RESUMO
BACKGROUND: Modelling acute post-operative pain trajectories may improve the prediction of persistent pain after breast cancer surgery (PPBCS). This study aimed to investigate the predictive accuracy of early post-operative pain (EPOP) trajectories in the development of PPBCS. MATERIALS & METHODS: This observational study was conducted in a French Comprehensive Cancer Centre and included patients who underwent breast cancer surgery from December 2017 to November 2018. Perioperative and follow-up data were obtained from medical records, and anaesthesia and perioperative charts. EPOP was defined as pain intensity during the first 24 h after surgery, and modelled by a pain trajectory. K-means clustering method was used to identify patient subgroups with similar EPOP trajectories. The prevalence of moderate-to-severe PPBCS (numeric rating scale ≥4) was evaluated until 24 months after surgery. RESULTS: A total of 608 patients were included in the study, of which 18% (n = 108) and 9% (n = 52) reported mild and moderate-to-severe PPBCS, respectively. Based on EPOP trajectories, we were able to identify a low (64%, n = 388), resolved (30%, n = 182), and unresolved (6%, n = 38) pain group. Multivariate analysis identified younger age, axillary lymph node dissection, and unresolved EPOP trajectory as independent risk factors for moderate-to-severe PPBCS development. When compared to patients reporting mild PPBCS, moderate-to-severe PPBCS patients experienced significantly more neuropathic pain features, pain-related interference, and delayed opioid cessation. CONCLUSION: EPOP trajectories can distinguish between resolved and unresolved acute pain after breast cancer surgery, allowing early identification of patients at risk to develop significant PPBCS.