Prediction at first year of incident new-onset diabetes after kidney transplantation by risk prediction models

Abstract

Objective: Our aim was to analyze the performance of two scores developed for predicting diabetes in nontransplant populations for identifying kidney transplant recipients with a higher new-onset diabetes mellitus after transplantation (NODAT) risk beyond the first year after transplantation.

Research design and methods: We analyzed 191 kidney transplants, which had at least 1-year follow-up posttransplant. First-year posttransplant variables were collected to estimate the San Antonio Diabetes Prediction Model (SADPM) and Framingham Offspring Study-Diabetes Mellitus (FOS-DM) algorithm.

Results: Areas under the receiver operating characteristic curve of FOS-DM and SADPM scores to predict NODAT were 0.756 and 0.807 (P < 0.001), respectively. FOS-DM and SADPM scores over 75 percentile (hazard ratio 5.074 and 8.179, respectively, P < 0.001) were associated with NODAT.

Conclusions: Both scores can be used to identify kidney recipients at higher risk for NODAT beyond the first year. SADPM score detects some 25% of kidney transplant patients with an eightfold risk for NODAT.

Figure 1

Kaplan-Meier analysis of cumulative NODAT incidence comparing patients with a SADPM score over the 75 percentile (continuous line) with patients under the 75 percentile (dashed line).