Pragmatic Advice to Improve Assessment Schedule of Preference-Based Measures of Health to Estimate Utilities in Clinical Trials
Author(s)
Rossella Belleli, MA, MPH1, Sandro Gsteiger, PhD2, Aino Launonen, MSc2, Evan Davies, MSc2, C Simone Sutherland, BSc, MSc, PhD3, Katya Galactionova, MA, PhD2, Yasmina Marti-Gil, PhD4.
1Access Evidence Lead, Roche Products Ltd, Basel, Switzerland, 2F. Hoffmann-La Roche Ltd, Basel, Switzerland, 3F. Hoffmann - La Roche AG, BASEL, Switzerland, 4Roche, Basel, Switzerland.
1Access Evidence Lead, Roche Products Ltd, Basel, Switzerland, 2F. Hoffmann-La Roche Ltd, Basel, Switzerland, 3F. Hoffmann - La Roche AG, BASEL, Switzerland, 4Roche, Basel, Switzerland.
OBJECTIVES: Background: Preference-based measures (PBM) of health, such as EQ-5D, are collected in clinical trials as secondary/exploratory endpoints for estimating utility values that inform quality adjusted life year (QALY) values used in cost-effectiveness models (CEM). There is lack of guidance on how to administer PBMs in clinical trials to provide accurate and precise utility estimates, which are essential for rigorous cost-utility analyses, directly impacting decisions on treatment reimbursement. Objectives: To provide guidance on the assessment schedule for PBMs in clinical trials ensuring robust estimation of utilities for CEMs.
METHODS: We interviewed experts in clinical trial design and in analysis of utilities to seek advice on how to include PBMs for the purpose of utility estimation for the CEM. We also collected internal examples where suboptimal timing of PBM assessments potentially led to increased bias and/or uncertainty in utility estimates. We synthesized the information and developed pragmatic recommendations for frequency and timing of PBMs assessments to reduce bias and uncertainty in utility estimation.
RESULTS: Pragmatic recommendations:
CONCLUSIONS: Properly scheduled PBM assessments mitigate the risks of relying on inconsistent or outdated utility values from literature, enhancing the credibility of cost-utility analyses and facilitating smoother HTA deliberations. The guidance emphasizes the need for rigorous PBM data collection throughout clinical trials to ensure accurate and precise utility estimates for CEMs, crucial for informed reimbursement decisions.
METHODS: We interviewed experts in clinical trial design and in analysis of utilities to seek advice on how to include PBMs for the purpose of utility estimation for the CEM. We also collected internal examples where suboptimal timing of PBM assessments potentially led to increased bias and/or uncertainty in utility estimates. We synthesized the information and developed pragmatic recommendations for frequency and timing of PBMs assessments to reduce bias and uncertainty in utility estimation.
RESULTS: Pragmatic recommendations:
- Always administer PBMs at baseline, end of study, treatment discontinuation, any changes in treatment, and start of follow-up therapy.
- Ensure ≥3 PBM assessments within each disease stage considered in the health economic model to characterize Health Related Quality of Life (HRQoL) accurately and precisely, accounting for endpoint variability and patient dropouts.
- Balance the number of assessments to cover the expected entire duration of major disease stages, to improve the accuracy and precision in utility estimates.
CONCLUSIONS: Properly scheduled PBM assessments mitigate the risks of relying on inconsistent or outdated utility values from literature, enhancing the credibility of cost-utility analyses and facilitating smoother HTA deliberations. The guidance emphasizes the need for rigorous PBM data collection throughout clinical trials to ensure accurate and precise utility estimates for CEMs, crucial for informed reimbursement decisions.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
SA76
Topic
Health Technology Assessment, Methodological & Statistical Research, Study Approaches
Disease
No Additional Disease & Conditions/Specialized Treatment Areas