{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/network-meta-analysis-of-time-to-event","title":"Network Meta-Analysis of Time-to-Event Endpoints with Individual Participant Data using Restricted Mean Survival Time Regression","arxiv_id":"2310.13162","date":"2023-10-19","proceeding":null,"authors":["Kaiyuan Hua","Xiaofei Wang","Hwanhee Hong"],"abstract":"Restricted mean survival time (RMST) models have gained popularity when analyzing time-to-event outcomes because RMST models offer more straightforward interpretations of treatment effects with fewer assumptions than hazard ratios commonly estimated from Cox models. However, few network meta-analysis (NMA) methods have been developed using RMST. In this paper, we propose advanced RMST NMA models when individual participant data are available. Our models allow us to study treatment effect moderation and provide comprehensive understanding about comparative effectiveness of treatments and subgroup effects. An extensive simulation study and a real data example about treatments for patients with atrial fibrillation are presented.","url_abs":"https://arxiv.org/abs/2310.13162v1","url_pdf":"https://arxiv.org/pdf/2310.13162v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"network-meta-analysis-of-time-to-event","repo_url":"https://github.com/kimihua1995/nma_ipd_rmst","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}