@article { author = {Xie, Xian-He and Hu, Yan-Fen and Jing, Chao and Luo, Shui-Mei and Lv, Yun-Fu and Yang, Hai-Tao and Li, Li-Na and Chen, Hui-Juan and Lin, Wan-Zun and Zheng, Wei-Li}, title = {A Comprehensive Model for Predicting Recurrence and Survival in Cases of Chinese Postoperative Invasive Breast Cancer}, journal = {Asian Pacific Journal of Cancer Prevention}, volume = {18}, number = {3}, pages = {727-733}, year = {2017}, publisher = {West Asia Organization for Cancer Prevention (WAOCP), APOCP's West Asia Chapter.}, issn = {1513-7368}, eissn = {2476-762X}, doi = {10.22034/APJCP.2017.18.3.727}, abstract = {  We investigated relationships between clinical pathologic data, molecular biomarkers and prognosis of invasive breast cancer based on a Chinese population. Immunohistochemistry (IHC) was used to assess the status of ER, PR, HER-2 and Ki-67, with fluorescence in situ hybridization (FISH) performed to further confirm HER-2 positivity with an equivocal result (IHC 2+). Subsequently, Kaplan-Meier univariate and multivariate COX regression analyses of ER, PR, HER-2, Ki-67, clinical features, therapeutic status and follow-up data were performed according to the establishment principle of the Nottingham prognostic index (NPI). From this study, age, tumor size, lymph node status, ER, HER-2, Ki-67 status were found to be associated with prognosis. Eventually, a prognostic model of (PI= (1.5×age) - size + (0.1×lymph node status) - (0.5×ER) + (2×HER-2) - (0.2×Ki-67)) was established with 288 randomly selected patients and verified with another 100 cases with invasive breast cancer. Pearson correlation analysis demonstrated a significant positive correlation index of 0.376 (P=0.012<0.05) between the prognostic index (PI) and actual prognosis. Remarkably, the consistency with the model predicted recurrence was 93% in the validation set. Therefore, it appears feasible to predict the prognosis of individuals with invasive breast cancer and to determine optimal therapeutic strategy with this model.}, keywords = {breast cancer,ER,Her-2,Ki-67,prognostic model}, url = {https://journal.waocp.org/article_44854.html}, eprint = {https://journal.waocp.org/article_44854_69fde74cbb3d0c53b60da053214c8c18.pdf} }