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Cumulative incidence function estimation using population-based biobank data

  • Malka Gorfine*
  • , David M. Zucker
  • , Shoval Shoham
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Many countries have established population-based biobanks, which are being used increasingly in epidemiological and clinical research. These biobanks offer opportunities for large-scale studies addressing questions beyond the scope of traditional clinical trials or cohort studies. However, using biobank data poses new challenges. Typically, biobank data are collected from a study cohort recruited over a defined calendar period, with subjects entering the study at various ages falling between and. This work focuses on biobank data with individuals reporting disease-onset age upon recruitment, termed prevalent data, along with individuals initially recruited as healthy, and their disease onset observed during the follow-up period. We propose a novel cumulative incidence function (CIF) estimator that efficiently incorporates prevalent cases, in contrast to existing methods, providing two advantages: (1) increased efficiency and (2) CIF estimation for ages before the lower limit,.

Original languageEnglish
Article numberujaf049
JournalBiometrics
Volume81
Issue number3
DOIs
StatePublished - 1 Sep 2025

Bibliographical note

Publisher Copyright:
© 2025 The Author(s). Published by Oxford University Press on behalf of The International Biometric Society.

Keywords

  • Aalen-Johansen estimator
  • delayed entry
  • illness-death model
  • left truncation
  • survival analysis

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