Abstract

Network meta-analysis (NMA) indirect treatment comparisons (ITCs) employ a network of trials, comparing common interventions in similar patient populations, to assess relative efficacy in the absence of head-to-head trials. Where single-arm trials or heterogeneous trial populations constitute the best-available evidence, individual patient data (IPD) from trials can be used to adjust for baseline characteristics and enable a comparison of treatment efficacy. The acceptance of ITC methods other than NMA by the UK National Institute for Health and Care Excellence (NICE) Evidence Review Groups (ERGs) in technology assessments (TAs) for haematological cancer therapies has not been described. A targeted review of NICE TAs in lymphoma and myeloma published between 2009 and 2019 examined the ITC methods used in manufacturer submissions and subsequent ERG comments on methodological quality. All types of ITC, except NMA, were considered. Of the 25 TAs identified in the review, 5 were excluded due to appraisal termination. Amongst the 20 TAs included, 13 (65%) included ITC methods to synthesise data; eight (40%) matched-adjusted indirect comparisons (MAIC); four (20%) multiple treatment comparisons (Bucher, Bayesian or other); and three (15%) naïve indirect comparisons. Two appraisals presented more than one ITC method. Non-NMA ITC techniques were accepted by ERGs where direct randomised comparative evidence was not available despite substantial uncertainty around treatment effect estimates, and inconsistencies in the choice of covariates and cohorts for matched analyses. Non-NMA ITC techniques are commonly used in submissions to NICE in haematological cancers, with MAIC most frequently used by manufacturers. Matching, or adjusting on baseline characteristics using IPD, can be used to demonstrate the relative effectiveness of new therapies in the absence of evidence from comparative trials. Non-NMA ITC methods preferred by ERGs are not apparent despite published guidance on population-adjusted indirect comparisons by the NICE Decision Support Unit.

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