Research Paper Volume 16, Issue 4 pp 3420—3530
Insights into serum metabolic biomarkers for early detection of incident diabetic kidney disease in Chinese patients with type 2 diabetes by random forest
Figure 6. Evaluation of the prognostic performance of CDBs in follow-up cohort. (A) The distribution of AUC values using single and combinations of variate(s) in follow-up patients. With stratified random sampling and random forest, AUC of distinction between and progressed patients were calculated 100 times with single and multiple variables. Results of AUC average and standard deviation indicated that ADT_SAdo_UACR (AUC average: 0.9502; CI: 0.9062–0.9805) manifested the best prediction, followed with UACR_ADT_SAdo_sCr (AUC average: 0.9482; CI:0.9248-0.9805) and ADT_UACR (AUC average: 0.9443; CI: 0.9141–0.9727). (B) Comparisons of the three CDB levels and UACR between “progressed” and “unprogressed” groups in all the follow-up individuals. (C) In stage 2 patients, levels of three CDBs and UCAR were remarkably different in “progressed” vs. “unprogressed”, **p < 0.01 and ***p < 0.001, respectively. (D) Risk sores of three CDBs and UCAR in DKD progression by logistic regression analysis.