Network Meta‐Analysis With Individual Participant‐Level Data of Time‐to‐Event Outcomes Using Cox Regression

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Main Authors: Kaiyuan Hua, Daniel Wojdyla, Anthony Carnicelli, Christopher Granger, Xiaofei Wang, Hwanhee Hong
Format: Artículo Open Access
Published: Wiley 2025
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author Kaiyuan Hua
Daniel Wojdyla
Anthony Carnicelli
Christopher Granger
Xiaofei Wang
Hwanhee Hong
author_facet Kaiyuan Hua
Daniel Wojdyla
Anthony Carnicelli
Christopher Granger
Xiaofei Wang
Hwanhee Hong
Kaiyuan Hua
Daniel Wojdyla
Anthony Carnicelli
Christopher Granger
Xiaofei Wang
Hwanhee Hong
collection Wiley Open Access
contents Network Meta‐Analysis With Individual Participant‐Level Data of Time‐to‐Event Outcomes Using Cox Regression Kaiyuan Hua Daniel Wojdyla Anthony Carnicelli Christopher Granger Xiaofei Wang Hwanhee Hong Statistics in Medicine ABSTRACT The accessibility of individual participant‐level data (IPD) enhances the evaluation of moderation effects of patient covariates. It facilitates the provision of accurate estimation of intervention effects and confidence intervals by incorporating covariate correlations across multiple clinical trials. With a time‐to‐event outcome, Cox regression can be applied for network meta‐analysis (NMA) using IPD. However, there lacks comprehensive reviews and comparisons of the specifications and assumptions of these Cox models and their impact on the interpretation of hazard ratios, effect moderation, and trial heterogeneity in IPD‐NMA. In this paper, we examine various Cox models for IPD‐NMA and compare different approaches to modeling trial, treatment, and covariate effects. We employ multiple graphical tools and statistical tests to assess proportional hazard assumptions and discuss their implications. Additionally, we explore the application of extended Cox models when the proportional hazard assumption is violated. Practical guidance on interpreting and reporting NMA results is provided. A simulation study is conducted to compare the performance of different models. We illustrate the methods to conduct IPD‐NMA through a real data example. 10.1002/sim.70027 http://onlinelibrary.wiley.com/termsAndConditions#vor
doi_str_mv 10.1002/sim.70027
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institution Wiley Open Access
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publishDate 2025
publisher Wiley
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spellingShingle Network Meta‐Analysis With Individual Participant‐Level Data of Time‐to‐Event Outcomes Using Cox Regression
Kaiyuan Hua
Daniel Wojdyla
Anthony Carnicelli
Christopher Granger
Xiaofei Wang
Hwanhee Hong
Statistics in Medicine
Network Meta‐Analysis With Individual Participant‐Level Data of Time‐to‐Event Outcomes Using Cox Regression Kaiyuan Hua Daniel Wojdyla Anthony Carnicelli Christopher Granger Xiaofei Wang Hwanhee Hong Statistics in Medicine ABSTRACT The accessibility of individual participant‐level data (IPD) enhances the evaluation of moderation effects of patient covariates. It facilitates the provision of accurate estimation of intervention effects and confidence intervals by incorporating covariate correlations across multiple clinical trials. With a time‐to‐event outcome, Cox regression can be applied for network meta‐analysis (NMA) using IPD. However, there lacks comprehensive reviews and comparisons of the specifications and assumptions of these Cox models and their impact on the interpretation of hazard ratios, effect moderation, and trial heterogeneity in IPD‐NMA. In this paper, we examine various Cox models for IPD‐NMA and compare different approaches to modeling trial, treatment, and covariate effects. We employ multiple graphical tools and statistical tests to assess proportional hazard assumptions and discuss their implications. Additionally, we explore the application of extended Cox models when the proportional hazard assumption is violated. Practical guidance on interpreting and reporting NMA results is provided. A simulation study is conducted to compare the performance of different models. We illustrate the methods to conduct IPD‐NMA through a real data example. 10.1002/sim.70027 http://onlinelibrary.wiley.com/termsAndConditions#vor
title Network Meta‐Analysis With Individual Participant‐Level Data of Time‐to‐Event Outcomes Using Cox Regression
topic Statistics in Medicine
url https://onlinelibrary.wiley.com/doi/10.1002/sim.70027