| Title |
Interpreting discordant indirect and multiple treatment comparison meta-analyses: an evaluation of direct acting antivirals for chronic hepatitis C infection
|
|---|---|
| Published in |
Clinical Epidemiology, June 2013
|
| DOI | 10.2147/clep.s44273 |
| Pubmed ID | |
| Authors |
Eric Druyts, Kristian Thorlund, Samantha Humphreys, Michaela Lion, Curtis L Cooper, Edward J Mills |
| Abstract |
Indirect treatment comparison (ITC) and multiple treatment comparison (MTC) meta-analyses are increasingly being used to estimate the comparative effectiveness of interventions when head-to-head data do not exist. ITC meta-analyses can be conducted using simple methodology to compare two interventions. MTC meta-analyses can be conducted using more complex methodology, often employing Bayesian approaches, to compare multiple interventions. As the number of ITC and MTC meta-analyses increase, it is common to find multiple analyses evaluating the same interventions in similar therapeutic areas. Depending on the choice of the methodological approach, the conclusions about relative treatment efficacy may differ. Such situations create uncertainty for decision makers. An illustration of this is provided by four ITC and MTC meta-analyses assessing the efficacy of boceprevir and telaprevir for chronic hepatitis C virus infection. This paper examines why these evaluations provide discordant results by examining specific methodological issues that can strengthen or weaken inferences. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 4 | 18% |
| Professor | 4 | 18% |
| Researcher | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Student > Master | 2 | 9% |
| Other | 5 | 23% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 59% |
| Agricultural and Biological Sciences | 2 | 9% |
| Arts and Humanities | 1 | 5% |
| Economics, Econometrics and Finance | 1 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 2 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 24 July 2013.
All research outputs
#13,386,934
of 22,714,025 outputs
Outputs from Clinical Epidemiology
#369
of 712 outputs
Outputs of similar age
#101,389
of 194,195 outputs
Outputs of similar age from Clinical Epidemiology
#8
of 10 outputs
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