "label") <- "Location of Dose Administration"
+attr(ex_ophtha$EXLAT, "label") <- "Laterality"
+attr(ex_ophtha$EXROUTE, "label") <- "Route of Administration"
+attr(ex_ophtha$EXDOSFRM, "label") <- "Dose Form"
+attr(ex_ophtha$EXDOSFRQ, "label") <- "Dose Frequency per Interval"
+
+# Save Dataset
+save(ex_ophtha, file = file.path("data", "ex_ophtha.rda"), compress = "bzip2")

data-raw/qs_ophtha.R

@@ -0,0 +1,130 @@
+library(pharmaversesdtm)
+library(dplyr)
+library(stringr)
+
+# create new QS data - keep standard variables from previous ADMIRAL project's QS ====
+qs1 <- admiral_qs %>%
+  # select standard variables
+  select(STUDYID, DOMAIN, USUBJID, QSBLFL, VISITNUM, VISIT, VISITDY, QSDTC, QSDY) %>%
+  # keep unique subjects and visits per subject
+  group_by(USUBJID, VISITDY) %>%
+  unique()
+
+# create dummy parameters and results ====
+dummy_param <- data.frame(QSTEST = c(
+  "Your Overall Health Is",
+  "Eyesight Using Both Eyes Is",
+  "How Often You Worry About Eyesight",
+  "How Often Pain in and Around Eyes",
+  "Difficulty Reading Newspapers",
+  "Difficulty Doing Work/Hobbies",
+  "Difficulty Finding on Crowded Shelf",
+  "Difficulty Reading Street Signs",
+  "Difficulty Going Down Step at Night",
+  "Difficulty Noticing Objects to Side",
+  "Difficulty Seeing How People React",
+  "Difficulty Picking Out Own Clothes",
+  "Difficulty Visiting With People",
+  "Difficulty Going Out to See Movies",
+  "Are You Currently Driving",
+  "Difficulty Driving During Daytime",
+  "Difficulty Driving at Night",
+  "Driving in Difficult Conditions",
+  "Eye Pain Keep You From Doing What You Like",
+  "I Stay Home Most of the Time",
+  "I Feel Frustrated a Lot of the Time",
+  "I Need a Lot of Help From Others",
+  "Worry I'll Do Embarrassing Things",
+  "Difficulty Reading Small Print",
+  "Difficulty Figure Out Bill Accuracy",
+  "Difficulty Shaving or Styling Hair",
+  "Difficulty Recognizing People",
+  "Difficulty Taking Part in Sports",
+  "Difficulty Seeing Programs on TV"
+)) %>%
+  mutate(
+    QSTESTCD = paste0("VFQ", row_number()),
+    QSCAT = "NEI VFQ-25",
+    QSSCAT = "Original Response"
+  )
+
+# dummy answers
+
+# difficulty in performing tasks
+difficulty_res <- c(
+  "SOME DIFFICULTY",
+  "NO DIFFICULTY",
+  "VERY DIFFICULT"
+)
+difficulty_resn <- c(1:3)
+difficulty <- setNames(difficulty_res, difficulty_resn)
+
+# frequency answers
+freq_res <- c("SOMETIMES", "FREQUENTLY", "RARELY", "NEVER")
+freq_resn <- c(1:4)
+frequency <- setNames(freq_res, freq_resn)
+
+# quality answers
+qual_res <- c("VERY GOOD", "GOOD", "FAIR", "POOR", "VERY POOR")
+qual_resn <- c(1:5)
+quality <- setNames(qual_res, qual_resn)
+
+# yesno answers
+yn_res <- c("YES", "NO")
+yn_resn <- c(1:2)
+yesno <- setNames(yn_res, yn_resn)
+
+answers <- c(difficulty_res, freq_res, qual_res, yn_res)
+answersn <- c(difficulty_resn, freq_resn, qual_resn, yn_resn)
+
+# assign answers to questions randomly for each subjects
+
+# take unique subjects
+subjects <- qs1 %>%
+  ungroup() %>%
+  select(USUBJID) %>%
+  distinct()
+
+dummy_param_res_by_subj <- merge(subjects, dummy_param) %>%
+  mutate(QSORRES = case_when(
+    str_detect(QSTEST, "Difficult") ~ sample(difficulty, size = nrow(.), replace = T),
+    str_detect(QSTEST, "How") ~ sample(frequency, size = nrow(.), replace = T),
+    str_detect(QSTEST, "Are You") ~ sample(yesno, size = nrow(.), replace = T),
+    str_detect(QSTEST, "Overall Health") ~ sample(quality, size = nrow(.), replace = T),
+    str_detect(QSTEST, "Eyesight") ~ sample(quality, size = nrow(.), replace = T),
+    TRUE ~ sample(frequency, size = nrow(.), replace = T)
+  )) %>%
+  mutate(
+    QSSTRESC = QSORRES,
+    QSORRESU = "",
+    QSSTRESU = "",
+    QSDRVFL = ""
+  )
+
+# merge standard QS with parameters and result variables from temp QS data
+
+qs2 <- merge(qs1, dummy_param_res_by_subj, by = "USUBJID") %>%
+  group_by(USUBJID) %>%
+  # create QSSEQ based on VFQ QS parameters
+  mutate(QSSEQ = row_number()) %>%
+  arrange(USUBJID, QSSEQ)
+
+qs3 <- qs2 %>%
+  group_by(QSTEST) %>%
+  # create numeric var for std result
+  mutate(QSSTRESN = as.numeric(factor(QSSTRESC))) %>%
+  select(
+    STUDYID, DOMAIN, USUBJID, QSSEQ, QSTESTCD, QSTEST, QSCAT, QSSCAT, QSORRES, QSORRESU, QSSTRESC, QSSTRESN, QSSTRESU,
+    QSBLFL, QSDRVFL, VISITNUM, VISIT, VISITDY, QSDTC, QSDY
+  ) %>%
+  ungroup()
+
+# NOTE: the QS2 dataset made above should be stacked below the admiral_qs dataset.
+# output qs_ophtha.RDS
+# remove the original vfq part from admiral_qs
+admiral_qs_novfq <- admiral_qs %>% filter(QSCAT != "NEI VFQ-25")
+
+qs_ophtha <- rbind(admiral_qs_novfq, qs3)
+
+# ---- Save output for temporary usage ----
+save(qs_ophtha, file = file.path("data", "qs_ophtha.rda"), compress = "bzip2")

inst/WORDLIST

@@ -8,12 +8,15 @@ Contestí
 DM
 DS
 EG
+EXLAT
+EXLOC
 Farrugia
 Github
 GSK
 Gopi
 LinkedIn
 MH
+NEI
 Onboarding
 Pharmacokinetic
 Pharmacokinetics
@@ -30,6 +33,7 @@ SUPPTR
 SV
 TAs
 USUBJIDs
+VFQ
 admiraldata
 admiraltemplate
 admiralxxx
@@ -39,6 +43,7 @@ dev
 nolint
 onboarding
 pharmaverse
+qs
 renv
 repo
 https