Leahy, Thomas P;
Kent, Seamus;
Sammon, Cormac;
Groenwold, Rolf HH;
Grieve, Richard;
Ramagopalan, Sreeram;
Gomes, Manuel;
(2022)
Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment.
Journal of Comparative Effectiveness Research
10.2217/cer-2022-0029.
(In press).
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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.
| Type: | Article |
|---|---|
| Title: | Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.2217/cer-2022-0029 |
| Publisher version: | https://doi.org/10.2217/cer-2022-0029 |
| Language: | English |
| Additional information: | This work is licensed under the Creative Commons Attribution 4.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Health Care Sciences & Services, HTA, nonrandomized, quantitative bias analysis, unmeasured confounding, BAYESIAN SENSITIVITY-ANALYSIS, EXTERNAL ADJUSTMENT, IMPACT, FORMULAS, OUTCOMES, MODEL |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Applied Health Research UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10150914 |
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