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Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study.

Francesco PantanoPaolo MancaFrancesco PantanoTea ZeppolaAngelo OnoratoMichele IulianiSonia SimonettiBruno VincenziDaniele SantiniSebastiano MercadantePaolo MarchettiArturo CuomoAugusto CaraceniRocco Domenico MediatiRenato VellucciMassimo MammucariSilvia NatoliMarzia LazzariMario DauriClaudio AdileMario AiroldiGiuseppe AzzarelloLivio BlasiBruno ChiurazziDaniela DegiovanniFlavio FuscoVittorio Andrea GuardamagnaSimeone LiguoriLoredana PalermoSergio MameliFrancesco MaseduTeresita MazzeiRita Maria MelottiValentino MenardoDanilo MiottiStefano MorosoGaetano PascolettiStefano De SantisRemo OrsettiAlfonso PapaSergio RicciElvira ScelziMichele SofiaFederica AielliAlessandro ValleGiuseppe Tonini
Published in: JCO precision oncology (2020)
This work proposes a classification for BTcP and identifies subgroups of patients with unique efficacy of different pain medications. This work supports the theory that the optimal dose of BTcP opioids depends on the dose of basal opioids and identifies novel values that are possibly useful for future trials. These results will allow us to target BTcP therapy on the basis of patient characteristics and to define a precision medicine strategy also for supportive care.
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