TY - JOUR

T1 - Cumulative risk regression in case–cohort studies using pseudo-observations

AU - Parner, Erik T.

AU - Andersen, Per K.

AU - Overgaard, Morten

PY - 2020

Y1 - 2020

N2 - Case–cohort studies are useful when information on certain risk factors is difficult or costly to ascertain. Particularly, a case–cohort study may be well suited in situations where several case series are of interest, e.g. in studies with competing risks, because the same sub-cohort may serve as a comparison group for all case series. Previous analyses of this kind of sampled cohort data most often involved estimation of rate ratios based on a Cox regression model. However, with competing risks this method will not provide parameters that directly describe the association between covariates and cumulative risks. In this paper, we study regression analysis of cause-specific cumulative risks in case–cohort studies using pseudo-observations. We focus mainly on the situation with competing risks. However, as a by-product, we also develop a method by which absolute mortality risks may be analyzed directly from case–cohort survival data. We adjust for the case–cohort sampling by inverse sampling probabilities applied to a generalized estimation equation. The large-sample properties of the proposed estimator are developed and small-sample properties are evaluated in a simulation study. We apply the methodology to study the effect of a specific diet component and a specific gene on the absolute risk of atrial fibrillation.

AB - Case–cohort studies are useful when information on certain risk factors is difficult or costly to ascertain. Particularly, a case–cohort study may be well suited in situations where several case series are of interest, e.g. in studies with competing risks, because the same sub-cohort may serve as a comparison group for all case series. Previous analyses of this kind of sampled cohort data most often involved estimation of rate ratios based on a Cox regression model. However, with competing risks this method will not provide parameters that directly describe the association between covariates and cumulative risks. In this paper, we study regression analysis of cause-specific cumulative risks in case–cohort studies using pseudo-observations. We focus mainly on the situation with competing risks. However, as a by-product, we also develop a method by which absolute mortality risks may be analyzed directly from case–cohort survival data. We adjust for the case–cohort sampling by inverse sampling probabilities applied to a generalized estimation equation. The large-sample properties of the proposed estimator are developed and small-sample properties are evaluated in a simulation study. We apply the methodology to study the effect of a specific diet component and a specific gene on the absolute risk of atrial fibrillation.

KW - Case–cohort study

KW - Competing risks

KW - Cumulative incidence

KW - Cumulative risk

KW - Pseudo-observations

U2 - 10.1007/s10985-020-09492-3

DO - 10.1007/s10985-020-09492-3

M3 - Journal article

C2 - 31933047

AN - SCOPUS:85077840745

VL - 26

SP - 639

EP - 658

JO - Lifetime Data Analysis

JF - Lifetime Data Analysis

SN - 1380-7870

IS - 4

ER -