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 language | English |
|---|---|
| Article number | ujaf049 |
| Journal | Biometrics |
| Volume | 81 |
| Issue number | 3 |
| DOIs | |
| State | Published - 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
Fingerprint
Dive into the research topics of 'Cumulative incidence function estimation using population-based biobank data'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver