What question did this study set out to answer?

This research aims to develop a framework for analyzing longitudinal biomarkers alongside competing survival outcomes within nested case-control designs.

January 25, 2026BioinformaticsOpen Access

Joint Modeling of Longitudinal Biomarker and Survival Outcomes with the Presence of Competing Risk in the Nested Case-Control Studies with Application to the TEDDY Microbiome Dataset

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This research aims to develop a framework for analyzing longitudinal biomarkers alongside competing survival outcomes within nested case-control designs.
Developed the JM-NCC joint modeling framework for nested case-control studies.
Utilized a generalized linear mixed-effects model for non-normally distributed biomarkers.
Integrated a cause-specific hazard model for addressing competing risks.
Implemented two estimation methods: fJM-NCC and wJM-NCC, differing in the use of data sources.
JM-NCC framework effectively addresses challenges of non-normally distributed biomarkers and competing risks.
Simulation studies validate the robustness and efficiency of the proposed methods.
Application to the TEDDY microbiome dataset confirms the methodology's practical applicability.

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Implication

Research demonstrates a joint modeling framework for competing risks in nested case-control studies, enhancing biomarker analysis efficiency.

Cite This Study

Zhao et al. (2026) studied this question.

synapsesocial.com/papers/6975b2aefeba4585c2d6e20d https://doi.org/10.1093/bioinformatics/btag038

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Implication

Research demonstrates a joint modeling framework for competing risks in nested case-control studies, enhancing biomarker analysis efficiency.

Joint Modeling of Longitudinal Biomarker and Survival Outcomes with the Presence of Competing Risk in the Nested Case-Control Studies with Application to the TEDDY Microbiome Dataset

Key Points

Discussion

Implication

Cite This Study

Joint Modeling of Longitudinal Biomarker and Survival Outcomes with the Presence of Competing Risk in the Nested Case-Control Studies with Application to the TEDDY Microbiome Dataset

Key Points

Discussion

Implication

Cite This Study

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