Factors Predicting Effectiveness of Neoadjuvant Therapy for Esophageal Squamous Cell Carcinoma

Yu Ohkura, Masaki Ueno, Toshiro Iizuka, Shusuke Haruta, Tsuyoshi Tanaka, Harushi Udagawa

研究成果: Article査読

3 被引用数 (Scopus)

抄録

The aim of the study was to elucidate pretreatment factors that can predict the outcome of neoadjuvant chemoradiotherapy or chemotherapy (NAC(R)T) and help us choose treatment strategies appropriate for individual patients. Few studies have investigated whether clinical data obtainable before the treatment can predict the efficacy of NAC(R)T. Of 1540 patients treated for esophageal squamous cell carcinoma (ESCC) at our department between January 2000 and June 2014, those who underwent surgical resection of cStage II or more advanced ESCC after NAC(R)T (113 NACRT and 146 NACT patients) were enrolled in this study. Information all available before the treatment was analyzed to extract factors that can predict the effectiveness of NAC(R)T. NAC(R)T was considered effective when Grade 2 or greater treatment efficacy was achieved based on the histological grading system. NACRT was effective in 51 (45%) of 113 patients. The analysis of 35 pretreatment factors showed that female sex (hazard ratio [HR]=3.650; 1.181-11.236), absence of dyslipidemia (HR=3.284; 1.341-8.041), and histologically poorly differentiated tumor (HR=2.431; 1.052-5.619) were factors predicting NACRT effectiveness. On the other hand, NACT was effective in 21 (14%) of 146 patients. The analysis of pretreatment factors showed that absence of dyslipidemia (HR=10.204; 1.302-83.33) and therapy with docetaxel, cisplatin, and 5-fluorouracil (HR=2.097; 1.027-4.280) were factors predicting NACT effectiveness. The findings of this study investigating factors that could predict the outcome of NAC(R)T suggest that the prevalence of dyslipidemia influences the outcome of NAC(R)T for ESCC.

本文言語English
論文番号e3365
ジャーナルMedicine (United States)
95
15
DOI
出版ステータスPublished - 01-04-2016
外部発表はい

All Science Journal Classification (ASJC) codes

  • 医学(全般)

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