Flexibility in the Modelling of Comparative Effectiveness in the Absence of Head-to-Head Comparisons in the NICE Single Technology Appraisal of Fenfluramine for Treating Seizures Associated with Lennox–Gastaut Syndrome: An External Assessment Group Perspective

Evidence-based healthcare decision-making requires systematic comparison of the consequences of all relevant interventions by synthesising the best available evidence, often into economic models [ 1 , 2 , 3 ]. Robust head-to-head randomised controlled trials (RCTs) are considered the gold standard for providing evidence on comparative effectiveness, as they are typically the study design least likely to be biased [ 4 ]. However, such trials are not always feasible. In the absence of direct head-to-head comparisons, alternative approaches such as indirect treatment comparisons (ITC) and network meta-analyses (NMA) can inform comparative effectiveness [ 2 ]. Commonly used approaches include simple naïve comparisons, Bayesian NMA, and population-adjusted indirect comparisons with individual patient data [ 5 , 6 , 7 ]. These methods depend heavily on assumptions (e.g., trial homogeneity, choice of population, approach to missing data, network connectivity), which may introduce bias into economic models, affecting reimbursement decisions. In cases where clinical similarity is considered plausible, pragmatic assumptions of equivalent efficacy can justify cost-comparison analyses [ 8 , 9 , 10 ]. This range of available approaches consequently enables flexibility in the modelling of comparative effectiveness, while the implications for cost-effectiveness outcomes may be considerable. This commentary emphasises the key learnings regarding flexibility in the modelling of comparative effectiveness in the absence of direct head-to-head comparisons from the perspective of the External Assessment Group (EAG).