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Planning future studies based on the precision of network meta-analysis results
Statistics in medicine, 2016-03, Vol.35 (7), p.978-1000
Nikolakopoulou, Adriani
Mavridis, Dimitris
Salanti, Georgia
2016
Volltextzugriff (PDF)
Details
Autor(en) / Beteiligte
Nikolakopoulou, Adriani
Mavridis, Dimitris
Salanti, Georgia
Titel
Planning future studies based on the precision of network meta-analysis results
Ist Teil von
Statistics in medicine, 2016-03, Vol.35 (7), p.978-1000
Ort / Verlag
England: Blackwell Publishing Ltd
Erscheinungsjahr
2016
Quelle
MEDLINE
Beschreibungen/Notizen
When there are multiple competing interventions for a healthcare problem, the design of new studies could be based on the entire network of evidence as reflected in a network meta‐analysis. There is a practical need to answer how many (if any) studies are needed, of which design (i.e., which treatments to compare), and with what sample size to infer conclusively about the relative treatment effects of a set of target or all competing treatments and their relative ranking. We consider the precision in the results obtained from network meta‐analysis: the precision of the joint distribution of the estimated basic parameters of the model and the precision in the treatment ranking. We quantify the precision in the estimated effects by considering their variance–covariance matrix and estimate the precision in ranking by quantifying the dissimilarity of the density functions of summary effect estimates. Then, based on a desirable improvement in precision, we calculate the required sample size for each possible study design and number of study arms, and we present visual tools that can help trialists select the optimal study design. We use a published network of interventions for the treatment of hepatocellular carcinoma to illustrate the suggested methodology. The presented methodology can aid investigators making informed and evidence‐based decisions about planning new studies. Copyright © 2015 John Wiley & Sons, Ltd.
Sprache
Englisch
Identifikatoren
ISSN: 0277-6715
eISSN: 1097-0258
DOI: 10.1002/sim.6608
Titel-ID: cdi_proquest_miscellaneous_1770219410
Format
–
Schlagworte
Biostatistics
,
Carcinoma, Hepatocellular - therapy
,
clinical trial design
,
Computer Simulation
,
Evidence-Based Medicine - statistics & numerical data
,
Humans
,
indirect evidence
,
Intervention
,
Intestate
,
Liver Neoplasms - therapy
,
Medical statistics
,
Medical treatment
,
Meta-analysis
,
Models, Statistical
,
Network Meta-Analysis
,
precision
,
Precision Medicine - statistics & numerical data
,
Sample Size
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