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Copula Dependent Censoring Models for Survival Prognosis: Application to Lactylation-Related Genes

Author

Listed:
  • Clarissa Auryn Kahardinata

    (Department of Information Management, Chang Gung University, Taoyuan 33302, Taiwan)

  • Gen-Yih Liao

    (Department of Information Management, Chang Gung University, Taoyuan 33302, Taiwan)

  • Takeshi Emura

    (Biostatistics Center, Kurume University, Kurume 8300011, Japan
    School of Informatics and Data Science, Hiroshima University, Higashi Hiroshima 7390046, Japan
    Research Center for Medical and Health Data Science, The Institute of Statistical Mathematics, Tokyo 1908562, Japan)

Abstract

Survival for cancer patients is predictable by gene expressions obtained from DNA microarrays for tumor samples. For analyzing survival data with gene expressions, traditional survival analysis methods have been employed. However, these methods rely on the independent censoring model. In real survival data, dependent censoring arises, which violates the fundamental assumption of independent censorship. In addition, how to handle dependent censoring has not been clearly demonstrated for scientists working on molecular genetics. In this article, we review copula-based methods to handle dependent censoring, including the copula-graphic estimator and significance test. We illustrate the copula-based method by the prognostic analysis of the lactylation-related genes from 327 breast cancer tumor tissues. To justify the correctness of the copula-based significance test, we examine the performance of the copula-based methods using a simulation study. The results of our analysis indicate that the copula-based analyses may reverse the conclusions derived from the traditional independent censoring model.

Suggested Citation

  • Clarissa Auryn Kahardinata & Gen-Yih Liao & Takeshi Emura, 2025. "Copula Dependent Censoring Models for Survival Prognosis: Application to Lactylation-Related Genes," Mathematics, MDPI, vol. 13(23), pages 1-17, November.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:23:p:3735-:d:1799686
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