Gastric Cancer
Copyright ©2005 Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Feb 7, 2005; 11(5): 641-644
Published online Feb 7, 2005. doi: 10.3748/wjg.v11.i5.641
Quantitative assessment model for gastric cancer screening
Kun Chen, Wei-Ping Yu, Liang Song, Yi-Min Zhu
Kun Chen, Wei-Ping Yu, Liang Song, Yi-Min Zhu, School of Medicine, Zhejiang University, Hangzhou 310031, Zhejiang Province, China
Author contributions: All authors contributed equally to the work.
Supported by National Nature Science Foundation of China, No.30170828
Correspondence to: Kun Chen, M.D., Department of Epidemiology, School of Medicine, Zhejiang University, 353 Yan-an Road, Hangzhou 310031, Zhejiang Province, China. ck@zjuem.zju.edu.cn
Telephone: +86-571-87217190 Fax: +86-571-87217184
Received: March 3, 2004
Revised: March 7, 2004
Accepted: April 13, 2004
Published online: February 7, 2005
Abstract

AIM: To set up a mathematic model for gastric cancer screening and to evaluate its function in mass screening for gastric cancer.

METHODS: A case control study was carried on in 66 patients and 198 normal people, then the risk and protective factors of gastric cancer were determined, including heavy manual work, foods such as small yellow-fin tuna, dried small shrimps, squills, crabs, mothers suffering from gastric diseases, spouse alive, use of refrigerators and hot food, etc. According to some principles and methods of probability and fuzzy mathematics, a quantitative assessment model was established as follows: first, we selected some factors significant in statistics, and calculated weight coefficient for each one by two different methods; second, population space was divided into gastric cancer fuzzy subset and non gastric cancer fuzzy subset, then a mathematic model for each subset was established, we got a mathematic expression of attribute degree (AD).

RESULTS: Based on the data of 63 patients and 693 normal people, AD of each subject was calculated. Considering the sensitivity and specificity, the thresholds of AD values calculated were configured with 0.20 and 0.17, respectively. According to these thresholds, the sensitivity and specificity of the quantitative model were about 69% and 63%. Moreover, statistical test showed that the identification outcomes of these two different calculation methods were identical (P>0.05).

CONCLUSION: The validity of this method is satisfactory. It is convenient, feasible, economic and can be used to determine individual and population risks of gastric cancer.

Keywords: Gastric cancer, Mass screening, Quantitative assessment model