Time-To-Event Data: An Overview and Analysis Considerations

Research output: Contribution to journalArticlepeer-review


In oncology, overall survival and progression-free survival are common time-to-event end points used to measure treatment efficacy. Analyses of this type of data rely on a complex statistical framework and the analysis results are only valid when the data meet certain assumptions. This article provides an overview of time-to-event data, the basic mechanics of common analysis methods, and issues often encountered when analyzing such data. Our goal is to provide clinicians and other lung cancer researchers with the knowledge to choose the appropriate time-to-event analysis methods and to interpret the outcomes of such analyses appropriately. We strongly encourage investigators to seek out statisticians with expertise in survival analysis when embarking on studies that include time-to-event data to ensure that their data are collected and analyzed using the appropriate methods.

Original languageEnglish (US)
Pages (from-to)1067-1074
Number of pages8
JournalJournal of Thoracic Oncology
Issue number7
StatePublished - Jul 2021


  • Competing risks
  • Cox model
  • Kaplan-Meier estimates
  • Log-rank test
  • Survival analysis
  • Time-to-event data

ASJC Scopus subject areas

  • Oncology
  • Pulmonary and Respiratory Medicine


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