Fixed Time Horizons

A time-to-event prediction must specify when the outcome is evaluated. Use fixed_time_horizons to declare those times in the same unit as times and the prediction model:

fixed_time_horizons = [5.0, 10.0]  # years

Choose clinically meaningful horizons before inspecting performance. Changing the horizon changes the outcome being validated.

Update administrative censoring

At a fixed horizon:

  • an event observed after the horizon is a ๐Ÿคจ non-event at that horizon;
  • event-free follow-up ending before the horizon is ๐Ÿคฌ censored;
  • a primary event observed by the horizon remains ๐Ÿคข; and
  • a competing event observed by the horizon remains ๐Ÿ’€.

Explore the horizon

Move the slider to see how the selected horizon changes each observation. The vertical line marks the horizon; information after it is not used.

The symbols are:

  • ๐Ÿคฌ censored before the horizon;
  • ๐Ÿคข primary event;
  • ๐Ÿคจ non-event through the horizon; and
  • ๐Ÿ’€ competing event.

Pass horizons to rtichoke

performance_data = rk.prepare_performance_data_times(
    probs=probs,
    reals=reals,
    times=times,
    fixed_time_horizons=[5.0, 10.0],
)