1
|
Youn S, Wong SA, Chrystoja C, Tomlinson G, Wijeysundera HC, Bell CM, Gagliardi AR, Baxter NN, Takata J, Sandhu L, Urbach DR. Bias estimation in study design: a meta-epidemiological analysis of transcatheter versus surgical aortic valve replacement. BMC Surg 2021; 21:285. [PMID: 34098926 PMCID: PMC8186071 DOI: 10.1186/s12893-021-01278-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 05/27/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Paucity of RCTs of non-drug technologies lead to widespread dependence on non-randomized studies. Relationship between nonrandomized study design attributes and biased estimates of treatment effects are poorly understood. Our purpose was to estimate the bias associated with specific nonrandomized study attributes among studies comparing transcatheter aortic valve implantation with surgical aortic valve replacement for the treatment of severe aortic stenosis. RESULTS We included 6 RCTs and 87 nonrandomized studies. Surgical risk scores were similar for comparison groups in RCTs, but were higher for patients having transcatheter aortic valve implantation in nonrandomized studies. Nonrandomized studies underestimated the benefit of transcatheter aortic valve implantation compared with RCTs. For example, nonrandomized studies without adjustment estimated a higher risk of postoperative mortality for transcatheter aortic valve implantation compared with surgical aortic valve replacement (OR 1.43 [95% CI 1.26 to 1.62]) than high quality RCTs (OR 0.78 [95% CI 0.54 to 1.11). Nonrandomized studies using propensity score matching (OR 1.13 [95% CI 0.85 to 1.52]) and regression modelling (OR 0.68 [95% CI 0.57 to 0.81]) to adjust results estimated treatment effects closer to high quality RCTs. Nonrandomized studies describing losses to follow-up estimated treatment effects that were significantly closer to high quality RCT than nonrandomized studies that did not. CONCLUSION Studies with different attributes produce different estimates of treatment effects. Study design attributes related to the completeness of follow-up may explain biased treatment estimates in nonrandomized studies, as in the case of aortic valve replacement where high-risk patients were preferentially selected for the newer (transcatheter) procedure.
Collapse
Affiliation(s)
- Saerom Youn
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
- Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Shannon Avery Wong
- College of Medicine and Dentistry, James Cook University, Parkville, QLD, Australia
| | - Caitlin Chrystoja
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
| | - George Tomlinson
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Harindra C Wijeysundera
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
| | - Chaim M Bell
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
| | - Anna R Gagliardi
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, Canada
| | - Nancy N Baxter
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Surgery, University of Toronto, Toronto, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
- School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - Julie Takata
- Women's College Hospital Research Institute (WCRI), Toronto, ON, Canada
| | - Lakhbir Sandhu
- Department of Surgery, University of Toronto, Toronto, Canada
| | - David Robert Urbach
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada.
- Department of Surgery, University of Toronto, Toronto, Canada.
- Women's College Hospital Research Institute (WCRI), Toronto, ON, Canada.
- Department of Surgery, Women's College Hospital, 76 Grenville St, Room 8332, M5S 1B2, Toronto, ON, Canada.
- Women's College Hospital Institute for Health System Solutions and Virtual Care (WIHV), Toronto, ON, Canada.
| |
Collapse
|