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Aggregate data meta-analysis with time-to-event outcomes.

Paula R Williamson1, Catrin Tudur Smith, Jane L Hutton

  • 1Department of Mathematical Sciences, University of Liverpool, UK. prw@liv.ac.uk

Statistics in Medicine
|October 31, 2002
PubMed
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This study presents improved methods for estimating hazard ratios from survival data in meta-analyses. These techniques help assess time-varying treatment effects and heterogeneity in clinical trials.

Area of Science:

  • Biostatistics
  • Clinical Epidemiology
  • Medical Research Methodology

Background:

  • Meta-analyses of randomized controlled trials (RCTs) with time-to-event outcomes often require aggregate data.
  • Inconsistent reporting of survival analyses in journals necessitates flexible methods for extracting log(hazard ratio) estimates.
  • Existing methods for estimating log(hazard ratio) from survival curves may not be universally applicable.

Purpose of the Study:

  • To describe improved methods for estimating the log(hazard ratio) from survival curves, extending to life-tables.
  • To develop and compare tests for assessing whether the hazard ratio changes over time.
  • To address heterogeneity in meta-analyses where treatment effects may vary over time and follow-up durations differ.

Main Methods:

Related Experiment Videos

  • Improved methods for estimating log(hazard ratio) from survival curves.
  • Extension of these methods to life-table data.
  • Development and comparative assessment of statistical tests for time-varying hazard ratios.

    • Main Results:

    • The proposed methods enhance the estimation of log(hazard ratio) from survival data.
    • Tests for time-dependent hazard ratios were proposed and compared.
    • Illustrative examples using a cohort study on cerebral palsy and a systematic review of anti-epileptic drugs were provided.

    Conclusions:

    • The developed methods offer more robust approaches for meta-analysis of time-to-event data.
    • The proposed tests aid in identifying and evaluating time-varying treatment effects.
    • Accurate estimation and assessment of hazard ratios are crucial for synthesizing evidence from clinical trials.