Development and Validation of Survival Scores and the Assessment of Spatial Trends in End-Stage Kidney Disease Outcomes

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Abstract

Background There is a need to create new mortality prediction models for end-stage kidney disease (ESKD). This study aimed to develop and validate survival scores for patients with ESKD using a mixture cure model (MCM) including assessing the spatial trends in ESKD outcomes. Methods This study used a United States Renal Data System (USRDS) dataset that contains 2,228,693 people with incident ESKD from 2000 through 2020, including those on dialysis or had at least one transplant. Many variables, including demographic and comorbid factors, were included within an MCM. This MCM was used to develop seven survival scores that would be summarized geographically. These survival scores are shown using maps of the United States and validated using the clinical measurements found within the USRDS dataset. Results Many spatial survival trends across the United States were observed that could be validated using the USRDS data and current literature. The Appalachian and Great Plains regions of the United States contained individuals who mostly had lower survivability. Conversely, individuals residing around Southern California, in the Southeast, and around the Texas-Mexico border had higher survivability. Most of these findings aligned with previous studies. Furthermore, many of the trends could be explained by both the coefficient estimates of the MCM and the characteristics of the individuals living in each region. For example, the MCM coefficient estimates found Hispanics to have a higher survivability than their non-Hispanic counterparts, which aligned with the predominantly Hispanic-populated area of the Texas-Mexico border. Lastly, serum creatine, a USRDS variable not used within the MCM, was found to have a moderately positive, linear relationship with the survival scores developed. Conclusions The survival scores developed and validated may benefit practitioners and policy-makers in more effectively addressing ESKD disparities.

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