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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Estimating hazard ratios from published Kaplan-Meier survival curves: A methods validation study.

Ronak Saluja1, Sierra Cheng1, Keemo Althea Delos Santos1

  • 1Division of Medical Oncology and Hematology, Sunnybrook Odette Cancer Centre, Toronto, Ontario, Canada.

Research Synthesis Methods
|May 29, 2019
PubMed
Summary

Researchers can reliably reconstruct hazard ratios (HRs) from Kaplan-Meier (KM) curves using the Guyot method. This method demonstrated superior accuracy and precision for aggregate data meta-analyses when reported HRs are unavailable.

Keywords:
Kaplan-Meier survival curveshazard ratiosmeta-analysisvalidation study

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Area of Science:

  • Biostatistics
  • Medical Informatics
  • Clinical Trials

Background:

  • Meta-analyses often require hazard ratios (HRs) from published Kaplan-Meier (KM) curves.
  • Several statistical methods exist to estimate HRs from KM curves, but their reliability is not well-established.

Purpose of the Study:

  • To evaluate the accuracy and precision of four common methods (Guyot, Williamson, Parmar, Hoyle and Henley) for reconstructing HRs from KM curves.
  • To compare the performance of these methods across different KM curve structures.

Main Methods:

  • Reconstruction of HRs from KM curves of pivotal oncology randomized controlled trials (RCTs) using four distinct statistical methods.
  • Comparison of reconstructed HRs against reported HRs (gold standard) using Bland-Altman plots and statistical summaries.
  • Assessment of interrater reliability using intraclass correlation coefficient (ICC).

Main Results:

  • The Guyot method exhibited the highest accuracy, with the lowest mean error (0.0094) and smallest bias.
  • All four methods demonstrated excellent interrater reliability.
  • The Guyot method consistently outperformed other methods in both primary and secondary analyses, including sensitivity analyses.

Conclusions:

  • The Guyot method is recommended for reconstructing HRs from KM curves in aggregate data meta-analyses when reported HRs are not available.
  • This method offers a reliable and accurate approach for data extraction from published survival curves.