New-Onset Diabetes and Preexisting Diabetes Are Associated With Comparable Reduction in Long-Term Survival After Liver Transplant: A Machine Learning Approach.

Abstract

To identify key predictors and survival outcomes of new-onset diabetes after transplant (NODAT) in liver transplant (LT) recipients by using the Scientific Registry of Transplant Recipients. Data of all adult LT recipients between October 1, 1987, and March 31, 2016, were analyzed using various machine learning methods. These data were divided into training (70%) and validation (30%) data sets to robustly determine predictors of NODAT. The long-term survival of patients with NODAT relative to transplant recipients with preexisting diabetes and those without diabetes was assessed. Increasing age (odds ratio [OR], 1.01; 95% CI, 1.00-1.02; P≤.001), male sex (OR, 1.09; 95% CI, 1.05-1.13; P=.03), and obesity (OR, 1.13; 95% CI, 1.08-1.18; P<.001) were significantly associated with NODAT. Sirolimus as a primary immunosuppressant carried a 33% higher risk of NODAT than did tacrolimus (OR, 1.33; 95% CI, 1.22-1.45; P<.001) at 1 year after LT. Patients with NODAT had significantly decreased 10-year survival than did those without diabetes (63.0% vs 74.9%; P<.001), similar to survival in patients with diabetes before LT (58.9%). Using a machine learning approach, we found that older, male, and obese recipients are at especially higher risk of NODAT. Donor features do not affect risk. In addition, sirolimus-based immunosuppression is associated with a significantly higher risk of NODAT than other immunosuppressants. Most importantly, NODAT adversely affects long-term survival after LT in a manner similar to preexisting diabetes, indicating the need for more aggressive care and closer follow-up.