Analysis of composite endpoints with component-wise censoring in the presence of differential visit schedules

Anne A. Eaton, Emily C. Zabor

Research output: Contribution to journalArticlepeer-review


Composite endpoints are very common in clinical research, such as recurrence-free survival in oncology research, defined as the earliest of either death or disease recurrence. Because of the way data are collected in such studies, component-wise censoring is common, where, for example, recurrence is an interval-censored event and death is a right-censored event. However, a common way to analyze such component-wise censored composite endpoints is to treat them as right-censored, with the date at which the non-fatal event was detected serving as the date the event occurred. This approach is known to introduce upward bias when the Kaplan-Meier estimator is applied, but has more complex impact on semi-parametric regression approaches. In this article we compare the performance of the Cox model estimators for right-censored data and the Cox model estimators for interval-censored data in the context of component-wise censored data where the visit process differs across levels of a covariate of interest, a common scenario in observational data. We additionally examine estimators of the cause-specific hazard when applied to the individual components of such component-wise censored composite endpoints. We found that when visit schedules differed according to levels of a covariate of interest, the Cox model estimators for right-censored data and the estimators for cause-specific hazards were increasingly biased as the frequency of visits decreased. The Cox model estimator for interval-censored data with censoring at the last disease-free date is recommended for use in the presence of differential visit schedules.

Original languageEnglish (US)
Pages (from-to)1599-1612
Number of pages14
JournalStatistics in Medicine
Issue number9
StatePublished - Apr 30 2022

Bibliographical note

Funding Information:
This publication is based on research using information obtained from, which is maintained by Project Data Sphere. Neither Project Data Sphere nor the owner(s) of any information from the web site have contributed to, approved or are in any way responsible for the contents of this publication. Research reported in this publication was supported in part by the National Cancer Institute of the National Institutes of Health, Grant number: P30 CA77598.

Publisher Copyright:
© 2022 John Wiley & Sons Ltd.


  • Cox proportional hazards regression
  • component-wise censoring
  • composite endpoint
  • interval censoring
  • observational study
  • right censoring
  • survival analysis

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural


Dive into the research topics of 'Analysis of composite endpoints with component-wise censoring in the presence of differential visit schedules'. Together they form a unique fingerprint.

Cite this