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Syst Rev. 2015 Nov 5;4:147. doi: 10.1186/s13643-015-0133-0.

Network meta-analysis incorporating randomized controlled trials and non-randomized comparative cohort studies for assessing the safety and effectiveness of medical treatments: challenges and opportunities.

Author information

1
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, 451 Smyth Road, Suite RGN 3105, Ottawa, ON, K1H 8 M5, Canada. ccame056@uottawa.ca.
2
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Avenue, 6th Floor, Boston, MA, 02215, USA. ccame056@uottawa.ca.
3
Evidence Synthesis Group, Cornerstone Research Group Inc., 3228 South Service Road, Burlington, ON, L7N 3H8, Canada. ccame056@uottawa.ca.
4
Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA. bruce.fireman@kp.org.
5
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, 451 Smyth Road, Suite RGN 3105, Ottawa, ON, K1H 8 M5, Canada. bhutton@ohri.ca.
6
Ottawa Hospital Research Institute, Center for Practice Changing Research Building, Ottawa Hospital-General Campus, PO Box 201B, Ottawa, ON, K1H 8 L6, Canada. bhutton@ohri.ca.
7
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, 451 Smyth Road, Suite RGN 3105, Ottawa, ON, K1H 8 M5, Canada. Tammyc@cadth.ca.
8
Canadian Agency for Drugs and Technologies in Health, 865 Carling Ave., Suite 600, Ottawa, ON, K1S 5S8, Canada. Tammyc@cadth.ca.
9
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, 451 Smyth Road, Suite RGN 3105, Ottawa, ON, K1H 8 M5, Canada. dcoyle@uottawa.ca.
10
School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, 451 Smyth Road, Suite RGN 3105, Ottawa, ON, K1H 8 M5, Canada. gawells@ottawaheart.ca.
11
Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada. colin.dormuth@ti.ubc.ca.
12
Department of Epidemiology and Biostatistics, McGill University, 4060 Ste Catherine W #300, Montréal, Québec, H3Z 2Z3, Canada. robert.platt@mcgill.ca.
13
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Avenue, 6th Floor, Boston, MA, 02215, USA. darren_toh@harvardpilgrim.org.

Abstract

Network meta-analysis is increasingly used to allow comparison of multiple treatment alternatives simultaneously, some of which may not have been compared directly in primary research studies. The majority of network meta-analyses published to date have incorporated data from randomized controlled trials (RCTs) only; however, inclusion of non-randomized studies may sometimes be considered. Non-randomized studies can complement RCTs or address some of their limitations, such as short follow-up time, small sample size, highly selected population, high cost, and ethical restrictions. In this paper, we discuss the challenges and opportunities of incorporating both RCTs and non-randomized comparative cohort studies into network meta-analysis for assessing the safety and effectiveness of medical treatments. Non-randomized studies with inadequate control of biases such as confounding may threaten the validity of the entire network meta-analysis. Therefore, identification and inclusion of non-randomized studies must balance their strengths with their limitations. Inclusion of both RCTs and non-randomized studies in network meta-analysis will likely increase in the future due to the growing need to assess multiple treatments simultaneously, the availability of higher quality non-randomized data and more valid methods, and the increased use of progressive licensing and product listing agreements requiring collection of data over the life cycle of medical products. Inappropriate inclusion of non-randomized studies could perpetuate the biases that are unknown, unmeasured, or uncontrolled. However, thoughtful integration of randomized and non-randomized studies may offer opportunities to provide more timely, comprehensive, and generalizable evidence about the comparative safety and effectiveness of medical treatments.

PMID:
26537988
PMCID:
PMC4634799
DOI:
10.1186/s13643-015-0133-0
[Indexed for MEDLINE]
Free PMC Article

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