Post-mastectomy pain syndrome as a model for mixed pain: clinical evidence from a specialized cancer pain clinic

乳房切除术后疼痛综合征作为混合性疼痛的模型:来自一家专门癌症疼痛诊所的临床证据

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Abstract

INTRODUCTION: Post-mastectomy pain syndrome (PMPS) is a common and disabling complication after breast cancer surgery. Although traditionally categorized as neuropathic or nociceptive, many patients present with overlapping features consistent with mixed pain, a phenotype that remains poorly defined in clinical practice. METHODS: We performed a retrospective analysis of prospectively maintained data from women with refractory PMPS referred to a tertiary cancer-related pain clinic between January 2022 and September 2025. Pain was classified as nociceptive, neuropathic, or mixed based on structured clinical assessment. Patient-reported measures included the Brief Pain Inventory (BPI) and Pain Catastrophizing Scale (PCS). Multivariable logistic regression was used to examine factors independently associated with mixed pain. RESULTS: One hundred twenty women (mean age 57.9 ± 12.5 years) were included. Pain phenotypes were nociceptive in 40.8%, neuropathic in 25.0%, and mixed in 34.2%. Pain intensity, interference, and catastrophizing scores were elevated across groups without statistically significant differences (all p > 0.05). In adjusted analyses (analytic N = 113), multiplicity of pain sources (≥2 concurrent pain generators; adjusted OR 49.96; 95% CI 11.69-213.41) and radiotherapy-attributed pain (adjusted OR 5.75; 95% CI 1.15-28.82) were independently associated with mixed pain. Model stability was evaluated in sensitivity analyses using Firth's penalized likelihood logistic regression. CONCLUSION: In this tertiary cohort of women with refractory PMPS, mixed pain accounted for approximately one-third of cases and was independently associated with multiple concurrent pain sources and radiotherapy-attributed pain. These findings suggest that the coexistence of multiple pain sources, rather than pain severity alone, may characterize mixed pain presentations. Given the observational design and model limitations, results should be interpreted as hypothesis-generating. Mechanism-based assessment may help inform individualized management strategies.

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