Exploring Outcome Priorities and Real-Life Management of Chemotherapy-Induced Peripheral Neurotoxicity: A Survey of the Italian Association for the Study of Pain members

Abstract

Introduction: Chemotherapy-induced peripheral neurotoxicity (CIPN) affects nearly 70% of cancer patients after chemotherapy, causing sensory, motor, autonomic dysfunction, and neuropathic pain. The Desirability of Outcome Ranking (DOOR) framework is proposed as a better way to assess preventive or therapeutic interventions for CIPN. Methods: A survey was conducted among Italian healthcare professionals and researchers affiliated to the Italian Chapter of the International Association for the Study of Pain (AISD) to identify the most important outcomes in clinical management and research. Results: Among the 73 respondents, 61 qualified for the survey, with an overall response rate of 1.2%. The vast majority were physicians (77%), most of whom were anesthesiologists (47.5%). The results showed that pain, survival, sensory impairment, motor impairment, and quality of life were consistently ranked as the most important outcomes, but there was significant disagreement in the outcomes relative ranking, making it difficult to develop a DOOR algorithm. The study also revealed that clinicians commonly use structured interviews to evaluate patients with CIPN, and the most prescribed drugs or supplements were palmitoylethanolamide, pregabalin, gabapentin and alpha lipoic acid as preventive agents and pregabalin, palmitoylethanolamide, duloxetine, gabapentin, and amitriptyline as therapeutic agents. However, many of these drugs have not been clinically proven to be effective for CIPN. Discussion: This study suggests that the implementation of a DOOR framework for CIPN using healthcare professionals is more difficult than expected, given the significant disagreement in our respondents’ ranking of outcomes. Our work provides interesting topics for future research in CIPN, but its limitations include a small sample size, a low response rate, and a possible selection bias.