Archive of Oncology (Jan 2003)
Complex analysis of lung cancer and stomach cancer risk factors
Abstract
BACKGROUND: We conducted a multifactorial cancer epidemiology case-control study to assess effects of a complex of factors on high cancer morbidity of population of an industrial town in the central part of Russia. The study was carried out in the town of Tula, one of the oldest industrial centers of Russia with a high occupational and industrial load on the population and a high cancer incidence rate exceeding the Russian average rates by 38.4% in men and 89.9% in women. METHODS: We examined 200 lung cancer cases, 206 stomach cancer cases, and 213 controls, all residents of Tula. On each of the 619 study participants we collected personal data, which allowed characterization of cases and controls by a complex of 29 features reflecting well-known lung and stomach cancer risk factors. Mathematical processing was performed using the technique of multifactorial analysis based on mathematical pattern recognition methods. All tasks were solved in the package of applied programs of pattern recognition KVAZAR. RESULTS: The results of the multifactorial analysis of epidemiological data collected showed that the contribution of smoking in the development of stomach cancer in Tula was 7%, alcohol abuse 4%, occupational exposure to carcinogens 12% a complex of individual biological factors 28%, environmental factors 22% radiation factors 5%, nutrition habits 10%, and other factors 12%. The contribution of smoking in lung cancer mortality was 27%, alcohol abuse 4% occupational exposure to carcinogens 14%, a complex of individual biological factors 32%, environmental factors 9%, radiation factors 7%, and other factors 7%. CONCLUSION: The results of the epidemiological study carried out on the basis of methods of a multifactorial analysis in the city of Tula Russia, showed the effectiveness of such an approach to solving complicated epidemiological tasks. The suggested method allows one to assess a complex effect of different factors on oncologic morbidity in an industrial town and the prediction of effectiveness of various cancer preventive measures facilitates the choice of the most effective complex of preventive actions on the certain territory and at low cost.
Keywords
