Benefits of combining prevalent and incident cohorts: An application to myotonic dystrophy

David B. Wolfson, Ana F. Best, Vittorio Addona, Julian Wolfson, Shahinaz M. Gadalla

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

It is frequently of interest to estimate the time that individuals survive with a disease, that is, to estimate the time between disease onset and occurrence of a clinical endpoint such as death. Epidemiologic survival data are commonly collected from either an incident cohort, whose members' disease onset occurs after the study baseline date, or from a cohort with prevalent disease that is followed forward in time. Incident cohort survival data are limited by study termination, while prevalent cohort data provide biased (left-truncated) survival data. In this article, we investigate the advantages of a study design featuring simultaneous follow-up of prevalent and incident cohorts to the estimation of the survivor function. Our analyses are supported by simulations and illustrated using data on survival after myotonic dystrophy diagnosis from the United Kingdom Clinical Practice Research Datalink (CPRD). We demonstrate that the NPMLE using combined incident and prevalent cohort data estimates the true survivor function very well, even for moderate sample sizes, and ameliorates the disadvantages of using a purely incident or prevalent cohort.

Original languageEnglish (US)
Pages (from-to)3333-3345
Number of pages13
JournalStatistical methods in medical research
Volume28
Issue number10-11
DOIs
StatePublished - Nov 1 2019

Keywords

  • Canadian longitudinal study on aging
  • UK clinical practice research datalink
  • delayed entry
  • incident cohort
  • left truncation
  • myotonic dystrophy
  • prevalent cohort
  • survival analysis

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Intramural

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