Incorporating Social Determinants of Health in the Prediction of Chronic Kidney Disease Progression in a National Cohort of US Veterans

Background As new therapies such as Sodium-Glucose Cotransporter-2 (SGLT2) inhibitors become available that may be effective earlier in the course of chronic kidney disease (CKD), newer risk prediction tools are required earlier in the course of CKD, and also to evaluate whether social determinants of health play a role in addition to individual-level risk factors. Methods We examined CKD progression among US Veterans who had known CKD in the VA health system using data from 2006-2016. CKD progression was defined based on two separate outcomes: 1) rapid CKD progression based on the eGFR slope < −3.7 mL/min/1.73m2 as a binary outcome, and 2) time-to-end stage kidney disease (ESKD) as a survival outcome. Veterans whose eGFR values were declining more steeply than −3.7 per year were considered “fast progressors,” representing 9.8% of the overall cohort. ESKD was identified by linking the VA data with US Renal Data System (USRDS) data, a national ESKD registry. After randomly dividing the dataset into a training, tuning, and testing set, tree ensemble models were trained and evaluated. Results We identified 1,550,526 patients meeting inclusion criteria, of which 930,615 patients were assigned to a training cohort, 309,831 to a tuning cohort, and 310,044 to a testing cohort. Tree ensemble models predicted fast progression with a C-statistic of 0.79 and time to ESKD with a C-statistic of 0.90. Baseline eGFR was the most important variable in predicting both outcomes, though social determinants constituted more of the important variables in rapid progression Conclusions CKD progression can be accurately predicted, though the predictors differ for fast progression and ESKD onset. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by the Department of Veterans Affairs, Office of Connected Health; VHA Department of Innovation Contract # 36C10B18C2768. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: University of Michigan Institutional Review Board I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript