A prognostic nomogram for ER/PR+ and HER2- breast cancer patients based on classical immunohistochemical index / 中国肿瘤生物治疗杂志

ABSTRACT

@# Objective: To modify traditional prognostic model for patients with ER/PR+, HER2- breast cancer to meet the actual requirements in current clinical practice. Methods: 335 patients with ER/PR+, HER2- breast cancer, who were admitted in Department of Breast Surgery, Shanghai Huangpu Center Hospital from January 2009 to December 2009, were enrolled in this study. 97 variables were incorporated into the model, using SCAD variable selection method, after fully considering whether covariates existing a log-linear relationship, reasonable determination of the cut-off value of the covariates in non-logarithmic linear relationship (piecewise linear relationship) and collinear and interaction, then we set up a new Cox regression prognostic model for traditional ER/PR+, HER2-type breast cancer patients with traditional immunohistochemical indicators, and further establish its nomogram model. On this basis, a nomogram of the survival probability of 1-, 3-, and 5- years after surgery was established; The discrimination and calibration of model were compared to evaluate the predictive ability of the model. Results: The Cox regression model shows that the prognosis of patients are associated with the histologic grade, lymph node metastasis, Ki67, PR and age etc. Among them, the histologic grade and lymph node metastasis have log-linear relationship with prognosis; Ki67, PR and age have non-log-linear relationship with prognosis and the reasonable cut-off values are Ki67(60%)，PR（20%）and age（55 years old） . Area under the receiver operating characteristic (ROC) curve（AUC）of this Cox model for 1-, 3- and 5- year survival after surgery are all above 0.85, indicating high discrimination. The Grønnesby-Borgan goodness-of-fit test statistics of this model is 1.37 with P>0.05, indicating good calibration. Conclusion: The modified nomogram.could accurately, directly and effectively predict the survival probability of patients, which may exert good guidance for the clinical practice for patients with breast cancer.