Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment

Journal of Comparative Effectiveness Research, vol. 11, pp. 851–859

Abstract

Evidence generated from nonrandomized studies (NRS) is increasingly submitted to health technology assessment (HTA) agencies. Unmeasured confounding is a primary concern with this type of evidence, as it may result in biased treatment effect estimates, which has led to much criticism of NRS by HTA agencies. Quantitative bias analyses are a group of methods that have been developed in the epidemiological literature to quantify the impact of unmeasured confounding and adjust effect estimates from NRS. Key considerations for application in HTA proposed in this article reflect the need to balance methodological complexity with ease of application and interpretation, and the need to ensure the methods fit within the existing frameworks used to assess nonrandomized evidence by HTA bodies.

Authors 7

1. Thomas P. Leahy
   Affiliation as printed

   PHMR Ltd., Westport, F28 ET85, Ireland

2. Seamus Kent

   National Institute for Health and Care Excellence

   Affiliation as printed

   National Institute for Health & Care Excellence, Manchester, M1 4BT, UK

3. Cormac Sammon
   Affiliation as printed

   PHMR Ltd., Westport, F28 ET85, Ireland

4. Rolf H. H. Groenwold Aachen Department of Clinical Epidemiology Department of Biomedical Data Sciences

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Clinical Epidemiology & Department of Biomedical Data Sciences, Leiden University Medical Centre, Einthovenweg 20, Leiden, 2333, The Netherlands

5. Richard Grieve

   London School of Hygiene & Tropical Medicine

   Affiliation as printed

   Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK

6. Sreeram V Ramagopalan corresponding

   Roche (Switzerland)

   Affiliation as printed

   Global Access, F. Hoffmann-La Roche, Grenzacherstrasse 124 CH-4070, Basel, Switzerland

7. Manuel Gomes

   University College London

   Affiliation as printed

   Department of Applied Health Research, University College London, London, WC1E 6BT, UK