Predictive modelling of Immunogenicity to Botulinumtoxin A Treatments for Glabellar Lines.

ABSTRACT

INTRODUCTION: Botulinum toxin A (BoNT-A), derived from Clostridium botulinum, is widely used in medical and aesthetic treatments. Its clinical application extends from managing chronic conditions like cervical dystonia and migraine to reducing facial wrinkles. Despite its efficacy, a significant challenge associated with BoNT-A therapy is immunogenicity, where the immune system produces neutralising antibodies (NAbs) against BoNT-A, reducing its effectiveness over time. This issue is critical for patients requiring repeated treatments. The study aims to compare FDA-approved BoNT-A products, examining the factors influencing NAbs development using advanced machine learning techniques. METHOD: This research analysed data from randomised controlled trials (RCTs) involving five main BoNT-A products. The study selected trials based on detailed immunogenic responses to these treatments, particularly for glabellar lines. Machine learning models, including logistic regression, random forest classifiers, and Bayesian logistic regression, were employed to assess how treatment specifics and BoNT-A product types affect the development of NAbs. RESULTS: Analysis of 14 studies with 8,190 participants revealed that dosage and treatment frequency are key factors influencing the risk of NAbs development. Among BoNT-A products, IncobotulinumtoxinA shows the lowest, and AbobotulinumtoxinA the highest likelihood of inducing NAbs. The study's machine learning and logistic regression findings indicated that treatment planning must consider these variables to minimise immunogenicity. CONCLUSION: The study underscores the importance of understanding BoNT-A immunogenicity in clinical practice. By identifying the main predictors of NAbs development and differentiating the immunogenic potential of BoNT-A products, the research provides insights for clinicians in optimising treatment strategies. It highlights the need for careful treatment customisation to reduce immunogenic risks, advocating for further research into the mechanisms of BoNT-A immunogenicity.