TSFLAB03

Subjects With =1 Laboratory Values With Elevated or Low Values Based on Worst On-treatment Value Using NCI-CTCAE Criteria

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Code

# Program Name:              tsflab03

# Prep Environment

library(envsetup)
library(tern)
library(dplyr)
library(rtables)
library(junco)

# Define script level parameters:

tblid <- "TSFLAB03"
fileid <- tblid
titles <- get_titles_from_file(input_path = '../../_data/', tblid)
string_map <- default_str_map

popfl <- "SAFFL"
trtvar <- "TRT01A"
ctrl_grp <- "Placebo"

## if the option TRTEMFL needs to be added to the TLF
trtemfl <- TRUE

## For analysis on SI units: use adlb dataset
## For analysis on Conventional units: use adlbc dataset -- shell is in conventional units

ad_domain <- "ADLB"

# Initial processing of data + check if table is valid for trial:

adlb_complete <- pharmaverseadamjnj::adlb


## parcat5 and 6 options :

availparcat56 <- c(
  "Investigations",
  "Metabolism and nutritional disorders",
  "Renal and urinary disorders",
  "Blood and lymphatic system disorders"
)

## resrict to some
selparcat56 <- availparcat56[c(1, 2, 4)]

## get all
selparcat56 <- availparcat56

lbtoxgrade_file <- file.path('../../_data', "lbtoxgrade.xlsx")
lbtoxgrade_sheets <- readxl::excel_sheets(path = lbtoxgrade_file)

### CTC5 or DAIDS21c : default CTC5

lbtoxgrade_defs <- readxl::read_excel(lbtoxgrade_file, sheet = "CTC5")

lbtoxgrade_defs <- unique(
  lbtoxgrade_defs %>%
    select(TOXTERM, TOXGRD, INDICATR)
) %>%
  mutate(
    ATOXDSCLH = TOXTERM,
    ATOXGRLH = paste("Grade", TOXGRD)
  ) %>%
  rename(ATOXDIR = INDICATR) %>%
  select(ATOXDSCLH, ATOXGRLH, ATOXDIR)

# Process Data:

adsl <- pharmaverseadamjnj::adsl %>%
  filter(.data[[popfl]] == "Y") %>%
  select(USUBJID, all_of(c(popfl, trtvar)))

adsl$colspan_trt <- factor(
  ifelse(adsl[[trtvar]] == ctrl_grp, " ", "Active Study Agent"),
  levels = c("Active Study Agent", " ")
)

adsl$rrisk_header <- "Risk Difference (%) (95% CI)"
adsl$rrisk_label <- paste(adsl[[trtvar]], paste("vs", ctrl_grp))

colspan_trt_map <- create_colspan_map(
  adsl,
  non_active_grp = ctrl_grp,
  non_active_grp_span_lbl = " ",
  active_grp_span_lbl = "Active Study Agent",
  colspan_var = "colspan_trt",
  trt_var = trtvar
)

adlb00 <- adlb_complete %>%
  select(
    USUBJID,
    AVISITN,
    AVISIT,
    starts_with("PAR"),
    starts_with("ATOX"),
    starts_with("ANL"),
    ONTRTFL,
    TRTEMFL,
    AVAL,
    APOBLFL,
    ABLFL,
    LVOTFL
  ) %>%
  inner_join(adsl) %>%
  mutate(
    ATOXGRL = as.character(ATOXGRL),
    ATOXGRH = as.character(ATOXGRH)
  ) %>%
  relocate(
    .,
    USUBJID,
    ANL04FL,
    ANL05FL,
    ONTRTFL,
    TRTEMFL,
    AVISIT,
    ATOXGRL,
    ATOXGRH,
    ATOXDSCL,
    ATOXDSCH,
    PARAMCD,
    AVISIT,
    AVAL,
    APOBLFL,
    ABLFL
  )


# adlb00 <- adlb00 #%>%
## APT comment on PARCAT6 :
## HGB and WBC : Set to "Blood and lymphatic system disorders".
## HGB and WBC parameter are in 2 categories, one for the high and another one for the low direction grading.
## Anemia (HGB low) and Leukocytosis (WBC high) are in the category "Blood and lymphatic system disorders".
## The grading in the opposite directions are categorized under "Investigations".
## Therefor, both PARCAT5 and PARCAT6 are populated for HGB abd WBC.
## Deal with what is needed at later level, when we have splitted low and high
# mutate(PARCAT56 = coalesce(PARCAT6,PARCAT5)) %>%
# mutate(PARCAT56 = factor(PARCAT56,levels=unique(c(levels(adlb_complete$PARCAT6),levels(adlb_complete$PARCAT5)))))

# obj_label(adlb00$PARCAT56) <- "Combined PARCAT56"

### important: previous actions lost the label of variables

adlb00 <- var_relabel_list(adlb00, var_labels(adlb_complete, fill = T))

parcat <- unique(
  adlb00 %>%
    select(starts_with("PARCAT"), PARAMCD, PARAM, ATOXDSCL, ATOXDSCH) %>%
    filter(!(is.na(PARCAT5) & is.na(PARCAT6)))
)


### data preparation

if (all(selparcat56 != "")) {
  filtered_adlb <- adlb00 %>%
    filter((PARCAT5 %in% selparcat56) | (PARCAT6 %in% selparcat56))
}


### low grades : ATOXDSCL ATOXGRL ANL04FL
### Note on Worst On-treatment
### note: by filter ANL04FL/ANL05FL, this table is restricted to On-treatment values, per definition of ANL04FL/ANL05FL
### therefor, no need to add ONTRTFL in filter
### if derivation of ANL04FL/ANL05FL is not restricted to ONTRTFL records, adding ONTRTFL here will not give the correct answer either
### as mixing worst with other period is not giving the proper selection !!!

filtered_adlb_low <- filtered_adlb %>%
  filter(ANL04FL == "Y" & !is.na(ATOXDSCL) & !is.na(ATOXGRL)) %>%
  mutate(
    ATOXDSCLH = ATOXDSCL,
    ATOXGRLH = ATOXGRL,
    ATOXDIR = "LOW"
  ) %>%
  select(USUBJID, starts_with("PAR"), starts_with("ATOX"), TRTEMFL) %>%
  select(-c(ATOXGRL, ATOXGRH, ATOXDSCL, ATOXDSCH))

### high grades: ATOXDSCH ATOXGRH ANL05FL
filtered_adlb_high <- filtered_adlb %>%
  filter(ANL05FL == "Y" & !is.na(ATOXDSCH) & !is.na(ATOXGRH)) %>%
  mutate(
    ATOXDSCLH = ATOXDSCH,
    ATOXGRLH = ATOXGRH,
    ATOXDIR = "HIGH"
  ) %>%
  select(USUBJID, starts_with("PAR"), starts_with("ATOX"), TRTEMFL) %>%
  select(-c(ATOXGRL, ATOXGRH, ATOXDSCL, ATOXDSCH))

## combine Low and high into adlb_tox
filtered_adlb_tox <-
  bind_rows(
    filtered_adlb_low,
    filtered_adlb_high
  ) %>%
  select(-c(ATOXGR, ATOXGRN)) %>%
  inner_join(adsl)

### correction of proper category (PARCAT56) for HGB (LOW) and WBC (HIGH)
filtered_adlb_tox <-
  filtered_adlb_tox %>%
  mutate(
    PARCAT56 = case_when(
      PARAMCD == "HGB" & ATOXDIR == "LOW" ~ PARCAT6,
      PARAMCD == "WBC" & ATOXDIR == "HIGH" ~ PARCAT6,

      ### fix on synthetic data !!!!
      PARAMCD == "WBC" & ATOXDIR == "LOW" ~ "Investigations",
      TRUE ~ PARCAT5
    )
  ) %>%
  mutate(
    PARCAT56 = factor(
      PARCAT56,
      levels = unique(c(
        "Blood and lymphatic system disorders",
        levels(adlb_complete$PARCAT5)
      ))
    )
  )


#### DO NOT USE TRTEMFL = Y in filter, as this will remove subjects from both numerator and denominator
#### instead : set ATOXGRLH to a non-reportable value (ie Grade 0) and keep in dataset
if (trtemfl) {
  filtered_adlb_tox <- filtered_adlb_tox %>%
    mutate(
      ATOXGRLH = case_when(
        is.na(TRTEMFL) | TRTEMFL != "Y" ~ "0",
        TRUE ~ ATOXGRLH
      )
    )
}


## convert some to factors -- lty will fail if these are not factors
filtered_adlb_tox <-
  filtered_adlb_tox %>%
  mutate(
    ATOXGRLH = factor(paste("Grade", ATOXGRLH), levels = paste("Grade", 0:5)),
    ATOXDIR = factor(ATOXDIR, levels = c("LOW", "HIGH"))
  )


filtered_adlb_tox <- unique(
  filtered_adlb_tox
)

check_non_unique_subject <- filtered_adlb_tox %>%
  group_by(USUBJID, PARAMCD, ATOXDSCLH) %>%
  summarize(n_subject = n()) %>%
  filter(n_subject > 1)

if (nrow(check_non_unique_subject)) {
  message(
    "Please review your data selection process, subject has multiple records"
  )
}


params <- unique(
  filtered_adlb_tox %>% select(PARCAT56, PARAMCD, PARAM, ATOXDSCLH, ATOXDIR)
)

all_params <- unique(
  adlb_complete %>%
    filter(!(is.na(PARCAT5) & is.na(PARCAT6))) %>%
    select(PARCAT5, PARCAT6, PARAMCD, PARAM, ATOXDSCL, ATOXDSCH)
)


### add relevant extra vars to lbtoxgrade_defs, only restrict to those actually in trial
lbtoxgrade_defs <- lbtoxgrade_defs %>%
  inner_join(
    .,
    unique(
      filtered_adlb_tox %>%
        select(PARAMCD, PARAM, ATOXDIR, ATOXDSCLH, PARCAT5, PARCAT6, PARCAT56)
    ),
    relationship = "many-to-many"
  )

### Define param_map to be used in layout
param_map <- lbtoxgrade_defs %>%
  select(PARCAT56, PARAM, PARAMCD, ATOXDIR, ATOXDSCLH, ATOXGRLH) %>%
  ### for proper sorting: add factor levels to PARAMCD, ATOXDIR
  mutate(
    PARAMCD = factor(PARAMCD, levels = levels(adlb00$PARAMCD)),
    ATOXDIR = factor(ATOXDIR, levels = c("LOW", "HIGH"))
  ) %>%
  # ### actual sorting
  #   arrange(PARCAT56,PARAMCD,ATOXDIR,ATOXGRLH) %>%
  ### actual sorting -- all alphabetic on output
  arrange(PARCAT56, ATOXDSCLH) %>%
  ### !!!! no factors are allowed in this split_fun map definition
  mutate(
    PARCAT56 = as.character(PARCAT56),
    PARAMCD = as.character(PARAMCD),
    PARAM = as.character(PARAM),
    ATOXDIR = as.character(ATOXDIR),
    ATOXDSCLH = as.character(ATOXDSCLH)
  ) # %>%
### !!!! do not remove Grade 0 here, as this would lead to incorrect N and % derivation
### filter(ATOXGRLH != "Grade 0")
### Grade 0 will be removed as a post-processing step

# Define layout and build table:

ref_path <- c("colspan_trt", " ", trtvar, ctrl_grp)

extra_args_rr <- list(
  method = "wald",
  denom = "n_df",
  ref_path = ref_path,
  .stats = c("denom", "count_unique_fraction")
)
extra_args_rr2 <- list(
  method = "wald",
  denom = "n_df",
  ref_path = ref_path,
  .stats = c("denom", "count_unique_denom_fraction")
)

lyt0 <- basic_table(show_colcounts = TRUE, colcount_format = "N=xx") %>%
  ### first columns
  split_cols_by(
    "colspan_trt",
    split_fun = trim_levels_to_map(map = colspan_trt_map)
  ) %>%
  split_cols_by(trtvar) %>%
  split_cols_by("rrisk_header", nested = FALSE) %>%
  split_cols_by(
    trtvar,
    labels_var = "rrisk_label",
    split_fun = remove_split_levels(ctrl_grp)
  ) %>%
  split_rows_by(
    "PARCAT56",
    label_pos = "topleft",
    child_labels = "visible",
    split_label = "NCI-CTCAE Category",
    ### trim_levels_to_map needs to be applied at ALL split_rows_by levels
    split_fun = trim_levels_to_map(param_map),
    section_div = " "
  ) %>%
  split_rows_by(
    "ATOXDSCLH",
    label_pos = "topleft",
    child_labels = "visible",
    split_label = "Laboratory Test",
    ### trim_levels_to_map needs to be applied at ALL split_rows_by levels
    split_fun = trim_levels_to_map(param_map),
    section_div = " "
  ) %>%
  append_topleft("    Grade, n (%)")

# version without explicit denominator (as in shell)
lyt <- lyt0 %>%
  # for testing, it is sometimes convenient to explicitely show the used denominator
  analyze(
    "ATOXGRLH",
    a_freq_j,
    extra_args = extra_args_rr,
    show_labels = "hidden",
    indent_mod = 0L
  )

result <- build_table(lyt, filtered_adlb_tox, alt_counts_df = adsl)


# version with explicit denominator (for verification)
lyt2 <- lyt0 %>%
  # for testing, it is sometimes convenient to explicitely show the used denominator
  analyze(
    "ATOXGRLH",
    a_freq_j,
    extra_args = extra_args_rr2,
    show_labels = "visible",
    indent_mod = 0L
  )

### apply layout
result2 <- build_table(lyt2, filtered_adlb_tox, alt_counts_df = adsl)

# Post-Processing:

remove_grade0 <- function(tr) {
  if (is(tr, "DataRow") & (tr@label == "Grade 0")) {
    return(FALSE)
  } else {
    return(TRUE)
  }
}

result <- result %>% prune_table(prune_func = keep_rows(remove_grade0))
result2 <- result2 %>% prune_table(prune_func = keep_rows(remove_grade0))

# Remove colcount from rrisk_header:

result <- remove_col_count(result)
result2 <- remove_col_count(result2)

# Add titles and footnotes:

result <- set_titles(result, titles)

# Convert to tbl file and output table

tt_to_tlgrtf(string_map = string_map, tt = result, file = fileid, orientation = "landscape")

TSFLAB03: Subjects With =1 Laboratory Values With Elevated or Low Values Based on Worst On-treatment Value Using NCI-CTCAE Criteria; Safety Analysis Set (Study jjcs - core)
NCI-CTCAE Category	Active Study Agent			Risk Difference (%) (95% CI)
Laboratory Test	Xanomeline High Dose	Xanomeline Low Dose	Placebo	Xanomeline High Dose vs Placebo	Xanomeline Low Dose vs Placebo
Grade, n (%)	N=53	N=73	N=59
Blood and lymphatic system disorders
Anemia
N	53	73	59
Grade 1	29 (54.7%)	42 (57.5%)	35 (59.3%)	-4.6 (-23.0, 13.7)	-1.8 (-18.7, 15.1)
Grade 2	16 (30.2%)	24 (32.9%)	23 (39.0%)	-8.8 (-26.3, 8.7)	-6.1 (-22.6, 10.4)
Grade 3	12 (22.6%)	18 (24.7%)	13 (22.0%)	0.6 (-14.8, 16.1)	2.6 (-11.9, 17.1)

Leukocytosis
N	53	73	59
Grade 3	0	0	0	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)

Metabolism and nutritional disorders
Hyperkalemia
N	53	73	59
Grade 1	1 (1.9%)	0	0	1.9 (-1.8, 5.5)	0.0 (0.0, 0.0)
Grade 2	0	0	1 (1.7%)	-1.7 (-5.0, 1.6)	-1.7 (-5.0, 1.6)
Grade 3	0	0	0	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)
Grade 4	0	0	0	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)

Hypernatremia
N	53	73	59
Grade 1	6 (11.3%)	5 (6.8%)	9 (15.3%)	-3.9 (-16.5, 8.6)	-8.4 (-19.3, 2.4)
Grade 2	1 (1.9%)	0	0	1.9 (-1.8, 5.5)	0.0 (0.0, 0.0)
Grade 3	0	0	0	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)
Grade 4	0	0	0	0.0 (0.0, 0.0)	0.0 (0.0, 0.0)

Hypoalbuminemia
N	53	73	59
Grade 1	37 (69.8%)	32 (43.8%)	40 (67.8%)	2.0 (-15.2, 19.2)	-24.0 (-40.4, -7.5)
Grade 2	23 (43.4%)	21 (28.8%)	25 (42.4%)	1.0 (-17.3, 19.4)	-13.6 (-29.9, 2.7)
Grade 3	11 (20.8%)	10 (13.7%)	15 (25.4%)	-4.7 (-20.2, 10.9)	-11.7 (-25.4, 1.9)

Hypoglycemia
N	53	72	59
Grade 1	30 (56.6%)	33 (45.8%)	37 (62.7%)	-6.1 (-24.3, 12.1)	-16.9 (-33.8, -0.0)
Grade 2	25 (47.2%)	23 (31.9%)	23 (39.0%)	8.2 (-10.1, 26.5)	-7.0 (-23.5, 9.4)
Grade 3	12 (22.6%)	17 (23.6%)	15 (25.4%)	-2.8 (-18.6, 13.0)	-1.8 (-16.6, 13.0)
Grade 4	0	1 (1.4%)	1 (1.7%)	-1.7 (-5.0, 1.6)	-0.3 (-4.6, 4.0)

Hypokalemia
N	53	73	58
Grade 2	20 (37.7%)	23 (31.5%)	20 (34.5%)	3.3 (-14.6, 21.1)	-3.0 (-19.2, 13.2)
Grade 3	11 (20.8%)	11 (15.1%)	15 (25.9%)	-5.1 (-20.8, 10.6)	-10.8 (-24.7, 3.1)
Grade 4	2 (3.8%)	4 (5.5%)	2 (3.4%)	0.3 (-6.6, 7.3)	2.0 (-5.0, 9.1)

Hyponatremia
N	53	71	59
Grade 1	36 (67.9%)	40 (56.3%)	40 (67.8%)	0.1 (-17.2, 17.5)	-11.5 (-28.0, 5.1)
Grade 3	16 (30.2%)	14 (19.7%)	12 (20.3%)	9.8 (-6.2, 25.9)	-0.6 (-14.4, 13.2)
Grade 4	3 (5.7%)	0	0	5.7 (-0.6, 11.9)	0.0 (0.0, 0.0)

Note: On-treatment is defined as treatment-emergentlaboratory values obtained after the first dose and within [30 days] following treatment discontinuation. [Treatment-emergent values are those that worsened from baseline.]
Note: NCI-CTCAE grades (version 5.0.) are based on the laboratory result and do not take into account the clinical component, if applicable.

Download RTF file

--- title: TSFLAB03 subtitle: Subjects With =1 Laboratory Values With Elevated or Low Values Based on Worst On-treatment Value Using NCI-CTCAE Criteria --- ------------------------------------------------------------------------ {{< include ../../_utils/envir_hook.qmd >}} ```{r setup, echo = FALSE, warning = FALSE, message = FALSE} options(docx.add_datetime = FALSE, tidytlg.add_datetime = FALSE) envsetup_config_name <- "default" # Path to the combined config file envsetup_file_path <- file.path("../..", "envsetup.yml") Sys.setenv(ENVSETUP_ENVIRON = '') library(envsetup) loaded_config <- config::get(config = envsetup_config_name, file = envsetup_file_path) envsetup::rprofile(loaded_config) dpscomp <- compound dpspdr <- paste(protocol,dbrelease,rpteff,sep="__") aptcomp <- compound aptpdr <- paste(protocol,dbrelease,rpteff,sep="__") ###### Study specific updates (formerly in envre) dpscomp <- "standards" dpspdr <- "jjcs__NULL__jjcs - core" apt <- FALSE library(junco) default_str_map <- rbind(default_str_map, c("&ctcae", "5.0")) ``` ## Output :::: panel-tabset ## {{< fa regular file-lines sm fw >}} Preview ```{r variant1, results='hide', warning = FALSE, message = FALSE} # Program Name: tsflab03 # Prep Environment library(envsetup) library(tern) library(dplyr) library(rtables) library(junco) # Define script level parameters: tblid <- "TSFLAB03" fileid <- tblid titles <- get_titles_from_file(input_path = '../../_data/', tblid) string_map <- default_str_map popfl <- "SAFFL" trtvar <- "TRT01A" ctrl_grp <- "Placebo" ## if the option TRTEMFL needs to be added to the TLF trtemfl <- TRUE ## For analysis on SI units: use adlb dataset ## For analysis on Conventional units: use adlbc dataset -- shell is in conventional units ad_domain <- "ADLB" # Initial processing of data + check if table is valid for trial: adlb_complete <- pharmaverseadamjnj::adlb ## parcat5 and 6 options : availparcat56 <- c( "Investigations", "Metabolism and nutritional disorders", "Renal and urinary disorders", "Blood and lymphatic system disorders" ) ## resrict to some selparcat56 <- availparcat56[c(1, 2, 4)] ## get all selparcat56 <- availparcat56 lbtoxgrade_file <- file.path('../../_data', "lbtoxgrade.xlsx") lbtoxgrade_sheets <- readxl::excel_sheets(path = lbtoxgrade_file) ### CTC5 or DAIDS21c : default CTC5 lbtoxgrade_defs <- readxl::read_excel(lbtoxgrade_file, sheet = "CTC5") lbtoxgrade_defs <- unique( lbtoxgrade_defs %>% select(TOXTERM, TOXGRD, INDICATR) ) %>% mutate( ATOXDSCLH = TOXTERM, ATOXGRLH = paste("Grade", TOXGRD) ) %>% rename(ATOXDIR = INDICATR) %>% select(ATOXDSCLH, ATOXGRLH, ATOXDIR) # Process Data: adsl <- pharmaverseadamjnj::adsl %>% filter(.data[[popfl]] == "Y") %>% select(USUBJID, all_of(c(popfl, trtvar))) adsl$colspan_trt <- factor( ifelse(adsl[[trtvar]] == ctrl_grp, " ", "Active Study Agent"), levels = c("Active Study Agent", " ") ) adsl$rrisk_header <- "Risk Difference (%) (95% CI)" adsl$rrisk_label <- paste(adsl[[trtvar]], paste("vs", ctrl_grp)) colspan_trt_map <- create_colspan_map( adsl, non_active_grp = ctrl_grp, non_active_grp_span_lbl = " ", active_grp_span_lbl = "Active Study Agent", colspan_var = "colspan_trt", trt_var = trtvar ) adlb00 <- adlb_complete %>% select( USUBJID, AVISITN, AVISIT, starts_with("PAR"), starts_with("ATOX"), starts_with("ANL"), ONTRTFL, TRTEMFL, AVAL, APOBLFL, ABLFL, LVOTFL ) %>% inner_join(adsl) %>% mutate( ATOXGRL = as.character(ATOXGRL), ATOXGRH = as.character(ATOXGRH) ) %>% relocate( ., USUBJID, ANL04FL, ANL05FL, ONTRTFL, TRTEMFL, AVISIT, ATOXGRL, ATOXGRH, ATOXDSCL, ATOXDSCH, PARAMCD, AVISIT, AVAL, APOBLFL, ABLFL ) # adlb00 <- adlb00 #%>% ## APT comment on PARCAT6 : ## HGB and WBC : Set to "Blood and lymphatic system disorders". ## HGB and WBC parameter are in 2 categories, one for the high and another one for the low direction grading. ## Anemia (HGB low) and Leukocytosis (WBC high) are in the category "Blood and lymphatic system disorders". ## The grading in the opposite directions are categorized under "Investigations". ## Therefor, both PARCAT5 and PARCAT6 are populated for HGB abd WBC. ## Deal with what is needed at later level, when we have splitted low and high # mutate(PARCAT56 = coalesce(PARCAT6,PARCAT5)) %>% # mutate(PARCAT56 = factor(PARCAT56,levels=unique(c(levels(adlb_complete$PARCAT6),levels(adlb_complete$PARCAT5))))) # obj_label(adlb00$PARCAT56) <- "Combined PARCAT56" ### important: previous actions lost the label of variables adlb00 <- var_relabel_list(adlb00, var_labels(adlb_complete, fill = T)) parcat <- unique( adlb00 %>% select(starts_with("PARCAT"), PARAMCD, PARAM, ATOXDSCL, ATOXDSCH) %>% filter(!(is.na(PARCAT5) & is.na(PARCAT6))) ) ### data preparation if (all(selparcat56 != "")) { filtered_adlb <- adlb00 %>% filter((PARCAT5 %in% selparcat56) | (PARCAT6 %in% selparcat56)) } ### low grades : ATOXDSCL ATOXGRL ANL04FL ### Note on Worst On-treatment ### note: by filter ANL04FL/ANL05FL, this table is restricted to On-treatment values, per definition of ANL04FL/ANL05FL ### therefor, no need to add ONTRTFL in filter ### if derivation of ANL04FL/ANL05FL is not restricted to ONTRTFL records, adding ONTRTFL here will not give the correct answer either ### as mixing worst with other period is not giving the proper selection !!! filtered_adlb_low <- filtered_adlb %>% filter(ANL04FL == "Y" & !is.na(ATOXDSCL) & !is.na(ATOXGRL)) %>% mutate( ATOXDSCLH = ATOXDSCL, ATOXGRLH = ATOXGRL, ATOXDIR = "LOW" ) %>% select(USUBJID, starts_with("PAR"), starts_with("ATOX"), TRTEMFL) %>% select(-c(ATOXGRL, ATOXGRH, ATOXDSCL, ATOXDSCH)) ### high grades: ATOXDSCH ATOXGRH ANL05FL filtered_adlb_high <- filtered_adlb %>% filter(ANL05FL == "Y" & !is.na(ATOXDSCH) & !is.na(ATOXGRH)) %>% mutate( ATOXDSCLH = ATOXDSCH, ATOXGRLH = ATOXGRH, ATOXDIR = "HIGH" ) %>% select(USUBJID, starts_with("PAR"), starts_with("ATOX"), TRTEMFL) %>% select(-c(ATOXGRL, ATOXGRH, ATOXDSCL, ATOXDSCH)) ## combine Low and high into adlb_tox filtered_adlb_tox <- bind_rows( filtered_adlb_low, filtered_adlb_high ) %>% select(-c(ATOXGR, ATOXGRN)) %>% inner_join(adsl) ### correction of proper category (PARCAT56) for HGB (LOW) and WBC (HIGH) filtered_adlb_tox <- filtered_adlb_tox %>% mutate( PARCAT56 = case_when( PARAMCD == "HGB" & ATOXDIR == "LOW" ~ PARCAT6, PARAMCD == "WBC" & ATOXDIR == "HIGH" ~ PARCAT6, ### fix on synthetic data !!!! PARAMCD == "WBC" & ATOXDIR == "LOW" ~ "Investigations", TRUE ~ PARCAT5 ) ) %>% mutate( PARCAT56 = factor( PARCAT56, levels = unique(c( "Blood and lymphatic system disorders", levels(adlb_complete$PARCAT5) )) ) ) #### DO NOT USE TRTEMFL = Y in filter, as this will remove subjects from both numerator and denominator #### instead : set ATOXGRLH to a non-reportable value (ie Grade 0) and keep in dataset if (trtemfl) { filtered_adlb_tox <- filtered_adlb_tox %>% mutate( ATOXGRLH = case_when( is.na(TRTEMFL) | TRTEMFL != "Y" ~ "0", TRUE ~ ATOXGRLH ) ) } ## convert some to factors -- lty will fail if these are not factors filtered_adlb_tox <- filtered_adlb_tox %>% mutate( ATOXGRLH = factor(paste("Grade", ATOXGRLH), levels = paste("Grade", 0:5)), ATOXDIR = factor(ATOXDIR, levels = c("LOW", "HIGH")) ) filtered_adlb_tox <- unique( filtered_adlb_tox ) check_non_unique_subject <- filtered_adlb_tox %>% group_by(USUBJID, PARAMCD, ATOXDSCLH) %>% summarize(n_subject = n()) %>% filter(n_subject > 1) if (nrow(check_non_unique_subject)) { message( "Please review your data selection process, subject has multiple records" ) } params <- unique( filtered_adlb_tox %>% select(PARCAT56, PARAMCD, PARAM, ATOXDSCLH, ATOXDIR) ) all_params <- unique( adlb_complete %>% filter(!(is.na(PARCAT5) & is.na(PARCAT6))) %>% select(PARCAT5, PARCAT6, PARAMCD, PARAM, ATOXDSCL, ATOXDSCH) ) ### add relevant extra vars to lbtoxgrade_defs, only restrict to those actually in trial lbtoxgrade_defs <- lbtoxgrade_defs %>% inner_join( ., unique( filtered_adlb_tox %>% select(PARAMCD, PARAM, ATOXDIR, ATOXDSCLH, PARCAT5, PARCAT6, PARCAT56) ), relationship = "many-to-many" ) ### Define param_map to be used in layout param_map <- lbtoxgrade_defs %>% select(PARCAT56, PARAM, PARAMCD, ATOXDIR, ATOXDSCLH, ATOXGRLH) %>% ### for proper sorting: add factor levels to PARAMCD, ATOXDIR mutate( PARAMCD = factor(PARAMCD, levels = levels(adlb00$PARAMCD)), ATOXDIR = factor(ATOXDIR, levels = c("LOW", "HIGH")) ) %>% # ### actual sorting # arrange(PARCAT56,PARAMCD,ATOXDIR,ATOXGRLH) %>% ### actual sorting -- all alphabetic on output arrange(PARCAT56, ATOXDSCLH) %>% ### !!!! no factors are allowed in this split_fun map definition mutate( PARCAT56 = as.character(PARCAT56), PARAMCD = as.character(PARAMCD), PARAM = as.character(PARAM), ATOXDIR = as.character(ATOXDIR), ATOXDSCLH = as.character(ATOXDSCLH) ) # %>% ### !!!! do not remove Grade 0 here, as this would lead to incorrect N and % derivation ### filter(ATOXGRLH != "Grade 0") ### Grade 0 will be removed as a post-processing step # Define layout and build table: ref_path <- c("colspan_trt", " ", trtvar, ctrl_grp) extra_args_rr <- list( method = "wald", denom = "n_df", ref_path = ref_path, .stats = c("denom", "count_unique_fraction") ) extra_args_rr2 <- list( method = "wald", denom = "n_df", ref_path = ref_path, .stats = c("denom", "count_unique_denom_fraction") ) lyt0 <- basic_table(show_colcounts = TRUE, colcount_format = "N=xx") %>% ### first columns split_cols_by( "colspan_trt", split_fun = trim_levels_to_map(map = colspan_trt_map) ) %>% split_cols_by(trtvar) %>% split_cols_by("rrisk_header", nested = FALSE) %>% split_cols_by( trtvar, labels_var = "rrisk_label", split_fun = remove_split_levels(ctrl_grp) ) %>% split_rows_by( "PARCAT56", label_pos = "topleft", child_labels = "visible", split_label = "NCI-CTCAE Category", ### trim_levels_to_map needs to be applied at ALL split_rows_by levels split_fun = trim_levels_to_map(param_map), section_div = " " ) %>% split_rows_by( "ATOXDSCLH", label_pos = "topleft", child_labels = "visible", split_label = "Laboratory Test", ### trim_levels_to_map needs to be applied at ALL split_rows_by levels split_fun = trim_levels_to_map(param_map), section_div = " " ) %>% append_topleft(" Grade, n (%)") # version without explicit denominator (as in shell) lyt <- lyt0 %>% # for testing, it is sometimes convenient to explicitely show the used denominator analyze( "ATOXGRLH", a_freq_j, extra_args = extra_args_rr, show_labels = "hidden", indent_mod = 0L ) result <- build_table(lyt, filtered_adlb_tox, alt_counts_df = adsl) # version with explicit denominator (for verification) lyt2 <- lyt0 %>% # for testing, it is sometimes convenient to explicitely show the used denominator analyze( "ATOXGRLH", a_freq_j, extra_args = extra_args_rr2, show_labels = "visible", indent_mod = 0L ) ### apply layout result2 <- build_table(lyt2, filtered_adlb_tox, alt_counts_df = adsl) # Post-Processing: remove_grade0 <- function(tr) { if (is(tr, "DataRow") & (tr@label == "Grade 0")) { return(FALSE) } else { return(TRUE) } } result <- result %>% prune_table(prune_func = keep_rows(remove_grade0)) result2 <- result2 %>% prune_table(prune_func = keep_rows(remove_grade0)) # Remove colcount from rrisk_header: result <- remove_col_count(result) result2 <- remove_col_count(result2) # Add titles and footnotes: result <- set_titles(result, titles) # Convert to tbl file and output table tt_to_tlgrtf(string_map = string_map, tt = result, file = fileid, orientation = "landscape") ``` ```{r result1, echo=FALSE, message=FALSE, warning=FALSE, test = list(result_v1 = "result")} tt_to_flextable_j(result, tblid, string_map = string_map) ``` [Download RTF file](`r paste0(tolower(tblid), '.rtf')`) ::::