Show survival curves based on model scores

Generate survival curves by grouping observations based on model prediction scores. This function is specifically designed for Cox regression models and creates survival curves comparing different risk groups.

Usage

br_show_survival_curves(
  breg,
  idx = NULL,
  n_groups = 3,
  group_labels = NULL,
  title = NULL,
  subtitle = NULL
)

Arguments

breg

A breg object with fitted Cox regression models.

idx

Index or name of the model to use for prediction. If NULL, uses the first model.

n_groups

Number of groups to create based on score quantiles. Default is 3.

group_labels

Custom labels for the groups. If NULL, uses "Low", "Medium", "High" for 3 groups or "Q1", "Q2", etc. for other numbers.

title

Plot title. If NULL, generates automatic title.

subtitle

Plot subtitle.

Value

A ggplot2 object showing survival curves.

See also

Other br_show: br_show_coxph_diagnostics(), br_show_fitted_line(), br_show_fitted_line_2d(), br_show_forest(), br_show_forest_ggstats(), br_show_forest_ggstatsplot(), br_show_nomogram(), br_show_residuals(), br_show_risk_network(), br_show_table(), br_show_table_gt()

Examples

# \donttest{
# Cox regression example with survival curves
if (requireNamespace("survival", quietly = TRUE)) {
  lung <- survival::lung |> dplyr::filter(ph.ecog != 3)
  mds <- br_pipeline(
    lung,
    y = c("time", "status"),
    x = c("age", "ph.ecog"),
    x2 = "sex",
    method = "coxph"
  )
  p <- br_show_survival_curves(mds)
  print(p)
}
#> exponentiate estimates of model(s) constructed from coxph method at default
#> `idx` not set, use the first model

# }