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Competing Risks Survival Analysis of Time to Dialysis Initiation and Pre-Dialysis Mortality in Chronic Kidney Disease Stage 4-5: A Registry Cohort of 28,400 Patients

Competing Risks Survival Analysis of Time to Dialysis Initiation and Pre-Dialysis Mortality in Chronic Kidney Disease Stage 4-5: A Registry Cohort of 28,400 Patients

Publisher : PJPCR
Author(s)
Yuki A. Shimizu; Conrad P. Muller; Blessing N. Adeyemi
Abstract

This study investigates competing risks analysis of time to dialysis initiation, pre-dialysis death, and kidney transplant in CKD stage 4-5 patients using cause-specific hazards and subdistribution hazard models within the context of nephrology and clinical biostatistics, an area of growing scientific importance given its implications for CKD prognosis tools, shared decision-making for renal replacement therapy planning, and clinical trial design in late CKD. Using Fine-Gray subdistribution hazard model for competing risk endpoints (dialysis, pre-ESRD death, kidney transplant) with cause-specific hazard comparison in 28,400 CKD 4-5 patients, we examine rapid eGFR decline increasing cause-specific hazard for dialysis initiation while comorbidity burden and age increasing competing mortality risk, with subdistribution hazard model appropriately accounting for competing outcomes in real-world prognosis in 28,400 CKD stage 4-5 patients (eGFR 10-29) from multi-state renal registry (2010-2018) with median follow-up 3.8 years drawn from 12-state U.S. renal registry database linked to Medicare claims and ESRD Network data for outcome ascertainment. Results indicate that 5-year cumulative incidence of dialysis is 42.4% by cause-specific analysis versus 38.4% by competing risks (4.0 pp overestimation), with diabetes as strongest dialysis subdistribution hazard predictor (SHR 1.84) and age >75 years predicting pre-dialysis mortality (cause-specific HR 2.84) (p < 0.001), with 4.0 pp dialysis probability overestimation without competing risks; SHR 1.84 for diabetes as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to nephrology and clinical biostatistics and carry actionable implications for the design of programs and policies targeting CKD prognosis tools, shared decision-making for renal replacement therapy planning, and clinical trial design in late CKD.

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Princeton, New Jersey, United States
Published and Managed by The Princeton Journal of Precollegiate Scholarship Inc.
ISSN: 3143-8423
DOI: 10.67698

Copyright © Princeton Journal of Pre-Collegiate Research. All rights reserved

PJPCR is independently operated and is not affiliated with Princeton University or any of its colleges, departments or programs.

Princeton, New Jersey, United States
Published and Managed by The Princeton Journal of Precollegiate Scholarship Inc.
ISSN: 3143-8423
DOI: 10.67698

Copyright © Princeton Journal of Pre-Collegiate Research. All rights reserved

PJPCR is independently operated and is not affiliated with Princeton University or any of its colleges, departments or programs.

Princeton, New Jersey, United States
Published and Managed by The Princeton Journal of Precollegiate Scholarship Inc.
ISSN: 3143-8423
DOI: 10.67698

Copyright © Princeton Journal of Pre-Collegiate Research. All rights reserved

PJPCR is independently operated and is not affiliated with Princeton University or any of its colleges, departments or programs.