To systematically evaluate the accuracy of prediction models in predicting the progression from prediabetes to type 2 diabetes mellitus (T2DM).
Approach:
Databases Searched: Cochrane Library, Embase, PubMed, and Web of Science were searched up to June 2, 2023.
Key Findings:
Sixteen studies included, covering 1,368,130 prediabetic individuals with 187,225 progressing to T2DM.
Pooled incidence of progression to T2DM was 42.3‰ (95% CI: 27.2‰–60.4‰).
Pooled C-indices for training and validation sets were 0.76 (0.71–0.80) and 0.84 (0.82–0.86), respectively.
Logistic regression and random forest models yielded C-indices of 0.81 and 0.86, respectively.
Interpretation:
Prediction models demonstrate promising accuracy for predicting progression from prediabetes to T2DM, though evidence is limited due to a lack of external validation.
Limitations:
Limited external validation of prediction models.
Variability in study designs and populations included.
Conclusion:
Future research should focus on strengthening model development, external validation, and reporting quality to enhance the robustness and clinical applicability of prediction models for prediabetes progression.
