Efficient Cumulative Incidence Estimation in Biobank Studies Using All Prevalent and Incident Events

2026-06-17

AI Summary

This study addresses the incidence time bias arising in biobank cohorts where prevalent cases (diagnosed before recruitment) coexist with incident cases (diagnosed during follow-up). To tackle this challenge, the authors propose a novel nonparametric estimator for the cumulative incidence function (CIF) that jointly models all diseased individuals—regardless of their disease onset time or survival trajectory—within a unified framework grounded in truncation data theory. The estimator is rigorously supported by asymptotic analysis to ensure desirable statistical properties. Application to UK Biobank cancer data and extensive simulation studies demonstrate that the proposed method substantially outperforms existing approaches, achieving markedly reduced bias while maintaining excellent convergence behavior, particularly for diseases characterized by early onset and long-term survival.

Abstract

Population-based biobanks, now established in many countries, offer opportunities for large-scale studies investigating the incidence of various diseases. Biobank data is typically collected from a study cohort recruited over a defined calendar period, with subjects entering the study at various ages falling between $R_L$ and $R_U$. This work focuses on biobank data that includes individuals in whom onset of the disease of interest occurred before recruitment, termed prevalent cases, along with individuals initially recruited as disease-free in whom disease onset occurred during the follow-up period. We propose a novel cumulative incidence function (CIF) estimator that goes beyond existing methods in that it incorporates all disease cases, both prevalent and incident, irrespective of their subsequent life course. In particular, the new method can handle situations involving diseases that can occur at young ages with long survival after disease onset. Asymptotic properties of the new method are established and a simulation study is presented examining the performance of the method. We illustrate the use of the method and highlight its advantages over existing methods with an application to cancer data from the UK biobank.

Problem

• cumulative incidence
• biobank
• prevalent cases
• incident cases
• disease incidence

Innovation

• cumulative incidence function
• prevalent cases
• incident cases
• biobank studies
• asymptotic properties