Extension of Competing Risks Model and Its Application to the Analysis of Two Negatively Correlated Events in a Kidney Disease Study

When subjects may fail from several distinct causes but the occurrence of failure from one precludes the others, it is referred competing risks. While both event of interest and competing event types are unfavorable in many typical settings, there are some cases in which a favorable event and unfavorable event types are competing. We extend an application of competing risks model to a case in IgA nephropathy, in which two types of events were negatively created but not satisfy the condition of competing risks. Each event type does not necessarily preclude the other type of event and the exact order of time to events was often unclear due to irregular censoring intervals. We discuss interpretation of the result and generalization of our extension.

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Publication Details

Journal
Japanese Journal of Biometrics
Published
2024-11-21
DOI
https://doi.org/10.5691/jjb.45.269
Primary Topic
Statistical Methods and Inference
Type
article
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article

Extension of Competing Risks Model and Its Application to the Analysis of Two Negatively Correlated Events in a Kidney Disease Study

Keita Hirano, Masako Nishikawa, Kentaro Koike, Tetsuya Kawamura
Japanese Journal of Biometrics
Statistical Methods and Inference
article

Extension of Competing Risks Model and Its Application to the Analysis of Two Negatively Correlated Events in a Kidney Disease Study

Keita Hirano, Masako Nishikawa, Kentaro Koike, Tetsuya Kawamura
article en

Abstract

When subjects may fail from several distinct causes but the occurrence of failure from one precludes the others, it is referred competing risks. While both event of interest and competing event types are unfavorable in many typical settings, there are some cases in which a favorable event and unfavorable event types are competing. We extend an application of competing risks model to a case in IgA nephropathy, in which two types of events were negatively created but not satisfy the condition of competing risks. Each event type does not necessarily preclude the other type of event and the exact order of time to events was often unclear due to irregular censoring intervals. We discuss interpretation of the result and generalization of our extension.

Japanese Journal of BiometricsVol. 45(2)
Jikei University School of Medicine (JP), Ashikaga Red Cross Hospital (JP)
Openalex Percentile: Top 79%
Statistical Methods and Inference
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Extension of Competing Risks Model and Its Application to the Analysis of Two Negatively Correlated Events in a Kidney Disease Study — Keita Hirano, Masako Nishikawa, et al. · Japanese Journal of Biometrics (2024) | TGRS Research Map | TGRS