Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Multidimensional Statistical Technique for Interpreting the Spontaneous breakthrough Cancer Pain Phenomenon. A Secondary Analysis from the IOPS-MS Study

Version 1 : Received: 20 July 2021 / Approved: 21 July 2021 / Online: 21 July 2021 (09:50:29 CEST)

A peer-reviewed article of this Preprint also exists.

Cascella, M.; Crispo, A.; Esposito, G.; Forte, C.A.; Coluccia, S.; Porciello, G.; Amore, A.; Bimonte, S.; Mercadante, S.; Caraceni, A.; Mammucari, M.; Marchetti, P.; Mediati, R.D.; Natoli, S.; Tonini, G.; Cuomo, A. Multidimensional Statistical Technique for Interpreting the Spontaneous Breakthrough Cancer Pain Phenomenon. A Secondary Analysis from the IOPS-MS Study. Cancers 2021, 13, 4018. Cascella, M.; Crispo, A.; Esposito, G.; Forte, C.A.; Coluccia, S.; Porciello, G.; Amore, A.; Bimonte, S.; Mercadante, S.; Caraceni, A.; Mammucari, M.; Marchetti, P.; Mediati, R.D.; Natoli, S.; Tonini, G.; Cuomo, A. Multidimensional Statistical Technique for Interpreting the Spontaneous Breakthrough Cancer Pain Phenomenon. A Secondary Analysis from the IOPS-MS Study. Cancers 2021, 13, 4018.

Journal reference: Cancers 2021, 13, 4018
DOI: 10.3390/cancers13164018

Abstract

Breakthrough cancer pain (BTcP) is a temporary exacerbation of pain that "breaks through" a phase of adequate pain control by an opioid-based therapy. The non-predictable BTcP (NP-BTcP) is a subtype of BTcP that occurs in the absence of any specific activity. Since NP-BTcP has an important clinical impact, this analysis is aimed at characterizing the NP-BTcP phenomenon through a multidimensional statistical technique. This is a secondary analysis based on the Italian Oncologic Pain multiSetting - Multicentric Survey (IOPS-MS) . A correlation analysis was performed to characterize NP-BTcP profile about its intensity, number of episodes per day, and type. The Multidimensional Correspondence Analysis (MCA) determined the identification of 4 groups (Phenotypes). A univariate analysis was performed to assess differences between the 4 Phenotypes and selected covariates. The four phenotypes represent the hierarchical classification according to the status of NP-BTcP: from the best (Phenotype 1) to the worst (Phenotype 4). The univariate analysis found a significant association between the onset time >10 min in the Phenotype 1 (37.3%) vs. the onset ≤ 10 min in Phenotype 4 (74.2%) (p<0.001). The Phenotype 1 was characterized by gastrointestinal type of cancer (26.4%) respect to Phenotype 4 where the most frequent cancer affected the lung (28.8%) (p<0.001). Phenotype 4 was mainly managed with rapid onset opioids, while in Phenotype 1 many patients were treated with oral, subcutaneous, or intravenous morphine (56.4% and 44.4%, respectively; p=0.008). The ability to characterize NP-BTcP can offer enormous benefits for the management of this serious aspect of cancer pain. This strategy can provide many indications for identifying the diagnostic and therapeutic gaps on NP-BTcP management.

Keywords

cancer pain; breakthrough cancer pain; cluster analysis

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