Psychosocial and Psychophysical Characteristics Predict Pain Following Mastectomy

Simple preoperative person-type indicators were found to be useful for predicting pain trajectories among patients who underwent mastectomy, according to the results of a study published in the Journal of Pain.

Patients (N=228) scheduled to undergo surgery for breast cancer at Brigham and Women’s Hospital were recruited to participate in this study. Pain assessments were obtained 2 weeks, 3 months, 6 months, and 12 months following surgery, respectively. The Rapid OPPERA Algorithm (ROPA) clustering approach was used to evaluate differences among patients with differing pain trajectories on the basis of preoperative psychosocial psychophysical evaluations.

The mean age of the patients was 55.81 (standard deviation [SD], 12.37) years, 87% were White, 53% underwent lumpectomy, 34% underwent mastectomy with reconstruction, 13% underwent mastectomy, 64% underwent sentinel node biopsy, and 16% underwent axillary node dissection.

Three clusters of patients were identified: those who were pain sensitive (54.8%), those who were adaptive (26.8%), and those with global symptoms (18.4%). The patients in the global symptoms group were the youngest (mean, 52.31 years), followed by those who were adaptive (mean, 53.93 years) and those who were pain sensitive (mean, 57.90 years; P =.015).

At 2 weeks following surgery, participants in the global symptoms cluster reported worse cognitive and emotional functioning (P <.001), pain catastrophizing (P <.001), pain severity (P =.045), and physical functioning (P =.048) compared with participants in the adaptive and pain-sensitive clusters.

At 3, 6, and 12 months, compared with participants in the global symptoms group, those in the pain-sensitive and adaptive groups demonstrated significantly better cognitive and emotional functioning (both P <.001), pain severity (both P <.001), physical functioning (both P ≤.001), and pain catastrophizing scores (both P ≤.016).

A major limitation of this study is the potential limited availability in the clinical setting of the 4 preoperative variables used to cluster the study population.

Study authors concluded, “The application of the ROPA clustering technique, which uses four simple measures, to a perioperative cohort undergoing surgery allowed distinction of groups of patients who were at higher risk of acute and persistent postsurgical pain. This cross-institutional exercise suggests that clustering of patients may be useful across different diagnoses and clinical settings, and may be an important tool for personalized medicine in the future.”