Comput. Biol. Med. - Neural network analysis of employment history as a risk factor for prostate cancer.

Tópicos

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Resumo

CKGROUND: Prostate cancer is the most common non-cutaneous malignancy in men. Its etiology likely involves environmental exposures and demographic factors.OBJECTIVE: Investigate the potential relationship between occupation history and prostate cancer risk in a population-based, case-control study (n=1365).METHODS: The variables: race, age group, smoking status, income, marital status, education and the first 15 years of employment history were examined by sequential odds ratio analysis then compared to a neural network consensus model.RESULTS: Both the sequential odds ratio method and the neural network consensus model identified a similar hypothetical case of greatest risk: a Black, married man, older than 60 years, with at best a high school diploma who made between $25,000-$65,000. The work history determined by odds ratio analysis consisted of 10 years in the chemical industry with 3 yrs in the processing plant. Neural network analysis showed a similar work history with 8 years in the chemical industry and 2 years in the processing plant.DISCUSSION: Neural network outcomes are similar to sequential odds ratio calculations. This work supported previous studies by finding well known demographic risk factors for prostate cancer including certain processing jobs and chemical related jobs.

Resumo Limpo

ckground prostat cancer common noncutan malign men etiolog like involv environment exposur demograph factorsobject investig potenti relationship occup histori prostat cancer risk populationbas casecontrol studi nmethod variabl race age group smoke status incom marit status educ first year employ histori examin sequenti odd ratio analysi compar neural network consensus modelresult sequenti odd ratio method neural network consensus model identifi similar hypothet case greatest risk black marri man older year best high school diploma made work histori determin odd ratio analysi consist year chemic industri yrs process plant neural network analysi show similar work histori year chemic industri year process plantdiscuss neural network outcom similar sequenti odd ratio calcul work support previous studi find well known demograph risk factor prostat cancer includ certain process job chemic relat job

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