Generating health technology assessment evidence for rare diseases

Facey, K., Granados, A., Guyatt, G., Kent, A., Shah, N., van der Wilt, G. J. and Wong-Rieger, D. (2014) Generating health technology assessment evidence for rare diseases. International Journal of Technology Assessment in Health Care, 30(4), pp. 416-422. (doi: 10.1017/S0266462314000464) (PMID:25407328)

Abstract

Objectives: Rare diseases are often heterogeneous in their progression and response to treatment, with only a small population for study. This provides challenges for evidence generation to support HTA, so novel research methods are required.

Methods: Discussion with an expert panel was augmented with references and case studies to explore robust approaches for HTA evidence generation for rare disease treatments.

Results: Traditional RCTs can be modified using sequential, three-stage or adaptive designs to gain more power from a small patient population or to focus trial design. However, such designs need to maintain important design aspects such as randomization and blinding and be analyzed to take account of the multiple analyses performed. N-of-1 trials use within-patient randomization to test repeat periods of treatment and control until a response is clear. Such trials could be particularly valuable for rare diseases and when prospectively planned across several patients and analyzed using Bayesian techniques, a population effect can be estimated that might be of value to HTA. When the optimal outcome is unclear in a rare disease, disease specific patient reported outcomes can elucidate impacts on patients’ functioning and wellbeing. Likewise, qualitative research can be used to elicit patients’ perspectives, with just a small number of patients.

Conclusions: International consensus is needed on ways to improve evidence collection and assessment of technologies for rare diseases, which recognize the value of novel study designs and analyses in a setting where the outcomes and effects of importance are yet to be agreed.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Facey, Dr Karen
• Authors: Facey, K., Granados, A., Guyatt, G., Kent, A., Shah, N., van der Wilt, G. J., and Wong-Rieger, D.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
• Journal Name: International Journal of Technology Assessment in Health Care
• Publisher: Cambridge University Press
• ISSN: 0266-4623
• ISSN (Online): 1471-6348
• Copyright Holders: Copyright © 2014 The Authors
• First Published: First published in International Journal of Technology Assessment in Health Care 30(4):416-422
• Publisher Policy: Reproduced under a Creative Commons License