Machine-Learning Exploration of Exposure-Effect Relationships of Cisplatin in Head and Neck Cancer Patients

• Published in: Pharmaceutics 2022-11, Vol.14 (11), p.2509
• Main Authors: Cauvin, Céleste, Bourguignon, Laurent, Carriat, Laure, Mence, Abel, Ghipponi, Pauline, Salas, Sébastien, Ciccolini, Joseph
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Applications; Bayesian; Cancer; Cancer therapies; Care and treatment; Cisplatin; Creatinine; Data mining; Diagnosis; Dosage and administration; Drug dosages; exposure-effect relationships; Generalized linear models; Head & neck cancer; Head and neck cancer; Health aspects; Life Sciences; Machine Learning; Methods; Patients; Pharmaceutical sciences; pharmacokinetics; Pharmacology; Plasma; Quality of life; Radiation therapy; Statistics
• ISSN: 1999-4923; 1999-4923
• DOI: 10.3390/pharmaceutics14112509

Cisplatin is a pivotal drug in the treatment of head and neck cancer, and personalized dosage should help the preservation of an optimal toxicity-efficacy ratio. We analyzed the exposure-effect relationships of 80 adult patients with head and neck cancers and treated with standard Cisplatin-based regimen administered as three-hour infusion. Individual pharmacokinetics (PK) parameters of Cisplatin were identified using a Bayesian approach. Nephrotoxicity and ototoxicity were considered as typical Cisplatin-related toxicities according to Common Terminology Criteria for Adverse Events (CTCAE) standards. Efficacy was evaluated based upon Response Evaluation Criteria in Solid Tumors (RECIST) criteria. Up to nine different machine-learning algorithms were tested to decipher the exposure-effect relationships with Cisplatin. The generalized linear model was the best algorithm with an accuracy of 0.71, a recall of 0.55 and a precision of 0.75. Among the various metrics for exposure (i.e., maximal concentration (Cmax), area-under-the-curve (AUC), trough levels), Cmax, comprising a range between 2.4 and 4.1 µg/mL, was the best one to be considered. When comparing a consequent, model-informed dosage with the standard dosage in 20 new patients, our strategy would have led to a reduced dosage in patients who would eventually prove to have severe toxicities while increasing dosage in patients with progressive disease. Determining a target Cmax could pave the way for PK-guided precision dosage with Cisplatin given as three-hour infusion.