Which statement best describes a way to quantify time to event in survival analysis?

• A. Overall probability of event
• B. Mean time to event
• C. Incidence rate
• D. Prevalence

Answer: (B)

In survival analysis, the key idea is to capture how long it takes for an event to occur for each subject. The statement that describes the mean time to the event directly quantifies this duration, giving the expected amount of time until the event happens. This reflects the time-to-event nature of the data and aligns with how survival distributions are used to summarize patterns of timing.

Other options don’t measure time until the event. A simple probability of the event looks at whether it occurs within a fixed window, not how long it takes. An incidence rate expresses how fast events occur per person-time, which is a rate rather than a duration for each individual. Prevalence is just a snapshot proportion of people with the condition at a point in time, not the timing of the event.

Note that in practice, the mean can be affected by censoring and skewed survival times, so the median survival time is often reported as a robust alternative. Still, the concept of time-to-event is best conveyed by a measure that summarizes the duration until the event occurs, such as the mean time to event.