Estimating Short-Term and Long-Term Survival for Patients With Kidney Failure Using a Mixture Survival Model.

Rationale & Objective: Traditional survival models assume all patients receiving kidney replacement therapy (KRT) may be grouped into one population, overlooking long-term survivors, particularly successful transplant recipients, and may fail to appreciate the disparities in minority populations. On the other hand, a mixture survival model allows for the estimation of hazard and odds ratios of all-cause mortality in patients with kidney failure undergoing either dialysis or transplantation. Study Design: This retrospective cohort study analyzed survival outcomes using a proportional hazards mixture survival model, comparing results to a traditional Cox proportional hazards model with time-varying modality of treatment. Setting & Participants: Data from the United States Renal Data System included 2,228,693 patients initiating KRT between 2000 and 2020. Predictors: Key predictors included demographics, comorbid conditions, socioeconomic status, geographic location, and rurality. Outcomes: The primary outcome was all-cause mortality. The mixture survival model distinguishes between patients' characteristics associated with long-term survival (ie, primarily those with successful transplants) and short-term survival (ie, those at a greater risk of mortality over time, such as patients treated with dialysis). Analytical Approach: Both a Cox proportional hazards model and a proportional hazards mixture survival model were applied to all patients. Results: Findings from both models were largely consistent, but the mixture survival model revealed new insights into racial disparities. In the Cox model, American Indian individuals had an adjusted hazard ratio of 0.63 compared with White individuals (95% CI. 0.62-0.63) and 0.74 for Black individuals compared with White (95% CI, 0.74-0.74). The mixture model confirmed these trends but also showed that American Indian individuals were 1.59 times more likely to not have a long-term survival than White individuals (95% CI, 1.415-1.797) and Black individuals were 1.35 times more likely to not be in the long-term surviving group than White individuals (95% CI, 1.310-1.397). Additional disparities were observed by socioeconomic and geographic factors. Limitations: Data collected at the beginning of dialysis may not fully capture patients' health trajectories. Conclusions: The mixture survival model provides a more comprehensive understanding of mortality disparities for patients with kidney failure receiving KRT by distinguishing between short-term and long-term survivability. The findings highlight the need for targeted interventions to improve long-term outcomes for minority patients.