Comparative effectiveness: Queries and clarifications

While a head-to-head randomized controlled trial (RCT) is the gold standard for generating comparative efficacy data, RCTs are not always feasible, and multiple relevant comparators may exist which could make it unlikely that a trial will be conducted for every pairwise comparison of interest. In rare diseases, small patient populations can make it difficult to adequately power an RCT, and ethical considerations may preclude randomizing patients.

Additionally, treatments may continue to come to market in a given therapeutic area, meaning a relevant comparator may not have existed when the pivotal trial was designed, and manufacturers of existing therapies may not be sufficiently incentivized to invest limited resources into a comparative trial. These gaps are why comparative effectiveness methods such as network meta-analyses (NMA), matching adjusted indirect comparators (MAIC), and external control arms (ECAs) are essential tools, enabling the generation of comparative effectiveness evidence using available data when head-to-head evidence from an RCT does not exist.

How do you decide between approaches like NMA, MAIC, or an external control arm?

The choice between these methods depends on several factors that include strategic needs, data availability, and methodological considerations. When considering ITCs, you should start with an evaluation of the treatment landscape and available evidence base from a systematic literature review. Once your evidence base is identified, you should assess the available evidence in the context of your strategic comparative evidence needs. When a connected network of sufficiently comparable randomized trials exists, NMAs are typically preferred because they maximize use of the evidence base while preserving the advantages of randomization across multiple treatments.

When the evidence network is sparse or clinically heterogeneous across studies, MAICs become more appropriate because they explicitly address cross-trial differences that could bias indirect comparisons. External control arm studies are best suited for scenarios where the evidence base doesn’t capture important treatment effect modifiers, or the evidence base is sparse and disconnected. Ultimately, the best approach is one that leverages the appropriate network of evidence and adheres to the methodological assumptions necessary to draw valid conclusions.

When should teams start thinking about comparative effectiveness strategy — and why is timing important?

HEOR, Medical, and Market Access teams should align on a comparative effectiveness strategy before Phase II/III trial designs are finalized, so the program generates evidence that supports reimbursement, access, and product differentiation. This includes choosing the comparators, endpoints, and patient populations most relevant to payers, Health Technology Assessment (HTA) agencies, and treatment decision-makers. Early planning is critical to answer a central question: why should this product be covered, reimbursed, or preferred over existing alternatives?

If comparative evidence cannot be built into the Phase III program, teams should immediately develop a fit-for-purpose evidence generation plan to address expected gaps. Delayed planning increases the likelihood of evidence gaps that can weaken the value story, reduce leverage in pricing negotiations, and delay coverage decisions.