Challenges in risk estimation using routinely collected clinical data: The example of estimating cervical cancer risks from electronic health-records.

ABSTRACT: Electronic health-records (EHR) are increasingly used by epidemiologists studying disease following surveillance testing to provide evidence for screening intervals and referral guidelines. Although cost-effective, undiagnosed prevalent disease and interval censoring (in which asymptomatic disease is only observed at the time of testing) raise substantial analytic issues when estimating risk that cannot be addressed using Kaplan-Meier methods. Based on our experience analysing EHR from cervical cancer screening, we previously proposed the logistic-Weibull model to address these issues. Here we demonstrate how the choice of statistical method can impact risk estimates. We use observed data on 41,067 women in the cervical cancer screening program at Kaiser Permanente Northern California, 200

SUBMITTER: Landy R 

PROVIDER: S-EPMC5930038 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature