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tables/tet01.qmd

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+---
+title: TET1
+subtitle: Time-to-Event Summary Tables
+---
+
+------------------------------------------------------------------------
+
+::: panel-tabset
+## Setup
+
+We will use the `synthetic_cdisc_data$adtte` data set from the `scda` package for the time-to-event summary table.
+We start by filtering the `adtte` data set for the overall survival observations, converting time of overall survival to months, creating new variables for event and non-event information and binarizing the `ARM` variable.
+
+```{r, message = FALSE}
+library(tern)
+library(dplyr)
+
+adtte <- scda::synthetic_cdisc_data("rcd_2022_06_27")$adtte %>% 
+  df_explicit_na() %>%
+  filter(
+    PARAMCD == "OS"
+  ) %>%
+  mutate(
+    AVAL = day2month(AVAL),
+    AVALU = "Months",
+    is_event = CNSR == 0,
+    is_not_event = CNSR == 1,
+    ARM_BIN = fct_collapse_only(
+      ARM,
+      CTRL = c("B: Placebo"),
+      TRT = c("A: Drug X", "C: Combination")
+    )
+  )
+```
+
+## Table
+
+This time-to-event summary table splits the columns by treatment arm using `split_cols_by()`, creates a summary for patients with and without event using `summarize_vars()`, summarizes survival time using `surv_time()` and summarizes the analysis from unstratified Cox Proportional Hazards models using `coxph_pairwise()`.
+
+```{r}
+lyt <- basic_table() %>% 
+  split_cols_by(
+    var = "ARM_BIN",
+    ref_group = "CTRL"
+  ) %>% 
+  add_colcounts() %>% 
+  summarize_vars(
+    vars = "is_event",
+    .stats = "count_fraction",
+    .labels = c(count_fraction = "Patients with event (%)"),
+    nested = FALSE,
+    show_labels = "hidden"
+  ) %>% 
+  summarize_vars(
+    vars = "is_not_event",
+    .stats = "count_fraction",
+    .labels = c(count_fraction = "Patients without event (%)"),
+    nested = FALSE,
+    show_labels = "hidden"
+  ) %>% 
+  surv_time(
+    vars = "AVAL",
+    var_labels = "Time to Event (months)",
+    is_event = "is_event",
+    table_names = "time_to_event"
+  ) %>% 
+  coxph_pairwise(
+    vars = "AVAL",
+    is_event = "is_event",
+    var_labels = c("Unstratified Analysis"),
+    control = control_coxph(pval_method = "log-rank"),
+    table_names = "coxph_unstratified"
+  )
+
+build_table(lyt, adtte)
+```
+
+## Time-to-Event Summary Table with Stratified Analysis (TET1A)
+
+We can add the summary of an analysis with Cox Proportional Hazards models stratified by `SEX` to the table above using `coxph_pairwise()`.
+
+```{r}
+lyt2 <- lyt %>% 
+  coxph_pairwise(
+    vars = "AVAL",
+    is_event = "is_event",
+    var_labels = c("Stratified Analysis"),
+    strat = "SEX",
+    control = control_coxph(pval_method = "log-rank"),
+    table_names = "coxph_stratified"
+  ) 
+
+build_table(lyt2, adtte)
+```
+
+{{< include ../session_info.qmd >}}
+:::