Individual prognosis of urolithiasis, benign hyperplasia and prostate cancer development based on medical and social risk factors

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Abstract

Aim. To predict the risk of developing urolithiasis, benign hyperplasia and prostate cancer on the basis of mathematical modeling on individual medical and social factors. Methods. Prognostic evaluation of the risk of studied pathology development based on 30 medical and social factors was performed. Representive samples of patients with verified diagnosis of urolithiasis, benign prostatic hyperplasia and prostate cancer (study groups) as well as individuals without these diseases (comparison group) constituted the material of the study. The study protocol included preparation of primary data, transformation of qualitative data into numerical form, logistic regression modeling of risk, verification of models. Risk prediction itself was performed with the use of reasonably chosen methods of mathematical modeling (a priori ranging, regression analysis and discrete correlation pleiades aimed at minimizing the informative parameter redundancy). The developed models were verified by passive experiment method. Results. Based on long-term empirical observation the scientific hypothesis was proposed that urolithiasis, benign hyperplasia and prostate cancer development is more probable in patients with certain risk factors. To prove or reject the proposed hypothesis, the analysis of prognostic informativeness was performed for 30 factors suspected to cause the studied pathology development. It was performed with the use of logistic regression models. As a result among the studied working and living conditions of urological patients prognostically significant factors were determined. Developed on their basis (and subsequently verified) models allowed mathematically evaluating real risk of the studied urologic diseases development. Conclusion. Development of the models of individual risk of the studied nosologic forms development based on the analysis of medical and social factors is principally possible; verification of the developed models confirms their practical applicability and proves the principal feasibility of the proposed approach.

About the authors

O V Zolotukhin

Voronezh State Medical University named after N.N. Burdenko

Email: zolotuhin-o@yandex.ru
Voronezh, Russia

References

  1. Гублер Е.В. Вычислительные методы распознавания патологических процессов. Ленинград: Медицина. 1970; 319 с.
  2. Гланц С. Медико-биологическая статистика. М.: Практика. 1999; 459 с.
  3. Реброва О.Ю. Статистический анализ медицинских данных: применение пакета прикладных программ STATISTICA. М.: МедиаСфера. 2002; 312 с.
  4. Дюк В.Э. Информационные технологии в медико-биологических исследованиях. СПб.: Питер. 2003; 528 с.
  5. Медик В.А., Токмачев М.С. Математическая статистика в медицине. М.: Финансы и статистика. 2007; 800 с.
  6. Халафян А.А. Statistica 6. Статистический анализ данных. М.: Бином-Пресс. 2008; 512 с.
  7. Чопоров О.Н., Золотухин О.В., Болгов С.В. Алгоритмизация интеллектуального анализа данных о распространённости заболеваний на региональном и муниципальном уровнях. Моделирование, оптимизация и информационные технологии. 2015; (9). http://moit.vivt.ru/wpcontent/uploads/2015/06/ChoporovZolotuhinBoglov_2_15_1.pdf (дата обращения: 08.05.2017).
  8. Чопоров О.Н., Болгов С.В., Манакин И.И. Особенности применения методов интеллектуального анализа данных и многоуровневого мониторинга при решении задачи рационализации медицинской помощи. Моделирование, оптимизация и информационные технологии. Воронеж. 2015; 8 (1). http://moit.vivt.ru/wp-content/uploads/2015/04/ChoporovBolgovManakin%20_1_15_1.pdf (дата обращения: 08.05.2017).
  9. Колесов Ю.Б., Сениченков Ю.Б. Моделирование систем. Объектно-ориентированный подход. СПб.: БХВ-Петербург. 2012; 185 с.
  10. Юнкеров В.И., Григорьев С.Г. Математико-статистическая обработка данных медицинских исследований. СПб.: ВМедА. 2002; 266 с.

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