Fig. 2

Kaplan-Meier curves of survival without conversion to AD produced by the prediction models. We calculated a prognostic index for each subject by applying the miR-eQTLs and clinical factors to our prognosis prediction model. a Based on the prognostic index, we divided the samples of the discovery cohort into high (red) and low (blue) risk groups. The optimal cutoff values were detected by using the minimum P value from the log-rank test and comparing the differences in survival without MCI-to-AD conversion as determined by Kaplan-Meier curves (optimal cutoff = 7.85, minimum P = 3.63 × 10⁻⁷). b The adjusted model was then evaluated on the validation cohort (log-rank test P = 3.44 × 10⁻⁴). c, d Prediction models constructed using only clinical factors (without miR-eQTLs) in the discovery cohort (c) and the validation cohort (d)