ArticleResearch synthesis methods2017
Bayesian one-step IPD network meta-analysis of time-to-event data using Royston-Parmar models.
Article in Research synthesis methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A network meta-analysis of immunotherapy-based treatments for advanced nonsquamous non-small cell lung cancer.Journal of comparative effectiveness research · 2023Pooled it
- A systematic review and network meta-analysis of first-line immune checkpoint inhibitor combination therapies in patients with advanced non-squamous non-small cell lung cancer.Frontiers in immunology · 2022Pooled it
- Individual participant data meta-analysis of intervention studies with time-to-event outcomes: A review of the methodology and an applied example.Research synthesis methods · 2020Pooled it
- Network Meta-Analysis of Survival Outcomes With Non-Proportional Hazards Using Flexible M-Splines.Statistics in medicine · 2026Article
- Evidence Synthesis via Indirect Treatment Comparisons in the European Framework of Joint Clinical Assessment.Epidemiologia (Basel, Switzerland) · 2026Review
- NMAsurv: An R Shiny application for network meta-analysis based on survival data.Research synthesis methods · 2025Review
- One-step parametric network meta-analysis models using the exact likelihood that allow for time-varying treatment effects.Research synthesis methods · 2025Article
- Network Meta-Analysis With Individual Participant-Level Data of Time-to-Event Outcomes Using Cox Regression.Statistics in medicine · 2025Article
- Balancing Efficacy and Tolerability of First-Line Systemic Therapies for Advanced Hepatocellular Carcinoma: A Network Meta-Analysis.Liver cancer · 2024Article
- Using individual participant data to improve network meta-analysis projects.BMJ evidence-based medicine · 2023Article
- Bayesian hierarchical model-based network meta-analysis to overcome survival extrapolation challenges caused by data immaturity.Journal of comparative effectiveness research · 2023Article
- Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network.Statistical methods in medical research · 2022Article
- Individual Patient Data Meta-Analysis and Network Meta-Analysis.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Antihypertensive treatment and risk of cancer: an individual participant data meta-analysis.The Lancet. Oncology · 2021Article
- A review of the quantitative effectiveness evidence synthesis methods used in public health intervention guidelines.BMC public health · 2021Review
- A frequentist one-step model for a simple network meta-analysis of time-to-event data in presence of an effect modifier.PloS one · 2021Article
- Uptake of methodological advances for synthesis of continuous and time-to-event outcomes would maximize use of the evidence base.Journal of clinical epidemiology · 2020Review
- Healthcare Costs of Treating Privately Insured Patients with Acute Myeloid Leukemia in the United States from 2004 to 2014: A Generalized Additive Modeling Approach.PharmacoEconomics · 2020Article
- Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?Statistics in medicine · 2019Article
- Individual patient data network meta-analysis using either restricted mean survival time difference or hazard ratios: is there a difference? A case study on locoregionally advanced nasopharyngeal carcinomas.Systematic reviews · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Network meta-analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time-to-event outcomes. Such outcomes are usually analysed using Cox proportional hazard (PH) models. However, in oncology with longer follow-up time, and time-dependent effects of targeted treatments, this may no longer be appropriate. Network meta-analysis conducted in the Bayesian setting has been increasing in popularity. However, fitting the Cox model is computationally intensive, making it unsuitable for many datasets. Royston-Parmar models are a flexible alternative that can accommodate time-dependent effects. Motivated by individual participant data (IPD) from 37 cervical cancer trials (5922 women) comparing surgery, radiotherapy, and chemotherapy, this paper develops an IPD Royston-Parmar Bayesian NMA model for overall survival. We give WinBUGS code for the model. We show how including a treatment-ln(time) interaction can be used to conduct a global test for PH, illustrate how to test for consistency of direct and indirect evidence, and assess within-design heterogeneity. Our approach provides a computationally practical, flexible Bayesian approach to NMA of IPD survival data, which readily extends to include additional complexities, such as non-PH, increasingly found in oncology trials.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.