Merge branch 'main' into stable-tlg-catalog

book/generate-index.R

@@ -37,21 +37,41 @@ cat(
 # Tables
 
 section_header("Tables")
+create_subsection("./tables/ADA", "ADA")
 create_subsection("./tables/adverse-events", "Adverse Events")
+create_subsection("./tables/concomitant-medications", "Concomitant Medications")
+create_subsection("./tables/deaths", "Deaths")
+create_subsection("./tables/demography", "Demography")
+create_subsection("./tables/disclosures", "Disclosures")
+create_subsection("./tables/disposition", "Disposition")
+create_subsection("./tables/ECG", "ECG")
 create_subsection("./tables/efficacy", "Efficacy")
+create_subsection("./tables/exposure", "Exposure")
 create_subsection("./tables/lab-results", "Lab Results")
+create_subsection("./tables/medical-history", "Medical History")
 create_subsection("./tables/pharmacokinetic", "Pharmacokinetic")
+create_subsection("./tables/risk-management-plan", "Risk Management Plan")
 create_subsection("./tables/safety", "Safety")
-create_subsection("./tables/other", "Other")
+create_subsection("./tables/vital-signs", "Vital Signs")
 
 # Listings
 
 section_header("Listings")
+create_subsection("./listings/ADA", "ADA")
+create_subsection("./listings/adverse-events", "Adverse Events")
+create_subsection("./listings/concomitant-medications", "Concomitant Medications") # nolint
+create_subsection("./listings/disposition", "Disposition")
+create_subsection("./listings/development-safety-update-report", "Development Safety Update Report") # nolint
+create_subsection("./listings/ECG", "ECG")
+create_subsection("./listings/exposure", "Exposure")
+create_subsection("./listings/lab-results", "Lab Results")
+create_subsection("./listings/medical-history", "Medical History")
 create_subsection("./listings/pharmacokinetic", "Pharmacokinetic")
-create_subsection("./listings/other", "Other")
+create_subsection("./listings/vital-signs", "Vital Signs")
 
 # Graphs
 
 section_header("Graphs")
+create_subsection("./graphs/efficacy", "Efficacy")
 create_subsection("./graphs/pharmacokinetic", "Pharmacokinetic")
 create_subsection("./graphs/other", "Other")

book/tables/pharmacokinetic/pkct01.qmd

@@ -10,6 +10,139 @@ subtitle: Summary Concentration Table
 ::: panel-tabset
 ## Data Setup
 
+```{r setup, message=FALSE}
+#| code-fold: show
+
+library(scda)
+library(dplyr)
+library(tern)
+
+adsl <- synthetic_cdisc_dataset("latest", "adsl") %>%
+  filter(ACTARM == "A: Drug X")
+adpc <- synthetic_cdisc_dataset("latest", "adpc") %>%
+  filter(ACTARM == "A: Drug X", PARAM == "Plasma Drug X")
+
+# Setting up the data
+adpc_1 <- adpc %>%
+  mutate(
+    NFRLT = as.factor(NFRLT),
+    AVALCAT1 = as.factor(AVALCAT1)
+  ) %>%
+  select(NFRLT, ACTARM, VISIT, AVAL, PARAM, AVALCAT1) %>%
+  var_relabel(NFRLT = "Nominal Time from First Dose (hr)")
+
+# Row structure
+lyt_rows <- basic_table() %>%
+  split_rows_by(
+    var = "ACTARM",
+    split_fun = drop_split_levels,
+    split_label = "Treatment Group",
+    label_pos = "topleft"
+  ) %>%
+  add_rowcounts(alt_counts = TRUE) %>%
+  split_rows_by(
+    var = "VISIT",
+    split_fun = drop_split_levels,
+    split_label = "Visit",
+    label_pos = "topleft"
+  ) %>%
+  split_rows_by(
+    var = "NFRLT",
+    split_fun = drop_split_levels,
+    split_label = obj_label(adpc_1$NFRLT),
+    label_pos = "topleft",
+    child_labels = "hidden"
+  )
+```
+
+## Standard Table (Stats in Columns)
+
+```{r variant1, test = list(result_v1 = "result")}
+lyt <- lyt_rows %>%
+  analyze_vars_in_cols(
+    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
+    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
+    .formats = c(
+      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
+      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
+    ),
+    .labels = c(
+      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
+      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
+    ),
+    na_level = "NE",
+    .aligns = "decimal"
+  )
+
+result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
+
+# Decorating
+main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
+subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
+main_footer(result) <- "NE: Not Estimable"
+
+result
+```
+
+## Table Implementing 1/3 Imputation Rule
+
+```{r variant2, test = list(result_v2 = "result")}
+lyt <- lyt_rows %>%
+  analyze_vars_in_cols(
+    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
+    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
+    .formats = c(
+      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
+      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
+    ),
+    .labels = c(
+      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
+      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
+    ),
+    imp_rule = "1/3",
+    .aligns = "decimal"
+  )
+
+result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
+
+# Decorating
+main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
+subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
+main_footer(result) <- c("NE: Not Estimable", "ND: Not Derived")
+
+result
+```
+
+## Table Implementing 1/2 Imputation Rule
+
+```{r variant3, test = list(result_v3 = "result")}
+lyt <- lyt_rows %>%
+  analyze_vars_in_cols(
+    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
+    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
+    .formats = c(
+      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
+      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
+    ),
+    .labels = c(
+      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
+      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
+    ),
+    imp_rule = "1/2",
+    .aligns = "decimal"
+  )
+
+result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
+
+# Decorate table
+main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
+subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
+main_footer(result) <- "ND: Not Derived"
+
+result
+```
+
+{{< include ../../test-utils/save_results.qmd >}}
 
 ## `teal` App
 

book/tables/pharmacokinetic/pkpt03.qmd

@@ -17,23 +17,80 @@ library(scda)
 library(dplyr)
 library(tern)
 
+# Preprocess analysis data ----
 adpp <- synthetic_cdisc_dataset("latest", "adpp")
-adpp <- adpp %>% filter(PPSPEC == "Plasma", AVISIT == "CYCLE 1 DAY 1")
+adpp <- adpp %>%
+  filter(PPSPEC == "Plasma") %>%
+  filter(AVISIT %in% c("CYCLE 1 DAY 1", "CYCLE 1 DAY 2")) %>%
+  h_pkparam_sort() %>%
+  mutate(PARAM = factor(paste0(TLG_DISPLAY, " (", AVALU, ")"))) %>%
+  mutate(PARAM = reorder(PARAM, TLG_ORDER))
+
+# Preprocess subject-level data ----
+adsl <- synthetic_cdisc_dataset("latest", "adsl")
+
+# Workaround needed to include (N=xx) population counts
+# Repeat ADSL by the number of levels in AVISIT
+# Include AVISIT and dummy PARAM as it's needed for trim_levels_in_group
+adsl_tmp <- adsl %>%
+  select(STUDYID, USUBJID, ARMCD) %>%
+  unique() %>%
+  mutate(PARAM = factor(NA_character_, levels = levels(adpp$PARAM)))
+
+# Data for Plasma Drug X example ----
+adpp_x <- adpp %>%
+  filter(PPCAT == "Plasma Drug X") %>%
+  # Please do not replicate mutate statement below!
+  # It is used to make the random data in this example more realistic
+  # as not all parameters are always available across all visits.
+  mutate(
+    AVAL = if_else(
+      ARMCD == "ARM A" & AVISIT == "CYCLE 1 DAY 1" & PARAM == "Cmax (ug/mL)",
+      NA_real_, AVAL
+    )
+  )
+
+adpp_x_tmp <- adpp_x %>%
+  select(STUDYID, USUBJID, ARMCD, AVISIT) %>%
+  unique()
+
+adsl_x_splitvars <- adsl_tmp %>%
+  left_join(adpp_x_tmp, by = c("STUDYID", "USUBJID", "ARMCD")) %>%
+  filter(!is.na(AVISIT))
+
+# Data for Plasma Drug Y example ----
+adpp_y <- adpp %>%
+  filter(PPCAT == "Plasma Drug Y")
+
+adpp_y_tmp <- adpp_y %>%
+  select(STUDYID, USUBJID, ARMCD, AVISIT) %>%
+  unique()
+
+adsl_y_splitvars <- adsl_tmp %>%
+  left_join(adpp_y_tmp, by = c("STUDYID", "USUBJID", "ARMCD")) %>%
+  filter(!is.na(AVISIT))
 ```
 
 ## Standard Table
 
 ```{r}
 # lyt creation
 lyt <- basic_table() %>%
+  split_rows_by(
+    var = "AVISIT",
+    split_fun = drop_split_levels,
+    split_label = "Visit",
+    page_by = TRUE
+  ) %>%
   split_rows_by(
     var = "ARMCD",
-    split_fun = trim_levels_in_group("ARMCD"),
+    split_fun = trim_levels_in_group("PARAM"),
     label_pos = "topleft",
     split_label = "Treatment Arm"
   ) %>%
+  add_rowcounts(alt_counts = TRUE) %>%
   split_rows_by(
-    var = "PKPARAM",
+    var = "PARAM",
     label_pos = "topleft",
     split_label = "PK Parameter",
     child_labels = "hidden"
@@ -58,45 +115,48 @@ lyt <- basic_table() %>%
     ),
     .formats = c(
       n = "xx.",
-      mean = sprintf_format("%.3e"),
-      sd = sprintf_format("%.3e"),
+      mean = format_sigfig(3),
+      sd = format_sigfig(3),
       cv = "xx.x",
-      median = sprintf_format("%.3e"),
-      geom_mean = sprintf_format("%.3e"),
+      median = format_sigfig(3),
+      geom_mean = format_sigfig(3),
       geom_cv = "xx.x",
-      min = sprintf_format("%.3e"),
-      max = sprintf_format("%.3e")
-    )
+      min = format_sigfig(3),
+      max = format_sigfig(3)
+    ),
+    na_level = "NE"
   )
 ```
 
 #### Plasma Drug X
 
 ```{r variant1, test = list(result_v1 = "result")}
-adpp0 <- adpp %>%
-  filter(PPCAT == "Plasma Drug X") %>%
-  h_pkparam_sort() %>%
-  mutate(PKPARAM = factor(paste0(TLG_DISPLAY, " (", AVALU, ")"))) %>%
-  mutate(PKPARAM = reorder(PKPARAM, TLG_ORDER))
-
-result <- build_table(lyt, df = adpp0)
-main_title(result) <- paste("Summary of", unique(adpp0$PPSPEC), "PK Parameter by Treatment Arm, PK Population")
-subtitles(result) <- paste("Analyte:", unique(adpp0$PPCAT), "\nVisit:", unique(adpp0$AVISIT))
+result <- build_table(lyt, df = adpp_x, alt_counts_df = adsl_x_splitvars)
+main_title(result) <- paste("Summary of", unique(adpp_x$PPSPEC), "PK Parameter by Treatment Arm, PK Population")
+subtitles(result) <- paste("Analyte:", unique(adpp_x$PPCAT))
+result <- paginate_table(result, landscape = TRUE)
 result
 ```
 
-#### Plasma Drug Y
+#### Plasma Drug X: Remove Rows with 0s
 
 ```{r variant2, test = list(result_v2 = "result")}
-adpp1 <- adpp %>%
-  filter(PPCAT == "Plasma Drug Y") %>%
-  h_pkparam_sort() %>%
-  mutate(PKPARAM = factor(paste0(TLG_DISPLAY, " (", AVALU, ")"))) %>%
-  mutate(PKPARAM = reorder(PKPARAM, TLG_ORDER))
+result <- build_table(lyt, df = adpp_x, alt_counts_df = adsl_x_splitvars) %>%
+  prune_table()
+
+main_title(result) <- paste("Summary of", unique(adpp_x$PPSPEC), "PK Parameter by Treatment Arm, PK Population")
+subtitles(result) <- paste("Analyte:", unique(adpp_x$PPCAT))
+result <- paginate_table(result, landscape = TRUE)
+result
+```
+
+#### Plasma Drug Y
 
-result <- build_table(lyt, df = adpp1)
-main_title(result) <- paste("Summary of", unique(adpp1$PPSPEC), "PK Parameter by Treatment Arm, PK Population")
-subtitles(result) <- paste("Analyte:", unique(adpp1$PPCAT), "\nVisit:", unique(adpp1$AVISIT))
+```{r variant3, test = list(result_v3 = "result")}
+result <- build_table(lyt, df = adpp_y, alt_counts_df = adsl_y_splitvars)
+main_title(result) <- paste("Summary of", unique(adpp_y$PPSPEC), "PK Parameter by Treatment Arm, PK Population")
+subtitles(result) <- paste("Analyte:", unique(adpp_y$PPCAT))
+result <- paginate_table(result, landscape = TRUE)
 result
 ```