Performance of clinical prediction models for identifying postmenopausal osteoporosis: a systematic review and meta-analysis.

ABSTRACT:

Purpose

Early clinical recognition of postmenopausal osteoporosis (PMOP) can be challenging. With the advancement of machine learning, several prediction models for PMOP have been developed. This study assessed their performance by carrying out a systematic review and meta-analysis.

Methods

The PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), WanFang database and China Science and Technology Journal Database (VIP) were systematically searched. Studies with a sample size of at least 100 and involving postmenopausal women were included Included models were descriptively summarized, and meta-analyses were conducted to derive discrimination estimates. Homogeneous results from different studies were pooled using MedCalc software.

SUBMITTER: Huang X 

PROVIDER: S-EPMC12857129 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature