Page 19 - Haematologica Vol. 109 - July 2024

EDITORIAL E. Bachy
Figure 1. Principle and level of clinical evidence of matching-adjusted indirect comparison. (A) Level of evidence of various treat- ment comparisons from unadjusted and unmatched comparison (poorest level of evidence) to randomized treatment allocation (gold standard). The list of various statistical approaches to make patient population as comparable as possible is not exhaustive. (B) Matching-adjusted indirect comparison (MAIC) allows for the comparison between aggregated patient data (e.g., based on patient characteristics from a trial publication) and individual patient data (from another trial or a real-life cohort or any other source of individual data). Basically, by removing or pondering patient characteristics to closely match final aggregated data (e.g., patient median age depicted here), the final group of patients from the cohort with available individual patient data (IPD) is ren- dered as similar as possible to the cohort for which only aggregated data are available (e.g., here, similar median age). This is performed for all variables that are considered as critical confounders for treatment comparison. Finally, outcome is compared in the 2 matched populations; here, the prognosis of the IPD is depicted as better after matching (blue line), while, by definition, the survival of the aggregated data population is left unchanged after matching (red line). Depicted data and survivals are for illustration only and are not based on true or relevant values or weights. PS: propensity score; yr: year.
was performed in the GO29781 trial and more accurately than what is usually performed outside a trial setting. It is also important to notice that among those patients from the LEO cohort, 11 received either another bispecific anti- body or a chimeric antigen receptor T-cell therapy and 38 another novel agent as monotherapy or in combination with an anti-CD20 monoclonal antibody. This explains, at least in part, the good outcome of patients from the LEO cohort and is critical to appreciate the small differences observed
in the MAIC according to the various scenarios tested. Beyond information about efficacy of this bi-specific anti- body, many lessons are to be learned from this study for any hematologist aiming at developing a critical appraisal of MAIC conclusions as they become increasingly used to support early phase study results for therapies still under development. First, results are strongly dependent upon which scenario and constraints are applied to the model. Second, a careful analysis of which variables have
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