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

Nathan Meyer1, Maxwell Donelan1, Hossein Moradi Rekabdarkolaee2

  • 1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD.

Kidney Medicine
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Summary

A new mixture survival model reveals significant racial disparities in long-term survival for patients undergoing kidney replacement therapy (KRT). This advanced model highlights the need for targeted interventions to improve outcomes for minority populations facing kidney failure.

Keywords:
Kidney failureUSRDSfinite mixture modelingsurvival analysistime-to-event data

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Area of Science:

  • Nephrology and Public Health
  • Biostatistics and Survival Analysis

Background:

  • Traditional survival models for kidney replacement therapy (KRT) may oversimplify patient populations, potentially masking disparities among minority groups and overlooking long-term survivors, especially transplant recipients.
  • A mixture survival model offers a more nuanced approach to estimating mortality risks in patients with kidney failure, differentiating between short-term and long-term survival probabilities.

Purpose of the Study:

  • To compare the effectiveness of a proportional hazards mixture survival model against a traditional Cox proportional hazards model in analyzing all-cause mortality in KRT patients.
  • To identify and quantify racial, socioeconomic, and geographic disparities in survival outcomes among a large cohort of patients with kidney failure.

Main Methods:

  • A retrospective cohort study utilizing data from the United States Renal Data System (USRDS) for 2,228,693 patients initiating KRT between 2000 and 2020.
  • Application of both a traditional Cox proportional hazards model and a proportional hazards mixture survival model to assess all-cause mortality, considering demographics, comorbidities, socioeconomic status, and geographic factors.

Main Results:

  • While both models showed consistent overall trends, the mixture survival model provided deeper insights into racial disparities.
  • The mixture model indicated that American Indian and Black individuals were significantly more likely than White individuals to not be in the long-term surviving group.
  • Additional survival disparities were identified based on socioeconomic status and geographic location, underscoring the complexity of mortality risk in KRT patients.

Conclusions:

  • The mixture survival model offers a more comprehensive understanding of mortality in kidney failure patients undergoing KRT by distinguishing between short-term and long-term survival.
  • Findings underscore the existence of significant disparities, particularly racial, in long-term survival, necessitating targeted interventions to improve outcomes for underrepresented minority groups.