Sample-weighted semiparametric estimation of cause-specific cumulative risk and incidence using left- or interval-censored data from electronic health records.

ABSTRACT: Electronic health records (EHRs) can be a cost-effective data source for forming cohorts and developing risk models in the context of disease screening. However, important issues need to be handled: competing outcomes, left-censoring of prevalent disease, interval-censoring of incident disease, and uncertainty of prevalent disease when accurate disease ascertainment is not conducted at baseline. Furthermore, novel tests that are costly and limited in availability can be conducted on stored biospecimens selected as samples from EHRs by using different sampling fractions. We extend sample-weighted semiparametric marginal mixture models to estimating competing risks. For flexible modeling of relative risks, a general transformation of the subdistribution hazard function and regression paramet

SUBMITTER: Hyun N 

PROVIDER: S-EPMC12416197 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature