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Novel and existing flexible survival methods for network meta-analyses
Bart Heeg1, Andrea Garcia1, Sophie van Beekhuizen1
1Cytel, 3012 NJ, Rotterdam, The Netherlands.
Journal of Comparative Effectiveness Research
|September 12, 2022
Summary
Flexible relative survival models were extended to network meta-analysis (NMA). Treatment-effect specification in these models impacts survival estimates and reduces uncertainty, improving health technology assessments.
Area of Science:
- Biostatistics
- Health Economics
- Pharmacometrics
Background:
- Flexible relative survival models are used for trial-based analyses.
- Network meta-analysis (NMA) synthesizes evidence from multiple treatment comparisons.
- Accounting for treatment-effect specifications is crucial in advanced statistical modeling.
Purpose of the Study:
- To generalize flexible relative survival models to the NMA setting.
- To investigate the impact of different treatment-effect specifications within NMAs.
- To enhance the reliability of extrapolations for health technology assessment (HTA).
Main Methods:
- Comparison of standard parametric models with flexible approaches (mixture, cure, piecewise, splines, fractional polynomial).
- Two-step optimization of treatment-effect parametrization by removing uncertain effects.
- Application to a network of previously treated advanced non-small-cell lung cancer data.
Main Results:
- Flexible model-based NMAs influence model fit and incremental mean survival, increasing uncertainty.
- Treatment-effect specification significantly impacts incremental survival, reduces uncertainty, and improves fit statistics.
- The chosen methods provide a robust framework for advanced NMA.
Conclusions:
- Extrapolation techniques from individual trials are now applicable to NMAs.
- This advancement ensures more plausible extrapolations for HTA submissions.
- The study provides a foundation for improved comparative effectiveness research.
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