Cumulative incidence function estimation using population-based biobank data

Area of Science:

• Epidemiology
• Biostatistics
• Biobanking Research

Background:

• Population-based biobanks are crucial for large-scale epidemiological and clinical research.
• Utilizing biobank data presents unique challenges, particularly with prevalent cases and age-related cohort entry.
• Existing methods struggle to efficiently incorporate prevalent disease data and estimate incidence at early ages.

Purpose of the Study:

• To develop a novel cumulative incidence function (CIF) estimator for biobank data.
• To efficiently incorporate prevalent cases into CIF estimation.
• To enable CIF estimation for disease onset ages below the lower recruitment limit ($c_L$).

Main Methods:

• Development of a new cumulative incidence function (CIF) estimator.
• Incorporation of prevalent disease data (individuals with disease at recruitment).
• Analysis of individuals recruited as healthy with disease onset during follow-up.

Main Results:

• The proposed CIF estimator demonstrates increased statistical efficiency.
• The method successfully provides CIF estimates for disease onset ages prior to the cohort's lower age limit ($c_L$).
• Enhanced ability to analyze disease incidence across a wider age range using biobank data.

Conclusions:

• The novel CIF estimator offers significant advantages for biobank data analysis.
• Improved efficiency and expanded age range for incidence estimation are key benefits.
• This method advances epidemiological research using large-scale biobank resources.