Predictors of pathological complete response after neoadjuvant chemotherapy for breast cancer
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摘要:
目的:探讨乳腺癌患者的一般临床因素和癌组织免疫组化(immunohistochemistry,IHC)对新辅助化疗(neoadjuvant che-motherapy,NAC)(多西他赛+表柔比星/吡柔比星+环磷酰胺)后达到病理完全缓解(pathological complete response,pCR)的预测作用。方法:对2012年1月1日到2012年12月31日接受NAC的257例乳腺癌患者进行回顾性分析,采用卡方检验和logistic回归分析对一般临床因素及IHC分子的表达水平进行比较。结果:257例患者中,pCR率为16.3%。单因素分析:年龄、月经情况、平均体质指数(body mass index,BMI)、血型等与pCR无相关性,肿瘤分期T1(P=0.006)、雌激素受体(estrogen receptor,ER)阴性(P=0.000)、孕激素受体(progesterone receptor,PR)阴性(P=0.013)、Ki67(增殖分数>30%,P=0.004)和生育1个孩子(P=0.032)与pCR有相关性。多因素分析:生育1个孩子(OR=3.926,95%CI=1.040~14.821)、双阴性乳腺癌[(double negative breast cancer,DNBC),ER、PR均为阴性;OR=7.248,95%CI=2.453~21.416]和Ki67>30%(OR=4.355,95%CI=1.513~12.537)是pCR的独立预测因素。结论:生育1个孩子、DNBC和Ki67>30%对蒽环类NAC更容易取得pCR。生育史是新发现的NAC非常重要的预测因素。
Abstract:
Objective:To discuss the general clinical factors for patients with breast cancer and to identify predicting function of im-munohistochemistry(IHC) for pathological complete response after neoadjuvant chemotherapy(NAC) (docetaxel + epirubicin/ pirarubicin + cyclophosphamide). Methods:From 1 January 2012 to 31 December 2012,257 patients treated with NAC were included in this retrospective study.Data were compared using Chi-square,Fisher’s exact tests,likelyhood ratio or multivariate analysis of variance,etc. Results:Of the 257 breast cancer patients receiving NAC,42(16.3%) gained pCR. Five factors were associ-ated with pCR:tumor grade T1(P=0.006),estrogen receptor negative(P=0.000),progesterone receptor negative(P=0.013),Ki67(proliferation scores >30%,P=0.004) and giving birth to one child(P=0.032). In multivariate analysis,double negative breast cancer(DNBC)(OR=7.248,95%CI=2.453 to 21.416),Ki67(proliferation scores >30%,OR=4.355,95%CI=1.513 to 12.537),giving birth to one child(OR=3.926,95%CI=1.040 to 14.821)were found to significantly correlate with pCR. Conclusion:DNBC,Ki67(prolifera-tion scores >30%),giving birth to one child are more likely to experience pCR to NAC. Childbearing history is newly identified as an important predictor.