External validation of the risk prediction model for early diabetic kidney disease in Taiwan population: a retrospective cohort study

Abstract

ObjectivesThis study aims to independently and externally validate the Risk Prediction Model for Diabetic Kidney Disease (RPM-DKD) in patients with type 2 diabetes mellitus (T2DM).DesignThis is a retrospective cohort study.SettingOutpatient clinics at Lee’s United Clinics, Taiwan, China.ParticipantsA total of 2504 patients (average age 55.44 years, SD, 7.49 years) and 4455 patients (average age 57.88 years, SD, 8.80 years) were included for analysis in the DKD prediction and progression prediction cohorts, respectively.ExposureThe predicted risk for DKD and DKD progression for each patient were all calculated using the RPM-DKD.Primary and secondary outcome measuresThe primary outcome measure was overall incidence of DKD. Secondary outcomes included DKD progression. The discrimination, calibration and precision of the RPM-DKD score were assessed.ResultsThe DKD prediction cohort and progression prediction cohort consisted of patients with 2504 and 4455 T2DM, respectively. The RPM-DKD examined in this study showed moderately discriminative ability with area under the curve ranged from 0.636 to 0.681 for the occurrence of DKD and 0.620 to 0.654 for the progression of DKD. The Hosmer-Lemeshow χ2test indicted the RPM-DKD was not well calibrated for predicting the occurrence of DKD and overestimated the progression of DKD. The precision for predicting the occurrence and progression of DKD were 43.2% and 42.2%, respectively.ConclusionsOn external validation, the RPM-DKD cannot accurately predict the risk of DKD occurrence and progression in patients with T2DM.