How well can we assess the validity of non-randomised studies of medications? A systematic review of assessment tools.

Autor:	D'Andrea E; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA., Vinals L; HEOR Department, Cytel Inc, Toronto, Quebec, Canada., Patorno E; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA., Franklin JM; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA., Bennett D; Pharmacoepidemiology, Takeda Pharmaceutical, Cambridge, Massachusetts, USA.; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Largent JA; Real-World Solutions, IQVIA, California, Los Angeles, USA., Moga DC; Department of Pharmacy Practice and Science, College of Pharmacy, University of Kentucky, Lexington, KY, USA., Yuan H; Canadian Agency for Drugs and Technologies in Health (CADTH), Ottawa, Ontario, Canada., Wen X; Department of Pharmacy Practice, University of Rhode Island, Kingston, RI, USA., Zullo AR; Department of Health Services, Policy, and Practice, Brown University, Providence, Rhode Island, USA.; Center of Innovation in Long-term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA., Debray TPA; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, Utrecht, The Netherlands T.Debray@umcutrecht.nl.; Smart Data Analysis and Statistics, Utrecht, The Netherlands., Sarri G; Real World Evidence Sciences, Visible Analytics Ltd, Oxford, UK.
Jazyk:	angličtina
Zdroj:	BMJ open [BMJ Open] 2021 Mar 24; Vol. 11 (3), pp. e043961. Date of Electronic Publication: 2021 Mar 24.
DOI:	10.1136/bmjopen-2020-043961
Abstrakt:	Objective: To determine whether assessment tools for non-randomised studies (NRS) address critical elements that influence the validity of NRS findings for comparative safety and effectiveness of medications. Design: Systematic review and Delphi survey. Data Sources: We searched PubMed, Embase, Google, bibliographies of reviews and websites of influential organisations from inception to November 2019. In parallel, we conducted a Delphi survey among the International Society for Pharmacoepidemiology Comparative Effectiveness Research Special Interest Group to identify key methodological challenges for NRS of medications. We created a framework consisting of the reported methodological challenges to evaluate the selected NRS tools. Study Selection: Checklists or scales assessing NRS. Data Extraction: Two reviewers extracted general information and content data related to the prespecified framework. Results: Of 44 tools reviewed, 48% (n=21) assess multiple NRS designs, while other tools specifically addressed case-control (n=12, 27%) or cohort studies (n=11, 25%) only. Response rate to the Delphi survey was 73% (35 out of 48 content experts), and a consensus was reached in only two rounds. Most tools evaluated methods for selecting study participants (n=43, 98%), although only one addressed selection bias due to depletion of susceptibles (2%). Many tools addressed the measurement of exposure and outcome (n=40, 91%), and measurement and control for confounders (n=40, 91%). Most tools have at least one item/question on design-specific sources of bias (n=40, 91%), but only a few investigate reverse causation (n=8, 18%), detection bias (n=4, 9%), time-related bias (n=3, 7%), lack of new-user design (n=2, 5%) or active comparator design (n=0). Few tools address the appropriateness of statistical analyses (n=15, 34%), methods for assessing internal (n=15, 34%) or external validity (n=11, 25%) and statistical uncertainty in the findings (n=21, 48%). None of the reviewed tools investigated all the methodological domains and subdomains. Conclusions: The acknowledgement of major design-specific sources of bias (eg, lack of new-user design, lack of active comparator design, time-related bias, depletion of susceptibles, reverse causation) and statistical assessment of internal and external validity is currently not sufficiently addressed in most of the existing tools. These critical elements should be integrated to systematically investigate the validity of NRS on comparative safety and effectiveness of medications. SYSTEMATIC REVIEW PROTOCOL AND REGISTRATION: https://osf.io/es65q. Competing Interests: Competing interests: DB is an employee of Takeda. ARZ has received salary support from Sanofi Pasteur through a grant to Brown University unrelated to the current work. TD provides consulting services via Smart Data Analysis and Statistics. GS discloses being employed by Visible Analytics Ltd. (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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