Abstract: Objective: To systematically review risk prediction models for the progression from prediabetes to diabetes mellitus, and to provide references for clinical practice. Methods: Related literature was retrieved from Chinese and English databases, with the search period ranging from the establishment of each database to January 2025. Two researchers independently performed literature screening and data extraction. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was used to evaluate the risk of bias and applicability of the included studies. Meta-analysis of the area under the receiver operating characteristic curve (AUC) was conducted using MedCalc software. Results: A total of 23 articles comprising 41 risk prediction models were included. AUC value ranged from 0.643 to 0.925. Twenty-two studies were rated as having a high risk of bias, one had an unclear risk of bias, and six were rated as having low applicability. Meta-analysis showed a pooled AUC value of 0.768 (95%CI: 0.732-0.804). Frequently reported predictors included fasting blood glucose, body mass index, age, glycated hemoglobin, and triglycerides, etc. Conclusion: Risk prediction models for progression from prediabetes to diabetes mellitus generally demonstrate good predictive performance. However, most studies have a high risk of bias. Future research should focus on improving model development methods to create higher-quality risk prediction models.

Key words: prediabetes; diabetes mellitus; prediction model; risk score; systematic review