Measuring the impact of monoclonal antibody therapies

• Published in: Frontiers in medicine Vol. 10; p. 1256712
• Main Authors: Lim, Ka Keat, Ng, Kenrick, Balachandran, Sathiyaa, Russell, Mark D, Boalch, Amy, Sinclair, Alasdair, Coker, Bolaji, Vinnakota, Krishna, Mansoor, Rashid, Douiri, Abdel, Marks, Lara V, Sacks, Steven
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 2023
• Subjects: cost benefit evaluation; meta-analysis; monoclonal antibodies; real world data (RWD); systematic literature review; real world data (RWD); meta-analysis; cost benefit evaluation; systematic literature review; monoclonal antibodies
• ISSN: 2296-858X; 2296-858X
• DOI: 10.3389/fmed.2023.1256712

Monoclonal antibody (Mab) treatments have significantly improved the quality and quantity of life, but they are some of the most expensive treatments, resulting in a degree of hesitancy to introduce new Mab agents. A system for estimating the effect of Mab drugs, in general, would optimally inform health strategy and fully realize how a single scientific discovery can deliver health benefits. We evaluated such a method with several well-established Mab regimens. We selected five different Mab regimens in oncology and rheumatology in England. We carried out two systematic literature reviews and meta-analyses to assess health outcomes (Health Assessment Questionnaire-Disability Index for rheumatoid arthritis; overall mortality for melanoma) from real-world data and compared them to the outcomes from randomized control trials (RCTs). We applied economic modeling to estimate the net monetary benefits for health outcomes for the estimated patient population size for each Mab regimen. Meta-analyses of 27 eligible real-world data (RWD) sets and 26 randomized controlled trial (RCT) sets found close agreement between the observed and expected health outcomes. A Markov model showed the net positive monetary benefit in three Mab regimens and the negative benefit in two regimens. However, because of limited access to NHS data, the economic model made several assumptions about the number of treated patients and the cost of treatment to the NHS, the accuracy of which may affect the estimation of the net monetary benefit. RCT results reliably inform the real-world experience of Mab treatments. Calculation of the net monetary benefit by the algorithm described provides a valuable overall measure of the health impact, subject to the accuracy of data inputs. This study provides a compelling case for building a comprehensive, systematized, and accessible database and related analytics, on all Mab treatments within health services.