1Sira O. V.,
2Kirkilevsky S. I.,
3,5Tkachenko O. I.,
3Dubinina V. G.,
2,3,4Mashukov A. A.,
3,4Bilenko A. A.,
3,4Merlich S. V.,
5Maksimovsky V. E.,
4Zgura A. N.,
4Ratsiborsky D. V.,
4Shilin I. V.,
4Sirbu V. N.,
4Boychenko A. I.
1Ukraine, Kharkiv, NTU Kharkiv National Technical University «Kharkov Polytechnic
Institute», Department of Distributed Information Systems and Cloud Technologies;
2Ukraine, Kiev, National Institute of Cancer, Research Department of tumors of the chest cavity;
3Ukraine, Odessa, Odessa National Medical University;
4Ukraine, Odessa, KU «Odessa Regional Oncology Center», Department of abdominal oncology;
5Ukraine, Odessa, Odessa National Medical University, Center of Reconstructive and
The purpose of this work was to find ways to predict the survival of gastric cancer patients. The study included 221 patients who were radically operated in the abdominal department of the Odessa Regional Oncology Center from 2007 to 2013. The life expectancy of this group of patients was measured in months. From the factors given in the article, only the age of the patient, the presence and invasion in neighboring organs and the number of organs resected during the operation were those factors that had a significant impact on the prognosis. A formula was obtained for the formal evaluation of the duration of patients. The results are preliminary. Conclusions. As a result of the regression analysis, a polynomial (formula) was obtained, which can be used to predict the survival of patients who underwent surgery for gastric cancer. There is a need to create clearer gradations of survival dependencies of cancer patients from different clinical and morphological situations. A mathematical apparatus with many variables can be used to create similar models for the analysis of survival in other types of pathology.
Keywords: stomach cancer, mathematical formula, immunohistochemistry, survival.
1. STATISTICA 6. Статистический анализ данных. Второе издание. М.: Бином, 2009.
Халафян А. А. ГЛАВА 14 Анализ выживаемости.
2. A Prognostic Model to Predict Mortality among Non-Small-Cell Lung Cancer Patients in
the U.S. Military Health System. Lin J, Carter CA, McGlynn KA, Zahm SH, Nations JA, Anderson WF, Shriver CD, Zhu K. J Thorac Oncol. 2015 Dec;10(12):1694-702. doi: 10.1097/JTO.0000000000000691. PMID:26473644.
3. Development of individual survival estimating program for cancer patients’ management.
Chang MC.Healthc Inform Res. 2015 Apr;21(2):134-7. doi: 10.4258/hir.2015.21.2.134. Epub 2015
Apr 30. PMID:25995966.
4. A new scoring system for predicting survival in patients with non-small cell lung cancer.
Schild SE, Tan AD, Wampfler JA, Ross HJ, Yang P, Sloan JA. Cancer Med. 2015 Sep;4(9):1334-43. doi: 10.1002/cam4.479. Epub 2015 Jun 23. PMID: 26108458.