Prediction Models for Type 2 Diabetes Risk in the General Population: A Systematic Review of Observational Studies.

ABSTRACT:

Objectives

This study aimed to provide an overview of prediction models of undiagnosed type 2 diabetes mellitus (U-T2DM) or the incident T2DM (I-T2DM) using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) checklist and the prediction model risk of the bias assessment tool (PROBAST).

Data sources

Both PUBMED and EMBASE databases were searched to guarantee adequate and efficient coverage.

Study selection

Articles published between December 2011 and October 2019 were considered.

Data extraction

For each article, information on model development requirements, discrimination measures, calibration, overall performance, clinical usefulness, overfitting, and risk of bias (ROB) was reported.

Results

The

SUBMITTER: Asgari S 

PROVIDER: S-EPMC8453657 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature