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A technique for approximating transition rates from published survival analyses.

Markian A Pahuta1, Joel Werier2, Eugene K Wai2,3

  • 11Department of Orthopaedic Surgery, Henry Ford Health System, Detroit, MI USA.

Cost Effectiveness and Resource Allocation : C/E
|July 16, 2019
PubMed
Summary

This study introduces a novel method to estimate transition rates for health economic models using progression-free survival (PFS) and overall survival (OS) data. This approach enables more accurate quality-adjusted life-year (QALY) calculations when detailed multistate modeling data is unavailable.

Keywords:
CancerMultistate modelQuality adjusted life yearSurvival analysis

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Area of Science:

  • Health economics
  • Biostatistics
  • Survival analysis

Background:

  • Quality-adjusted life-years (QALYs) are crucial for evaluating treatment benefits and risks.
  • QALYs are commonly calculated using partitioned-survival or state-transition models.
  • State-transition models require transition rates, often derived from multistate modeling (MSM).
  • Estimating transition rates for state-transition models is challenging when only progression-free survival (PFS) and overall survival (OS) data are reported.

Purpose of the Study:

  • To develop and present a method for estimating approximate transition rates from published PFS and OS analyses.
  • To enable the use of flexible state-transition models for QALY calculations even with limited survival data.
  • To provide a practical approach for health economic evaluations.

Main Methods:

  • Developed a novel approximation method to estimate transition rates from PFS and OS data.
  • Distinguished between approximate transition rates and true transition rates (from full MSM).
  • Applied the method to a case study and evaluated its performance in a simulation study.

Main Results:

  • The approximation method provides reasonable estimates for transition rates, particularly for transitions out of health.
  • The method tends to underestimate true transition rates as the level of censoring in the data increases.
  • Accuracy is influenced by the extent of data censoring.

Conclusions:

  • The presented method offers a viable approach to derive essential transition rates for state-transition models when full MSM data is unavailable.
  • This facilitates more robust QALY calculations in health economic evaluations.
  • The method's performance is dependent on data characteristics, particularly censoring.