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A Scoring System to Predict Arm Lymphedema Risk for Individual Chinese Breast Cancer Patients.
Breast Care 2016 Februrary
BACKGROUND: Lymphedema (LE) is recognized as a common complication after axillary lymph node dissection (ALND). Numerous studies have attempted to identify risk factors for LE. However, it is difficult to predict the probability of LE for an individual patient. The purpose of this study was to construct a scoring system for predicting the probability of LE after ALND for Chinese breast cancer patients.
PATIENTS AND METHODS: 358 breast cancer patients were surveyed and followed for 12 months. LE was defined by circumferential measurement. Univariate and multivariate logistic regression analyses were used to screen risk factors of LE. Based on this, ß-coefficient of each risk factor was translated into a prognostic score and the scoring system was constructed. The area under the receiver operating characteristic curve (AUC) and calibration were calculated as an index for the predictive value of the scoring system. The model was internally validated using bootstrapping techniques.
RESULTS: The incidence rate of LE was 31.84%. Variables associated with LE and their corresponding score in the scoring system were: the level of ALND (level I = 0, level II = 1, level III = 2), history of hypertension (yes = 1, no = 0), surgery on dominant arm (yes = 1, no = 0), radiotherapy (yes = 2, no = 0), and surgical infection/seroma/early edema (yes = 2, no = 0). The probability of LE was predicted according to the total risk scores. The system had good discrimination, with an AUC at 0.877. If a cut-off value of 3 was used, the sensitivity was 81.20% and the specificity was 80.90%. An individual whose total risk score was higher than 3 was recognized as being at risk for LE. On internal validation, the bootstrap-corrected predictive accuracy was 0.798. The model demonstrated excellent calibration in the development set and internal validation.
CONCLUSIONS: Our scoring system could be a simple and easy tool for physicians to estimate the risk of LE.
PATIENTS AND METHODS: 358 breast cancer patients were surveyed and followed for 12 months. LE was defined by circumferential measurement. Univariate and multivariate logistic regression analyses were used to screen risk factors of LE. Based on this, ß-coefficient of each risk factor was translated into a prognostic score and the scoring system was constructed. The area under the receiver operating characteristic curve (AUC) and calibration were calculated as an index for the predictive value of the scoring system. The model was internally validated using bootstrapping techniques.
RESULTS: The incidence rate of LE was 31.84%. Variables associated with LE and their corresponding score in the scoring system were: the level of ALND (level I = 0, level II = 1, level III = 2), history of hypertension (yes = 1, no = 0), surgery on dominant arm (yes = 1, no = 0), radiotherapy (yes = 2, no = 0), and surgical infection/seroma/early edema (yes = 2, no = 0). The probability of LE was predicted according to the total risk scores. The system had good discrimination, with an AUC at 0.877. If a cut-off value of 3 was used, the sensitivity was 81.20% and the specificity was 80.90%. An individual whose total risk score was higher than 3 was recognized as being at risk for LE. On internal validation, the bootstrap-corrected predictive accuracy was 0.798. The model demonstrated excellent calibration in the development set and internal validation.
CONCLUSIONS: Our scoring system could be a simple and easy tool for physicians to estimate the risk of LE.
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