ArticleWorld journal of gastroenterology2005
Quantitative assessment model for gastric cancer screening.
Article in World journal of gastroenterology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 3 citations in OpenAlex.
- Risk assessment models to estimate cancer probabilities.Current oncology reports · 2007Review
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4 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
aimTo set up a mathematic model for gastric cancer screening and to evaluate its function in mass screening for gastric cancer.
methodsA 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).
resultsBased 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).
conclusionThe validity of this method is satisfactory. It is convenient, feasible, economic and can be used to determine individual and population risks of gastric cancer.
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