Clinical Prediction Model and Tool for Assessing Risk of Persistent Pain After Breast Cancer Surgery

TY - JOUR

T1 - Clinical Prediction Model and Tool for Assessing Risk of Persistent Pain After Breast Cancer Surgery

AU - Meretoja, Tuomo J

AU - Andersen, Kenneth Geving

AU - Bruce, Julie

AU - Haasio, Lassi

AU - Sipilä, Reetta

AU - Scott, Neil W

AU - Ripatti, Samuli

AU - Kehlet, Henrik

AU - Kalso, Eija

PY - 2017/5

Y1 - 2017/5

N2 - Purpose Persistent pain after breast cancer surgery is a well-recognized problem, with moderate to severe pain affecting 15% to 20% of women at 1 year from surgery. Several risk factors for persistent pain have been recognized, but tools to identify high-risk patients and preventive interventions are missing. The aim was to develop a clinically applicable risk prediction tool. Methods The prediction models were developed and tested using three prospective data sets from Finland (n = 860), Denmark (n = 453), and Scotland (n = 231). Prediction models for persistent pain of moderate to severe intensity at 1 year postoperatively were developed by logistic regression analyses in the Finnish patient cohort. The models were tested in two independent cohorts from Denmark and Scotland by assessing the areas under the receiver operating characteristics curves (ROC-AUCs). The outcome variable was moderate to severe persistent pain at 1 year from surgery in the Finnish and Danish cohorts and at 9 months in the Scottish cohort. Results Moderate to severe persistent pain occurred in 13.5%, 13.9%, and 20.3% of the patients in the three studies, respectively. Preoperative pain in the operative area ( P < .001), high body mass index ( P = .039), axillary lymph node dissection ( P = .008), and more severe acute postoperative pain intensity at the seventh postoperative day ( P = .003) predicted persistent pain in the final prediction model, which performed well in the Danish (ROC-AUC, 0.739) and Scottish (ROC-AUC, 0.740) cohorts. At the 20% risk level, the model had 32.8% and 47.4% sensitivity and 94.4% and 82.4% specificity in the Danish and Scottish cohorts, respectively. Conclusion Our validated prediction models and an online risk calculator provide clinicians and researchers with a simple tool to screen for patients at high risk of developing persistent pain after breast cancer surgery.

AB - Purpose Persistent pain after breast cancer surgery is a well-recognized problem, with moderate to severe pain affecting 15% to 20% of women at 1 year from surgery. Several risk factors for persistent pain have been recognized, but tools to identify high-risk patients and preventive interventions are missing. The aim was to develop a clinically applicable risk prediction tool. Methods The prediction models were developed and tested using three prospective data sets from Finland (n = 860), Denmark (n = 453), and Scotland (n = 231). Prediction models for persistent pain of moderate to severe intensity at 1 year postoperatively were developed by logistic regression analyses in the Finnish patient cohort. The models were tested in two independent cohorts from Denmark and Scotland by assessing the areas under the receiver operating characteristics curves (ROC-AUCs). The outcome variable was moderate to severe persistent pain at 1 year from surgery in the Finnish and Danish cohorts and at 9 months in the Scottish cohort. Results Moderate to severe persistent pain occurred in 13.5%, 13.9%, and 20.3% of the patients in the three studies, respectively. Preoperative pain in the operative area ( P < .001), high body mass index ( P = .039), axillary lymph node dissection ( P = .008), and more severe acute postoperative pain intensity at the seventh postoperative day ( P = .003) predicted persistent pain in the final prediction model, which performed well in the Danish (ROC-AUC, 0.739) and Scottish (ROC-AUC, 0.740) cohorts. At the 20% risk level, the model had 32.8% and 47.4% sensitivity and 94.4% and 82.4% specificity in the Danish and Scottish cohorts, respectively. Conclusion Our validated prediction models and an online risk calculator provide clinicians and researchers with a simple tool to screen for patients at high risk of developing persistent pain after breast cancer surgery.

KW - Breast Neoplasms/pathology

KW - Cancer Pain/etiology

KW - Cohort Studies

KW - Female

KW - Humans

KW - Logistic Models

KW - Middle Aged

KW - Models, Statistical

KW - Pain, Postoperative/etiology

KW - Predictive Value of Tests

KW - ROC Curve

KW - Risk Assessment

U2 - 10.1200/JCO.2016.70.3413

DO - 10.1200/JCO.2016.70.3413

M3 - Journal article

C2 - 28524782

SN - 0732-183X

VL - 35

SP - 1660

EP - 1667

JO - Journal of Clinical Oncology

JF - Journal of Clinical Oncology

IS - 15

ER -