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单中心41例炎性乳腺癌的临床病理特征和预后分析 被引量:3

Prognosis and Clinical Characteristics of Inflammatory Breast Cancer
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摘要 目的回顾性分析女性炎性乳腺癌患者资料,初步探讨患者临床病理特征及影响预后的因素。方法收集2009年1月-2014年12月病理确诊、接受治疗、临床资料较完整的41例炎性乳腺癌患者的临床资料。采用对数秩检验和Cox回归分析影响炎性乳腺癌患者预后的因素。结果 41例炎性乳腺癌患者雌激素受体阴性率、孕激素受体阴性率和人类表皮生长因子受体2阳性率分别为58.5%、61.0%、34.2%。无疾病进展生存时间(PFS)为2-60个月,中位PFS为35个月,3年生存率为31.7%。单因素分析显示:TNM分期(P=0.016)、初始化学疗法(化疗)疗效(P=0.002)对PFS的影响有统计学意义。多因素分析显示:TNM分期(P=0.006)、初始化疗疗效(P=0.002)、表柔比星联合紫杉类化疗方案(P=0.041)均可影响患者预后。结论 TNM分期和初始化疗疗效是影响炎性乳腺癌预后的主要因素。蒽环类联合紫杉类的化疗方案优于其他方案。以化疗为主的多学科综合治疗模式是炎性乳腺癌患者的最佳治疗方案。 Objective To investigate the prognostic factors for inflammatory breast cancer based on the data from West China Hospital with a relatively large sample.Methods Clinical data of 41 patients with histopathologically confirmed inflammatory breast cancer(IBC) who received treatment at West China Hospital Oncology Center of Sichuan University between January 2009 and December 2014 were collected and analyzed.Log-rank test and Cox regression model were used for statistical analysis.Results In the study,negative estrogen receptor,negative progestrone receptor and positive human epidermal growth factor receptor- 2 were identified in 58.5%,61.0%and 34.2%of the inflammatory breast cancer tissues,respectively.Progress free survival(PFS) were between 2 and 60 months,with a median of 35 months.Univariate analysis showed that Tumor Node Metastasis(TNM) stage(P= 0.016) and therapeutic effect(P= 0.002)influenced the survival.Multivariate analysis showed that TNM stage(P= 0.006),therapeutic effect(P= 0.002),and anthracycline-taxane based chemotherapy(P= 0.041) were the significant prognostic factors.Conclusions TNM stage is the major prognostic factor for IBC.Preoperative chemotherapy with paclitaxel-epirubicin combination can improve the PFS of IBC.Comprehensive treatment mode with operation is recommended for the treatment of IBC.
出处 《华西医学》 CAS 2016年第1期48-52,共5页 West China Medical Journal
关键词 炎性乳腺癌 临床病理特征 单因素 多因素 生存分析 Inflammatory breast cancer Clinicopathological characteristics Univariate Multivariate Survival analysis
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