Suppr超能文献

Changes in tumor marker levels as a predictor of chemotherapeutic effect in patients with gastric carcinoma.

作者信息

Nakata B, Chung K H, Muguruma K, Yamashita Y, Inoue T, Matsuoka T, Onoda N, Kato Y, Sakurai M, Sowa M

机构信息

First Department of Surgery, Osaka City University Medical School, Osaka, Japan.

出版信息

Cancer. 1998 Jul 1;83(1):19-24.

PMID:9655288
Abstract

BACKGROUND

Evaluating chemotherapeutic effect in patients with gastric carcinoma sometimes is difficult. The authors investigated whether changes in the serum levels of three tumor markers can be used to predict the clinical outcome after chemotherapy.

METHODS

Thirty patients with advanced and recurrent gastric carcinoma were treated with continuous 5-fluorouracil and low dose cisplatin for 4 weeks. Thirteen patients were treated neoadjuvantly prior to gastrectomy. The serum levels of carcinoembryonic antigen, carbohydrate antigen 19-9, and sialyl-Tn antigen were measured prior to and after chemotherapy. Responders were defined as those in whom abnormal serum levels of all three markers decreased to at least 50% of the pretreatment values and remained stable for at least 1 month.

RESULTS

The tumor markers could be evaluated in 27 of 30 patients (90%). The median duration of survival for the 15 responders and 12 nonresponders was 17 months and 6 months, respectively. There was a significant difference in the median duration of survival between the responders and nonresponders using the log rank test (P=0.0005). In the patients who received neoadjuvant therapy, the eight responders had a significantly longer survival period than did the three nonresponders (P=0.018). Seven of the eight responders showed evidence of tumor destruction histologically whereas none of the three nonresponders did.

CONCLUSIONS

Changes in the serum levels of these tumor markers after chemotherapy may be an excellent prognostic indicator for patients with gastric carcinoma.

摘要

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