| Title |
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
|
|---|---|
| Published in |
Systematic Reviews, November 2015
|
| DOI | 10.1186/s13643-015-0133-0 |
| Pubmed ID | |
| Authors |
Chris Cameron, Bruce Fireman, Brian Hutton, Tammy Clifford, Doug Coyle, George Wells, Colin R. Dormuth, Robert Platt, Sengwee Toh |
| 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. |
X Demographics
The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 9 | 45% |
| United States | 2 | 10% |
| Australia | 1 | 5% |
| South Africa | 1 | 5% |
| Sweden | 1 | 5% |
| Brazil | 1 | 5% |
| Egypt | 1 | 5% |
| Canada | 1 | 5% |
| Unknown | 3 | 15% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 50% |
| Scientists | 8 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
| Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Indonesia | 1 | 1% |
| Netherlands | 1 | 1% |
| France | 1 | 1% |
| Unknown | 83 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 22% |
| Researcher | 11 | 13% |
| Student > Master | 9 | 10% |
| Professor | 5 | 6% |
| Student > Bachelor | 5 | 6% |
| Other | 17 | 20% |
| Unknown | 20 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 36% |
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 7% |
| Mathematics | 4 | 5% |
| Agricultural and Biological Sciences | 3 | 3% |
| Computer Science | 3 | 3% |
| Other | 10 | 12% |
| Unknown | 29 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 August 2020.
All research outputs
#2,326,538
of 23,509,982 outputs
Outputs from Systematic Reviews
#406
of 2,043 outputs
Outputs of similar age
#34,868
of 286,908 outputs
Outputs of similar age from Systematic Reviews
#8
of 38 outputs
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So far Altmetric has tracked 2,043 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.9. This one has done well, scoring higher than 80% of its peers.
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We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.