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Multivariate network meta-analysis of survival function parameters.

Shannon Cope1, Keith Chan1, Jeroen P Jansen2,3

  • 1Precision Health Economics & Outcomes Research, Vancouver, British Columbia, Canada.

Research Synthesis Methods
|March 4, 2020
PubMed
Summary

This study introduces a novel two-step network meta-analysis (NMA) for time-to-event data, improving upon existing methods by using parametric survival analysis for more transparent and efficient evidence synthesis.

Keywords:
evidence synthesismultivariate methodsnetwork meta-analysissurvivaltime-to-event

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Area of Science:

  • Biostatistics
  • Clinical Epidemiology
  • Health Services Research

Background:

  • Traditional network meta-analysis (NMA) for survival data often relies on the proportional hazards assumption.
  • Flexible NMA models exist but use approximate likelihoods for discrete hazards, limiting analysis of individual event times.
  • This study addresses limitations in flexible NMA for time-to-event outcomes.

Purpose of the Study:

  • To present an alternative, two-step implementation of flexible NMA models for time-to-event outcomes.
  • To overcome limitations of existing approximate likelihood methods in NMA for survival data.
  • To provide a more transparent and efficient model selection process for evidence synthesis.

Main Methods:

  • A two-step approach is proposed for NMA of time-to-event data.
  • Patient-level data from randomized controlled trials (RCTs) are fitted to various survival distributions (e.g., Weibull, log-logistic).
  • Scale and shape parameters from chosen distributions are incorporated into a multivariate NMA for time-varying relative treatment effects.

Main Results:

  • An illustrative analysis was conducted on RCTs for advanced melanoma overall survival.
  • Different survival distributions were compared using model fit criteria.
  • The log-logistic distribution identified treatment-specific shape and scale parameters relative to dacarbazine (DTIC), with corresponding hazard and survival curves presented.

Conclusions:

  • The novel two-step NMA approach offers a robust framework for evidence synthesis of time-to-event outcomes.
  • The method is grounded in standard parametric survival analysis practices.
  • It facilitates a more transparent and efficient model selection process in NMA.