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insightsengineering / teal.modules.clinical

Provides teal modules for the standard clinical trials outputs
https://insightsengineering.github.io/teal.modules.clinical/
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Grey error when launching the safety sample application #283

Closed kpagacz closed 2 years ago

kpagacz commented 2 years ago

Grey error upon launch of this tab: image

Code:


library(dplyr)
library(scda)
library(scda.2021)
library(teal.modules.general)
library(teal.modules.clinical)

# code>
## Generate Data
ADSL <- synthetic_cdisc_data("latest")$adsl

## Create variable type lists
date_vars_adsl <- names(ADSL)[vapply(ADSL, function(x) inherits(x, c("Date", "POSIXct", "POSIXlt")), logical(1))]
char_vars_adsl <- names(Filter(isTRUE, sapply(ADSL, is.character)))

ADAE <- synthetic_cdisc_data("latest")$adae
ADAETTE <- synthetic_cdisc_data("latest")$adaette
ADAETTE <- ADAETTE %>%
   mutate(is_event = case_when(grepl("TOT", .data$PARAMCD, fixed = TRUE) ~ TRUE,
                               TRUE ~ CNSR == 0)) %>%
   mutate(n_events = case_when(grepl("TOT", .data$PARAMCD, fixed = TRUE) ~ as.integer(.data$AVAL),
                                TRUE ~ as.integer(is_event)
                              )) %>%
  rtables::var_relabel(
    is_event = "Is an Event"
  ) %>%
  rtables::var_relabel(
    n_events = "Number of Events"
  )
ADAETTE_AE <- filter(ADAETTE, grepl("TOT", .data$PARAMCD, fixed = TRUE)) %>% select(-"AVAL")
ADAETTE_OTH <- filter(ADAETTE, !(grepl("TOT", .data$PARAMCD, fixed = TRUE)))

ADAETTE_TTE <- ADAETTE %>%
  filter(PARAMCD == "AEREPTTE") %>%
  select(USUBJID, ARM, ARMCD, AVAL)

ADAETTE_AE <- full_join(ADAETTE_AE, ADAETTE_TTE, by = c("USUBJID", "ARM", "ARMCD"))
ADAETTE <- rbind(ADAETTE_AE,ADAETTE_OTH)

ADEX <- synthetic_cdisc_data("latest")$adex
ADEX_labels <- var_labels(ADEX)
# Below steps are done to simulate data with TDURD parameter as it is not in the ADEX data from scda package
set.seed(1, kind = "Mersenne-Twister")
ADEX <- ADEX %>%
  distinct(USUBJID, .keep_all = TRUE) %>%
  mutate(
    PARAMCD = "TDURD",
    PARAM = "Overall duration (days)",
    AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE),
    AVALU = "Days",
    PARCAT1 = "OVERALL"
  ) %>%
  bind_rows(ADEX)
ADEX <- ADEX %>%
  filter(PARCAT1 == "OVERALL" & PARAMCD %in% c("TDOSE", "TNDOSE", "TDURD"))
var_labels(ADEX) <- ADEX_labels

ADLB <- synthetic_cdisc_data("latest")$adlb

ADEG <- synthetic_cdisc_data("latest")$adeg

# For real data, ADVS needs some preprocessing like group different ANRIND and BNRIND into abnormal
ADVS <- synthetic_cdisc_data("latest")$advs %>%
  mutate(
    ONTRTFL = ifelse(AVISIT %in% c("SCREENING", "BASELINE"), "", "Y")
  ) %>%
  var_relabel(
    ONTRTFL = "On Treatment Record Flag"
  ) %>%
  mutate(ANRIND = as.character(ANRIND), BNRIND = as.character(BNRIND)) %>%
  mutate(
    ANRIND = case_when(
      ANRIND == "HIGH HIGH" ~ "HIGH",
      ANRIND == "LOW LOW" ~ "LOW",
      TRUE ~ ANRIND
    ),
    BNRIND = case_when(
      BNRIND == "HIGH HIGH" ~ "HIGH",
      BNRIND == "LOW LOW" ~ "LOW",
      TRUE ~ BNRIND
    )
  )

ADCM <- synthetic_cdisc_data("latest")$adcm %>% mutate(CMSEQ = as.integer(CMSEQ))

# Add study-specific pre-processing: convert arm, param and visit variables to factors
# Sample code:
# ADSL$ACTARM <- factor(ADSL$ACTARM)
# ADAE$AETOXGR <- factor(ADAE$AETOXGR)
# ADLB <- ADLB %>%
#   tern::df_explicit_na(omit_columns = setdiff(names(ADLB), c("PARAM", "PARAMCD", "AVISIT") ))
# ADEX <- ADEX %>%
#   tern::df_explicit_na(omit_columns = setdiff(names(ADEX), c("PARAM", "PARAMCD", "PARCAT2") ))

# define study-specific analysis subgroups and baskets from ADAE
add_event_flags <- function(dat){
  dat %>%
    dplyr::mutate(
      TMPFL_SER = AESER == "Y",
      TMPFL_REL = AEREL == "Y",
      TMPFL_GR5 = AETOXGR == "5",
      TMP_SMQ01 = !is.na(SMQ01NAM),
      TMP_SMQ02 = !is.na(SMQ02NAM),
      TMP_CQ01 = !is.na(CQ01NAM)
    ) %>%
    rtables::var_relabel(
      TMPFL_SER = "Serious AE",
      TMPFL_REL = "Related AE",
      TMPFL_GR5 = "Grade 5 AE",
      TMP_SMQ01 = aesi_label(dat$SMQ01NAM, dat$SMQ01SC),
      TMP_SMQ02 = aesi_label(dat$SMQ02NAM, dat$SMQ02SC),
      TMP_CQ01 = aesi_label(dat$CQ01NAM)
    )
}

ADAE <- ADAE %>%
  add_event_flags()
# <code

## Reusable Configuration For Modules
arm_vars <- c("ACTARMCD", "ACTARM")

demog_vars_adsl <- names(ADSL)[!(names(ADSL) %in% c("USUBJID", "STUDYID", date_vars_adsl))]

cs_arm_var <- choices_selected(
  choices = variable_choices(ADSL, subset = arm_vars),
  selected = "ACTARM"
)

ae_anl_vars <- names(ADAE)[startsWith(names(ADAE), "TMPFL_")]
# flag variables for AE baskets; set to NULL if not applicable to study
aesi_vars <- names(ADAE)[startsWith(names(ADAE), "TMP_SMQ") | startsWith(names(ADAE), "TMP_CQ")]

## Setup App
app <- teal::init(
  data = cdisc_data(
    cdisc_dataset("ADSL", ADSL, code = 'ADSL <- synthetic_cdisc_data("latest")$adsl',
                  vars = list(char_vars_adsl = char_vars_adsl)),
    cdisc_dataset("ADAE", ADAE, code = 'ADAE <- synthetic_cdisc_data("latest")$adae
                                        add_event_flags <- function(dat) {
                                          dat %>%
                                            dplyr::mutate(
                                              TMPFL_SER = AESER == "Y",
                                              TMPFL_REL = AEREL == "Y",
                                              TMPFL_GR5 = AETOXGR == "5",
                                              TMP_SMQ01 = !is.na(SMQ01NAM),
                                              TMP_SMQ02 = !is.na(SMQ02NAM),
                                              TMP_CQ01 = !is.na(CQ01NAM)
                                            ) %>%
                                            rtables::var_relabel(
                                              TMPFL_SER = "Serious AE",
                                              TMPFL_REL = "Related AE",
                                              TMPFL_GR5 = "Grade 5 AE",
                                              TMP_SMQ01 = aesi_label(dat$SMQ01NAM, dat$SMQ01SC),
                                              TMP_SMQ02 = aesi_label(dat$SMQ02NAM, dat$SMQ02SC),
                                              TMP_CQ01 = aesi_label(dat$CQ01NAM)
                                            )
                                        }

                                        ADAE <- ADAE %>%
                                          add_event_flags()'),
    cdisc_dataset("ADAETTE", ADAETTE, code = 'ADAETTE <- synthetic_cdisc_data("latest")$adaette
                            ADAETTE <- ADAETTE %>%
                   mutate(is_event = case_when(grepl("TOT", .data$PARAMCD, fixed = TRUE) ~ TRUE,
                                               TRUE ~ CNSR == 0)) %>%
                   mutate(n_events = case_when(grepl("TOT", .data$PARAMCD, fixed = TRUE) ~ as.integer(.data$AVAL),
                                                TRUE ~ as.integer(is_event)
                                              )) %>%
                  rtables::var_relabel(
                    is_event = "Is an Event"
                  ) %>%
                  rtables::var_relabel(
                    n_events = "Number of Events"
                  )
                ADAETTE_AE <- filter(ADAETTE, grepl("TOT", .data$PARAMCD, fixed = TRUE)) %>% select(-"AVAL")
                ADAETTE_OTH <- filter(ADAETTE, !(grepl("TOT", .data$PARAMCD, fixed = TRUE)))

                ADAETTE_TTE <- ADAETTE %>%
                  filter(PARAMCD == "AEREPTTE") %>%
                  select(USUBJID, ARM, ARMCD, AVAL)

                ADAETTE_AE <- full_join(ADAETTE_AE, ADAETTE_TTE, by = c("USUBJID", "ARM", "ARMCD"))
                ADAETTE <- rbind(ADAETTE_AE,ADAETTE_OTH)'),
    cdisc_dataset("ADEX", ADEX, code = 'ADEX <- synthetic_cdisc_data("latest")$adex
                                        ADEX_labels <- var_labels(ADEX)
                                        set.seed(1, kind = "Mersenne-Twister")
                                        ADEX <- ADEX %>%
                                          distinct(USUBJID, .keep_all = TRUE) %>%
                                          mutate(
                                            PARAMCD = "TDURD",
                                            PARAM = "Overall duration (days)",
                                            AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE),
                                            AVALU = "Days",
                                            PARCAT1 = "OVERALL"
                                          ) %>%
                                          bind_rows(ADEX)
                                        ADEX <- ADEX %>%
                                          filter(
                                            PARCAT1 == "OVERALL" & PARAMCD %in% c("TDOSE", "TNDOSE", "TDURD")
                                          )
                                        var_labels(ADEX) <- ADEX_labels'),
    cdisc_dataset("ADLB", ADLB, code = "ADLB <- synthetic_cdisc_data(\"latest\")$adlb"),
    cdisc_dataset("ADEG", ADEG, code = "ADEG <- synthetic_cdisc_data(\"latest\")$adeg"),
    cdisc_dataset("ADVS", ADVS, code = 'ADVS <- synthetic_cdisc_data(\"latest\")$advs %>%
                                        mutate(
                                          ONTRTFL = ifelse(AVISIT %in% c("SCREENING", "BASELINE"), "", "Y")
                                        ) %>%
                                        var_relabel(
                                          ONTRTFL = "On Treatment Record Flag"
                                        ) %>%
                                        mutate(ANRIND = as.character(ANRIND), BNRIND = as.character(BNRIND)) %>%
                                        mutate(
                                          ANRIND = case_when(
                                            ANRIND == "HIGH HIGH" ~ "HIGH",
                                            ANRIND == "LOW LOW" ~ "LOW",
                                            TRUE ~ ANRIND
                                          ),
                                          BNRIND = case_when(
                                            BNRIND == "HIGH HIGH" ~ "HIGH",
                                            BNRIND == "LOW LOW" ~ "LOW",
                                            TRUE ~ BNRIND
                                          )
                                        )'),
    cdisc_dataset("ADCM", ADCM, code = 'ADCM <- synthetic_cdisc_data("latest")$adcm %>% mutate(CMSEQ = as.integer(CMSEQ))'),
    # code = get_code("app.R")),
    check = TRUE
  ),
  modules = root_modules(
    module(
      label = "Study Information",
      server = function(input, output, session, datasets) {},
      ui = function(id, ...) {
        tagList(
          tags$p("Info about data source:"),
          tags$p(
            "Random data are used that has been created with the ",
            tags$code("scda"), "R package."
          )
        )
      },
      filters = "all"
    ),
    tm_data_table("Data Table"),
    tm_variable_browser("Variable Browser"),
    tm_t_summary(
      label = "Demographic Table",
      dataname = "ADSL",
      arm_var = cs_arm_var,
      summarize_vars = choices_selected(
        choices = variable_choices(ADSL, demog_vars_adsl),
        selected = c("SEX", "AGE", "RACE")
      )
    ),
    modules(
      "Adverse Events",
      tm_t_events_summary(
        label = "AE Summary",
        dataname = "ADAE",
        arm_var = cs_arm_var,
        flag_var_anl = choices_selected(
          choices = variable_choices("ADAE", ae_anl_vars),
          selected = ae_anl_vars,
          keep_order = TRUE
        ),
        flag_var_aesi = choices_selected(
          choices = variable_choices("ADAE", aesi_vars),
          selected = aesi_vars,
          keep_order = TRUE
        ),
        add_total = TRUE
      ),
      tm_t_events(
        label = "AE by Term",
        dataname = "ADAE",
        arm_var = cs_arm_var,
        llt = choices_selected(
          choices = variable_choices(ADAE, c("AETERM", "AEDECOD")),
          selected = c("AEDECOD")
        ),
        hlt = choices_selected(
          choices = variable_choices(ADAE, c("AEBODSYS", "AESOC")),
          selected = "AEBODSYS"
        ),
        add_total = TRUE,
        event_type = "adverse event"
      ),
      tm_t_events_by_grade(
        label = "AE Table by Grade",
        dataname = "ADAE",
        arm_var = cs_arm_var,
        llt = choices_selected(
          choices = variable_choices(ADAE, c("AEDECOD")),
          selected = c("AEDECOD")
        ),
        hlt = choices_selected(
          choices = variable_choices(ADAE, c("AEBODSYS", "AESOC")),
          selected = "AEBODSYS"
        ),
        grade = choices_selected(
          choices = variable_choices(ADAE, c("AETOXGR")),
          selected = "AETOXGR"
        ),
        add_total = TRUE
      ),
      tm_t_events_patyear(
        label = "AE Rates Adjusted for Patient-Years at Risk",
        dataname = "ADAETTE",
        arm_var = cs_arm_var,
        paramcd = choices_selected(
          choices = value_choices(ADAETTE, "PARAMCD", "PARAM"),
          selected = "AETTE1"
          ),
        events_var = choices_selected(
          choices = variable_choices(ADAETTE, "n_events"),
          selected = "n_events",
          fixed = TRUE
          )
      ),
      tm_t_smq(
        label = "Adverse Events by SMQ Table",
        dataname = "ADAE",
        arm_var = choices_selected(
          choices = variable_choices(ADSL, subset = c(arm_vars, "SEX")),
          selected = "ACTARM"
        ),
        add_total = FALSE,
        baskets = choices_selected(
          choices = variable_choices(ADAE, subset = grep("^(SMQ|CQ).*NAM$", names(ADAE), value = TRUE)),
          selected = grep("^(SMQ|CQ).*NAM$", names(ADAE), value = TRUE)
        ),
        scopes = choices_selected(
          choices = variable_choices(ADAE, subset = grep("^SMQ.*SC$", names(ADAE), value = TRUE)),
          selected = grep("^SMQ.*SC$", names(ADAE), value = TRUE),
          fixed = TRUE
        ),
        llt = choices_selected(
          choices = variable_choices(ADAE, subset = c("AEDECOD")),
          selected = "AEDECOD"
        )
      )
    ),
    modules(
      "Lab Tables",
      tm_t_summary_by(
        label = "Labs Summary",
        dataname = "ADLB",
        arm_var = cs_arm_var,
        by_vars = choices_selected(
          choices = variable_choices(ADLB, c("PARAM", "AVISIT")),
          selected = c("PARAM", "AVISIT"),
          fixed = TRUE
        ),
        summarize_vars = choices_selected(
          choices = variable_choices(ADLB, c("AVAL", "CHG")),
          selected = c("AVAL")
        ),
        paramcd = choices_selected(
          choices = value_choices(ADLB, "PARAMCD", "PARAM"),
          selected = "ALT"
        )
      ),
      tm_t_shift_by_grade(
        label = "Grade Laboratory Abnormality Table",
        dataname = "ADLB",
        arm_var = cs_arm_var,
        paramcd = choices_selected(
          choices = value_choices(ADLB, "PARAMCD", "PARAM"),
          selected = "ALT"
        ),
        worst_flag_var = choices_selected(
          choices = variable_choices(ADLB, subset = c("WGRLOVFL", "WGRLOFL", "WGRHIVFL", "WGRHIFL")),
          selected = c("WGRLOVFL")
        ),
        worst_flag_indicator = choices_selected(
          value_choices(ADLB, "WGRLOVFL"), selected = "Y", fixed = TRUE
        ),
        anl_toxgrade_var = choices_selected(
          choices = variable_choices(ADLB, subset = c("ATOXGR")),
          selected = c("ATOXGR"),
          fixed = TRUE
        ),
        base_toxgrade_var = choices_selected(
          choices = variable_choices(ADLB, subset = c("BTOXGR")),
          selected = c("BTOXGR"),
          fixed = TRUE
        ),
        add_total = FALSE
      ),
      tm_t_abnormality_by_worst_grade(
        label = "Laboratory test results with highest grade post-baseline", 
        dataname = "ADLB", 
        arm_var = choices_selected(
          choices = variable_choices(ADSL, subset = c("ARM", "ARMCD")),
          selected = "ARM"
          ), 
        paramcd = choices_selected(
          choices = value_choices(ADLB, "PARAMCD", "PARAM"), 
          selected = c("ALT", "CRP", "IGA")
          ), 
        add_total = FALSE
      )
    ),
    modules(
      "Exposure",
      tm_t_summary_by(
        label = "Exposure Summary",
        dataname = "ADEX",
        arm_var = cs_arm_var,
        by_vars = choices_selected(
          choices = variable_choices(ADEX, c("PARCAT2", "PARAM")),
          selected = c("PARCAT2", "PARAM"),
          fixed = TRUE
        ),
        summarize_vars = choices_selected(
          choices = variable_choices(ADEX, "AVAL"),
          selected = c("AVAL"),
          fixed = TRUE
        ),
        paramcd = choices_selected(
          choices = value_choices(ADEX, "PARAMCD", "PARAM"),
          selected = "TDOSE"
        ),
        denominator = choices_selected(
          choices = c("n", "N", "omit"),
          selected = "n"
        )
      ),
      tm_t_exposure(
        label = "Duration of Exposure Table",
        dataname = "ADEX",
        paramcd = choices_selected(
         choices = value_choices(ADEX, "PARAMCD", "PARAM"),
         selected = "TDURD",
         fixed = TRUE
         ),
         col_by_var = choices_selected(
           choices = variable_choices(ADEX, subset = c(arm_vars, "SEX")),
           selected = "SEX"
         ),
         row_by_var = choices_selected(
           choices = variable_choices(ADEX, subset = c("RACE", "REGION1", "STRATA1", "SEX")),
           selected = "RACE"
         ),
         parcat = choices_selected(
           choices = value_choices(ADEX, "PARCAT2"),
           selected = "Drug A"
         ),
         add_total = FALSE
        )
    ),
    tm_t_abnormality(
      label = "Vital Signs Abnormality",
      dataname = "ADVS",
      arm_var = cs_arm_var,
      id_var = choices_selected(
        choices = variable_choices(ADSL, subset = "USUBJID"),
        selected = "USUBJID",
        fixed = TRUE
      ),
      by_vars = choices_selected(
        choices = variable_choices(ADVS, subset = c("PARAM", "AVISIT")),
        selected = c("PARAM"),
        keep_order = TRUE
      ),
      grade = choices_selected(
        choices = variable_choices(ADVS, subset = "ANRIND"),
        selected = "ANRIND",
        fixed = TRUE
      ),
      abnormal = list("LOW", "HIGH")
    ),
    tm_t_mult_events(
      label = "Concomitant Medication",
      dataname = "ADCM",
      arm_var = cs_arm_var,
      seq_var = choices_selected("CMSEQ", selected = "CMSEQ", fixed = TRUE),
      hlt = choices_selected(
        choices = variable_choices(ADCM, c("ATC1", "ATC2", "ATC3", "ATC4")),
        selected ="ATC2"
      ),
      llt = choices_selected(
        choices = variable_choices(ADCM, c("CMDECOD")),
        selected = "CMDECOD",
        fixed = TRUE
      ),
      add_total = TRUE,
      event_type = "treatment"
    ),
    tm_t_shift_by_arm(
      label = "ECG Shift Table by Arm",
      dataname = "ADEG",
      arm_var = cs_arm_var,
      paramcd = choices_selected(
        value_choices(ADEG, "PARAMCD"), selected = "HR"
      ),
      visit_var = choices_selected(
        value_choices(ADEG, "AVISIT"), selected = "POST-BASELINE MINIMUM"
      ),
      aval_var = choices_selected(
        variable_choices(ADEG, subset = "ANRIND"), selected = "ANRIND", fixed = TRUE
      ),
      base_var = choices_selected(
        variable_choices(ADEG, subset = "BNRIND"), selected = "BNRIND", fixed = TRUE
      )
    ),
    tm_g_lineplot(
      label = "Line Plot",
      dataname = "ADLB",
      strata = cs_arm_var,
      x = choices_selected(variable_choices(ADLB, "AVISIT"), "AVISIT", fixed = TRUE),
      y = choices_selected(variable_choices(ADLB, c("AVAL", "BASE", "CHG", "PCHG")), "AVAL"),
      y_unit = choices_selected(variable_choices(ADLB, "AVALU"), "AVALU", fixed = TRUE),
      paramcd = choices_selected(variable_choices(ADLB, "PARAMCD"), "PARAMCD", fixed = TRUE),
      param = choices_selected(value_choices(ADLB, "PARAMCD", "PARAM"), "ALT"),
      plot_height = c(1000L, 200L, 4000L)
    )
  ),
  header = div(
    class = "",
    style = "margin-bottom: 2px;",
    tags$h1("Example Safety App with teal.modules.clinical modules", tags$span("SPA", class = "pull-right"))
  ),
  footer = tags$p(class = "text-muted", "Source: agile-R website"),
  # Set initial filter state as safety-evaluable population
  filter = list(
    ADSL = list(SAFFL = "Y"),
    ADLB = list(AVAL = default_filter()),
    ADEX = list(AVAL = default_filter()),
    ADEG = list(AVAL = default_filter())
  )
)

shinyApp(app$ui, app$server)
shajoezhu commented 2 years ago

Thanks @kpagacz ! This is the same issue as https://github.com/insightsengineering/teal.modules.clinical/issues/286. Now have been fixed in the sample app by 

+    abnormal = list(low = "LOW", high = "HIGH")
-    abnormal = list("LOW", "HIGH")

Closing the issue now.