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Scenario drafting to anticipate future developments in technology assessment.

Valesca P Retèl1, Manuela A Joore, Sabine C Linn

  • 1Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital (NKI-AVL), Department of Psychosocial Research and Epidemiology, Plesmanlaan 121, Amsterdam 1066 CX, The Netherlands.

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Summary

This study developed a framework using scenario drafting to assess the cost-effectiveness of new health technologies like the 70-gene signature for breast cancer. The 70-gene signature became cost-effective by 2010, with patient uptake significantly influencing outcomes.

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Area of Science:

  • Health Technology Assessment (HTA)
  • Genomic Medicine
  • Decision Analysis

Background:

  • Health Technology Assessment (HTA) requires early cost-effectiveness data, but development stages involve high uncertainty due to limited evidence and evolving paths.
  • A novel multi-parameter framework was developed to assess dynamic aspects of developing technologies using scenario drafting.
  • The framework's value was explored using the 70-gene signature for breast cancer, a gene expression profile for chemotherapy patient selection.

Purpose of the Study:

  • To develop and evaluate a multi-parameter framework for assessing the dynamic cost-effectiveness of technologies in early development.
  • To determine the cost-effectiveness of the 70-gene signature for breast cancer over time under various diffusion scenarios.
  • To incorporate process uncertainty into health technology assessment through scenario drafting.

Main Methods:

  • Developed a multi-parameter framework incorporating scenario drafting to model future diffusion patterns of new technologies.
  • Drafted ten scenarios with European experts regarding the introduction of the 70-gene signature.
  • Quantitatively integrated three key diffusion drivers (non-compliance, technical failure, uptake) into a decision-analytical model for the most likely scenarios.

Main Results:

  • In 2005, the 70-gene signature's Incremental Cost-Effectiveness Ratio (ICER) was €1.9 million/QALY, exceeding cost-effectiveness thresholds.
  • By 2010 and 2020, ICERs ranged from €1.9 million to €26,145 and €11,123/QALY respectively, depending on the scenario.
  • The 70-gene signature was projected to be cost-effective from 2010 onwards, with patient uptake demonstrating the most significant influence on cost-effectiveness.

Conclusions:

  • Incorporating process uncertainty via scenario drafting into decision models can reveal potential developments and a range of cost-effectiveness outcomes for new technologies.
  • Scenario analysis provides crucial information on the timeline for achieving cost-effectiveness, offering a more realistic outlook for policymakers, opinion leaders, and manufacturers.
  • The study highlights the importance of considering dynamic diffusion patterns and uncertainties in HTA for technologies in early development.