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

A large proportion of patients with cancer suffer from breakthrough cancer pain (BTcP). Several unmet clinical needs concerning BTcP treatment, such as optimal opioid dosages, are being investigated. In this analysis the hypothesis, we explore with an unsupervised learning algorithm whether distinct subtypes of BTcP exist and whether they can provide new insights into clinical practice. Partitioning around a k-medoids algorithm on a large data set of patients with BTcP, previously collected by the Italian Oncologic Pain Survey group, was used to identify possible subgroups of BTcP. Resulting clusters were analyzed in terms of BTcP therapy satisfaction, clinical features, and use of basal pain and rapid-onset opioids. Opioid dosages were converted to a unique scale and the BTcP opioids-to-basal pain opioids ratio was calculated for each patient. We used polynomial logistic regression to catch nonlinear relationships between therapy satisfaction and opioid use. Our algorithm identified 12 distinct BTcP clusters. Optimal BTcP opioids-to-basal pain opioids ratios differed across the clusters, ranging from 15% to 50%. The majority of clusters were linked to a peculiar association of certain drugs with therapy satisfaction or dissatisfaction. A free online tool was created for new patients' cluster computation to validate these clusters in future studies and provide handy indications for personalized BTcP therapy. 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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© 2020 by American Society of Clinical Oncology.

Déclaration de conflit d'intérêts

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/po/author-center. Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments). Paolo MancaPatents, Royalties, Other Intellectual Property: Patent for a method for the identification of gene panels optimal for TMB estimation (Inst)Grazia ArmentoConsulting or Advisory Role: Novartis Travel, Accommodations, Expenses: TevaBruno VincenziSpeakers' Bureau: PharmaMarPaolo MarchettiHonoraria: AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eisai, Incyte, Merck Sharp & Dohme, Novartis, Pierre Fabre, Pfizer, Roche Consulting or Advisory Role: AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Merck Sharp & Dohme, Novartis, Pierre Fabre, Roche Research Funding: AstraZeneca (Inst), Bristol Myers Squibb (Inst), Incyte (Inst), Eli Lilly (Inst), Merck Serono (Inst), Merck Sharp & Dohme (Inst), Novartis (Inst), NanoString Technologies (Inst), Pierre Fabre (Inst), Pfizer (Inst), Roche (Inst), Takeda (Inst) Travel, Accommodations, Expenses: Boehringer Ingelheim, Bristol Myers Squibb, Incyte, Merck Sharp & Dohme, RocheAugusto CaraceniConsulting or Advisory Role: Angelini Pharma, Shionogi Molteni, Kyowa Hakko KirinRocco Domenico MediatiSpeakers' Bureau: Angelini Pharma, Kyowa Hakko KirinRenato VellucciTravel, Accommodations, Expenses: Grünenthal GroupSilvia NatoliConsulting or Advisory Role: Grünenthal Italia, Sandoz, Angelini Pharma Speakers' Bureau: Mylan Travel, Accommodations, Expenses: AMS Group, SandozGiuseppe AzzarelloConsulting or Advisory Role: MerckVittorio GuardamagnaConsulting or Advisory Role: Istituto GentiliStefano MorosoConsulting or Advisory Role: Novartis, Janssen-CilagGiuseppe ToniniConsulting or Advisory Role: Novartis, Molteni Farmaceutici, Roche, Pierre Fabre, Italfarmaco Research Funding: PharmaMar (Inst), Novartis (Inst) No other potential conflicts of interest were reported.