Abstract
BackgroundNetwork meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model. There are well-established advantages to using individual patient data to perform network meta-analysis and methods for network meta-analysis of individual patient data have already been developed for dichotomous and time-to-event data. This paper describes appropriate methods for the network meta-analysis of individual patient data on continuous outcomes.MethodsThis paper introduces and describes network meta-analysis of individual patient data models for continuous outcomes using the analysis of covariance framework. Comparisons are made between this approach and change score and final score only approaches, which are frequently used and have been proposed in the methodological literature. A motivating example on the effectiveness of acupuncture for chronic pain is used to demonstrate the methods. Individual patient data on 28 randomised controlled trials were synthesised. Consistency of endpoints across the evidence base was obtained through standardisation and mapping exercises.ResultsIndividual patient data availability avoided the use of non-baseline-adjusted models, allowing instead for analysis of covariance models to be applied and thus improving the precision of treatment effect estimates while adjusting for baseline imbalance.ConclusionsThe network meta-analysis of individual patient data using the analysis of covariance approach is advocated to be the most appropriate modelling approach for network meta-analysis of continuous outcomes, particularly in the presence of baseline imbalance. Further methods developments are required to address the challenge of analysing aggregate level data in the presence of baseline imbalance.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-016-0224-1) contains supplementary material, which is available to authorized users.
Highlights
Network meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model
In this paper we present a model for Network meta-analysis (NMA) of individual patient data (IPD) on continuous outcomes using the analysis of covariance (ANCOVA) approach which does adjust for baseline outcome data
ANCOVA analysis results Table 2 and Fig. 2 show the evidence from model 1 on relative treatment effect estimates adjusted for baseline and treatment-by-pain interaction effects
Summary
Network meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model. Evidence synthesis tools are increasingly used to pool estimates of treatment effects from multiple randomised controlled trials (RCTs) to inform assessments of comparative effectiveness generally, and in the context of health technology assessment One such tool is network meta-analysis (NMA, known as mixed treatment comparisons), which extends standard pair-wise meta-analysis by allowing the simultaneous synthesis of evidence on multiple treatments [1,2,3,4]. Recent publications by Hong et al [15] and Thom et al [16] explored and discussed the synthesis of continuous endpoints using IPD in NMA While the former proposes a framework to pool multiple continuous outcomes under contrast- and arm-based parameterisations, the latter focused mainly on modelling observational evidence available in both IPD and AD formats. In this paper we present a model for NMA of IPD on continuous outcomes using the analysis of covariance (ANCOVA) approach which does adjust for baseline outcome data
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