Kaplan-Meier Survival Curve
Description on how the survival plot data is calculated


How to build a Kaplan-Meier tile to a dashboard

To generate a survival plot, select 1 numerical field, which represents time, and 1 categorical field, which will be transformed into the individual’s status.
Dimension 1
Dimension 2
1x numerical
1x categorical
The categorical field should use one of the following 4 terms (case-insensitive) to indicate a status of "Living": “living”, “alive”, “diseasefree”, “disease-free”
For multi-entity datasets, survival curve charts only support data fields from the main entity, or entities with 1:1 relation to the main entity.

Survival Percentage Calculation

To calculate survival percent at the current event the system evaluates the following formula:
ST: Survival at the current event
LT0: Number of subjects living at the start of the period or event
D: Number of subjects that died
For each time period the following values are generated:
  • Each individual is considered Dead unless they qualify as Living
Number of Subjects Living at the Start (LT0)
  • For the initial value this is the total number of records returned by the backend from survival data with Living or Dead Status.
  • For followup events this is the number of subjects at the start of the previous event minus the number of subjects that died in the previous event and the subjects that dropped out or were censored in the previous event
Number of Subjects that Died (D)
  • 1 for each individual who at the event does not have a status of Living
Number of Subjects Dropped or Censored
  • 1 for each individual who at the event has a status of Living
Survival Percent at the Current Event (ST)
Cumulative Survival (S)
  • ST-1: Survival percent at the previous event
NOTE: this is the actual point drawn on the survival plot