Dynamic risk prediction for diabetes using biomarker change measurements.

ABSTRACT:

Background

Dynamic risk models, which incorporate disease-free survival and repeated measurements over time, might yield more accurate predictions of future health status compared to static models. The objective of this study was to develop and apply a dynamic prediction model to estimate the risk of developing type 2 diabetes mellitus.

Methods

Both a static prediction model and a dynamic landmark model were used to provide predictions of a 2-year horizon time for diabetes-free survival, updated at 1, 2, and 3 years post-baseline i.e., predicting diabetes-free survival to 2 years and predicting diabetes-free survival to 3 years, 4 years, and 5 years post-baseline, given the patient already survived past 1 year, 2 years, and 3 years post-baseline, respectively. Prediction acc

SUBMITTER: Parast L 

PROVIDER: S-EPMC6694545 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature