关键词: LASSO回归, 期乳腺癌, Ⅳ, 手术

Abstract: Objective The aim of this study was to construct a prognosis nomogram for patients with de novo stage Ⅳ breast cancer, screening out those who could benefit from locoregional surgery.Methods The clinicopathologic characteristics of 7379 patients with de novo stage Ⅳ breast cancer in SEER database from 1973-2015 were analyzed. Overall survival（OS） was estimated using the Kaplan-Meier method and the log-rank test. Least Absolute Shrinkage and Selector Operation （LASSO） regression analysis were used to screen out the clinicopathologic characteristics which related to the prognosis of patients. The risk score equation was established by multivariate Cox regression analysis and the risk prognosis model was constructed. The predictive accuracy of nomogram was assessed by using operating characteristic curve （ROC） analysis, calculating the area under the curves （AUC）, and concordance index （C-index）. Results Among 7379 patients included in this study, 2703 patients （36.6%） received locoregional surgery and 4676 patients （63.4%） underwent no surgery. LASSO regression analysis screened out 10 clinicopathologic characteristics （age, histologic type, clinical tumor stage, ER status, PR status, HER-2 status, bone metastasis, liver metastasis, lung metastasis, lymph metastasis） which were independent prognosis factors and could be used to constructed risk model for predicting the prognosis of patients. The model predicted well in 1-year and 3-year OS in development cohort （AUCs for 1-, 3-year OS of 0.75, 0.73, respectively） and validation cohort （AUCs for 1-, 3-year OS of 0.72, 0.75, respectively）. C-index of the model was 0.700 （95%CI： 0.69-0.71） and 0.695 （95%CI： 0.67-0.71） respectively in development cohort and validation cohort. According to risk score, patients could divide into low-risk group, medium-risk group, and high-risk group. Kaplan-Meier analyses showed that patients from low-risk and medium-risk group could benefit from locoregional surgery（low-riskgroup： development cohort：HR=0.49, 95%CI：0.42~0.57, P<0.001;validation cohort： HR=0.43, 95%CI： 0.34~0.55, P<0.001; medium-risk group：development cohort： HR=0.75, 95%CI：0.65~0.86, P<0.001; validation cohort：HR=0.72, 95%CI：0.57~0.90, P=0.003）, whereas patients underwent locoregional surgery from high-risk group couldn't improve OS（development cohort： HR=0.65, 95%CI： 0.41~1.02, P=0.06; validation cohort： HR=0.83, 95%CI： 0.41~1.69, P=0.61）. Conclusion The prognosis nomogram of patients with de novo stage Ⅳ breast cancer was constructed based on machine learning algorithms, which could effectively distinguish patients between low-risk group, medium-risk group, and high-risk group. Moreover, locoregional surgery was not recommended for patients from high-risk group （> 360）.

Key words: surgery, breast cancer, LASSO regression analysis, stage Ⅳ