An evolving machine-learning-based algorithm to early predict response to anti-CGRP monoclonal antibodies in patients with migraine.

Journal: Cephalalgia : an international journal of headache
PMID: 39654467

Abstract

BACKGROUND: The present study aimed to determine whether machine-learning (ML)-based models can predict 3-, 6, and 12-month responses to the monoclonal antibodies (mAbs) against the calcitonin gene-related peptide (CGRP) or its receptor (anti-CGRPmAbs) in patients with migraine using early predictors (up to one month) and to create an evolving prediction tool.

Authors

  • Marina Romozzi
    Dipartimento Universitario di Neuroscienze, Università Cattolica del Sacro Cuore, Rome, Italy.
  • Ammar Lokhandwala
    Department of Computer Science, Drexel University, Philadelphia, PA.
  • Catello Vollono
    Dipartimento Universitario di Neuroscienze, Università Cattolica del Sacro Cuore, Rome, Italy.
  • Giulia Vigani
    Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, Florence, Italy.
  • Andrea Burgalassi
    Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, Florence, Italy.
  • David García-Azorín
    Headache Unit, Department of Neurology, Hospital Clinico Universitario de Valladolid, Valladolid, Spain.
  • Paolo Calabresi
    Sezione di Malattie Infettive, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy.
  • Alberto Chiarugi
    Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, Florence, Italy.
  • Pierangelo Geppetti
    Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, Florence, Italy.
  • Luigi Francesco Iannone
    Section of Clinical Pharmacology and Oncology, Department of Health Sciences, University of Florence, Florence, Italy.

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