added medSurvCI, medSurvQuant as summary statistics for survival

R/tableby.R

@@ -126,7 +126,7 @@ tableby <- function(formula, data, na.action, subset=NULL, weights=NULL, strata,
 
  Call <- match.call()
  ## Tell user if they passed an argument that was not expected, either here or in control
- expectArgs <- c("formula", "data", "na.action", "subset", "weights", "strata", "control", names(control), "times")
+ expectArgs <- c("formula", "data", "na.action", "subset", "weights", "strata", "control", names(control), "times","survconf.type")
  match.idx <- match(names(Call)[-1], expectArgs)
  if(anyNA(match.idx)) warning("unused arguments: ", paste(names(Call)[1+which(is.na(match.idx))], collapse=", "), "\n")
 
@@ -401,11 +401,11 @@ tableby <- function(formula, data, na.action, subset=NULL, weights=NULL, strata,
  for(bylev in by.levels) {
  idx <- bycol == bylev
  bystatlist[[bylev]] <- do.call(statfun, list(currcol[idx], levels=xlevels, na.rm=TRUE,
- weights=weightscol[idx], conf.level=control$conf.level, times=control$times))
+ weights=weightscol[idx], conf.level=control$conf.level, times=control$times, survconf.type=control$survconf.type))
  }
  ## add Total
  bystatlist[[totallab]] <- do.call(statfun, list(currcol, levels=xlevels, na.rm=TRUE,
- weights=weightscol, conf.level=control$conf.level, times=control$times))
+ weights=weightscol, conf.level=control$conf.level, times=control$times, survconf.type=control$survconf.type))
  }
  statList[[statfun2]] <- bystatlist
  }

R/tableby.control.R

@@ -149,6 +149,7 @@ add_tbc_stats_labels <- function(x) {
  mean = "Mean", sd = "SD", var = "Var", max = "Max", min = "Min", meanCI = "Mean (CI)", sum = "Sum",
  gmean = "Geom Mean", gsd = "Geom SD", gmeansd = "Geom Mean (Geom SD)", gmeanCI = "Geom Mean (CI)",
  range="Range", Npct="N (%)", Nrowpct="N (%)", Nevents="Events", medSurv="Median Survival",
+ medSurvQuant="Median (Q1, Q3) Survival", medSurvCI="Median (CI)",
  medTime = "Median Follow-Up", medianmad="Median (MAD)", Nsigntest = "N (sign test)",
  overall = "Overall", total = "Total", difference = "Difference"
  )

R/tableby.stats.R

@@ -313,6 +313,46 @@ medSurv <- function(x, na.rm = TRUE, weights = NULL, ...) {
  as.tbstat(y)
 }
 
+## Median survival with confidence interval
+#' @rdname tableby.stats
+#' @export
+medSurvCI <- function (x, na.rm = TRUE, weights = NULL, robust = FALSE, conf.type = 'log', ...) {
+ y <- if (na.rm && allNA(x)) {
+ NA_real_
+ }
+ else {
+ arsenal:::check_pkg("survival")
+ mat <- summary(survival::survfit(x ~ 1,
+ weights = weights,
+ robust = robust,
+ conf.type =conf.type))$table
+ m <- as.numeric(mat["median"])
+ ci <- c(as.numeric(mat["0.95LCL"]), as.numeric(mat["0.95UCL"]))
+ c(m, ci)
+ }
+ as.tbstat(y, fmt = "{y[1]} ({y[2]}, {y[3]})")
+}
+
+## Median survival with 25th/75th quantiles
+#' @rdname tableby.stats
+#' @export
+medSurvQuant <- function (x, na.rm = TRUE, weights = NULL, robust = FALSE, ...) {
+ y <- if (na.rm && allNA(x)) {
+ NA_real_
+ }
+ else {
+ arsenal:::check_pkg("survival")
+ mat <- quantile(survival::survfit(x ~ 1,
+ weights = weights,
+ robust = robust
+ ),
+ probs=c(0.5,0.25, 0.75))$quantile
+ mat
+ }
+ as.tbstat(y, fmt = "{y[1]} ({y[2]}, {y[3]})")
+}
+
+
 #' @rdname tableby.stats
 #' @export
 NeventsSurv <- function(x, na.rm = TRUE, weights = NULL, times=1:5, ...) {

vignettes/tableby.Rmd

@@ -319,7 +319,15 @@ summary(survfit(Surv(fu.time/365.25, fu.stat)~sex, data=mockstudy), times=1:5)
 ```
 
 ```{r, results='asis', eval=ge330}
-summary(tableby(sex ~ Surv(fu.time/365.25, fu.stat), data=mockstudy, times=1:5, surv.stats=c("NeventsSurv","NriskSurv")))
+summary(tableby(sex ~ Surv(fu.time/365.25, fu.stat), data=mockstudy, times=1:3, surv.stats=c("NeventsSurv")))
+
+summary(tableby(sex ~ Surv(fu.time/365.25, fu.stat), data=mockstudy, times=1:5, surv.stats=c("NriskSurv")))
+
+summary(tableby(sex ~ Surv(fu.time/365.25, fu.stat), data=mockstudy, surv.stats="medSurvCI", survconf.type='log-log'), digits=2)
+
+summary(tableby(sex ~ Surv(fu.time/365.25, fu.stat), data=mockstudy, surv.stats="medSurvQuant"), digits=2)
+
+
 ```
 
 ## 5. Summarize date variables