Suppr超能文献

Neoadjuvant human epidermal growth factor receptor-2 targeted therapy in patients with locally advanced breast cancer.

作者信息

Cho Dong Hui, Lee Se Kyung, Kim Sangmin, Choi Min-Young, Jung Seung Pil, Lee Jeonghui, Kim Jiyoung, Koo Min Young, Bae Soo Youn, Kim Jung-Han, Kim Jee Soo, Ho Kil Won, Lee Jeong Eon, Nam Seok Jin, Yang Jung-Hyun

机构信息

Department of Surgery, Seoul Medical Center, Seoul, Korea.

出版信息

J Korean Surg Soc. 2013 May;84(5):273-80. doi: 10.4174/jkss.2013.84.5.273. Epub 2013 Apr 24.

Abstract

PURPOSE

We analyzed the responses of patients with locally advanced breast cancer to neoadjuvant chemotherapy (NAC) and NAC combined with neoadjuvant human epidermal growth factor receptor-2 (HER2) targeted therapy (NCHTT).

METHODS

We retrospectively reviewed 59 patients with HER2 amplified locally advanced breast cancer among patients who were treated surgically after neoadjuvant therapy at Samsung Medical Center between 2005 and 2009. Thirty-one patients received conventional NAC and 28 patients received NCHTT. Pathologic responses were assessed according to response evaluation criteria in solid tumors (RECIST) guidelines.

RESULTS

Pathologic complete response (pCR) was achieved in 13 out of 28 patients treated with NCHTT and in 6 out of 31 patients treated with NAC alone (46.4% vs. 19.4%, respectively, P = 0.049). Breast conserving surgery (BCS) was more frequently performed in the NCHTT group than in the NAC only group (71.4% vs. 19.4%, P < 0.001). The 3-year recurrence-free survival (RFS) rate was 100% in the NCHTT group and 76.4% in the NAC group (P = 0.014). Together, NCHTT, type of operation (BCS vs. mastectomy) and pathologic nodal status were significant prognostic factors for RFS in univariate analysis.

CONCLUSION

We found that NCHTT produced higher pCR rates than NAC alone in locally advanced breast cancer.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3184/3641366/8a0db4a779cc/jkss-84-273-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验