Evidence synthesis as the key to more coherent and efficient research.
BACKGROUND
Systematic review and meta-analysis currently underpin much of evidence-based medicine. Such methodologies bring order to previous research, but future research planning remains relatively incoherent and inefficient.


METHODS
To outline a framework for evaluation of health interventions, aimed at increasing coherence and efficiency through i) making better use of information contained within the existing evidence-base when designing future studies; and ii) maximising the information available and thus potentially reducing the need for future studies.


RESULTS
The framework presented insists that an up-to-date meta-analysis of existing randomised controlled trials (RCTs) should always be considered before future trials are conducted. Such a meta-analysis should inform critical design issues such as sample size determination. The contexts in which the use of individual patient data meta-analysis and mixed treatment comparisons modelling may be beneficial before further RCTs are conducted are considered. Consideration should also be given to how any newly planned RCTs would contribute to the totality of evidence through its incorporation into an updated meta-analysis. We illustrate how new RCTs can have very low power to change inferences of an existing meta-analysis, particularly when between study heterogeneity is taken into consideration.


CONCLUSIONS
While the collation of existing evidence as the basis for clinical practice is now routine, a more coherent and efficient approach to planning future RCTs to strengthen the evidence base needs to be developed. The framework presented is a proposal for how this situation can be improved.
Sutton
Alexander J
AJ
Department of Health Sciences, University of Leicester, Leicester, UK. ajs22@le.ac.uk
Cooper
Nicola J
NJ
Jones
David R
DR
D019317:Evidence-Based Medicine / Q000379:methods*; D006801:Humans; D008491:Medical Informatics Applications; D015201:Meta-Analysis as Topic; D017063:Outcome Assessment, Health Care; D016032:Randomized Controlled Trials as Topic; D012107:Research Design