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Survival prediction of gastric cancer patients by Artificial Neural Network model

Jamshid Yazdani Charati, Ghasem Janbabaei, Nadia Alipour, Soraya Mohammadi, Somayeh Ghorbani Gholiabad, Afsaneh Fendereski




Aim: This study aims to predict survival rate of gastric cancer patients and identify the effective factors related to it, using artificial
neural network model.
Background: Gastric cancer is the most deadly disease in north and northeast provinces of Iran. A total of 430 patients with gastric
cancer who referred to Baghban clinic in Sari, from early November 2006 to late October 2013 were followed.
Methods: A historical cohort of patients who referred to Baghban Clinic, the cancer research center of Mazandaran University of
Medical Sciences in Sari, from early November 2006 to late October 2013 was studied. Three groups of variables (demographic,
biological and socio-economic) were studied. Survival rate and effective factors on survival time were calculated using Kaplan-Meier
methods and artificial neural networks and the best network structure were chosen using the mean square error and ROC curve. All
analyses were performed using SPSS v.18.0 and the level of significance was selected ?=0.05.
Results: In this research, the median survival time was 19±2.04 months. The 1 to 5-year survival rates for patients were 0.64, 0.44,
0.34, 0.24 and 0.19, respectively. The percentage of right predictions of the selected network and the area under the ROC curve were
92% and 94%, respectively. According to the results, the type of treatment, metastasis, stage of disease, histology grade, histology type
and the age of diagnosis were effective factors on survival period.
Conclusion: the 5 years survival rate of gastric cancer patients in Mazandaran is lower than other provinces which could be due to the
delay in diagnosis or patient’s referral. Therefore, the use of screening methods and early diagnosis could be influential for improving
survival rate of these patients.
Keywords: Gastric cancer, Survival analysis, Artificial neural network.
(Please cite as: Yazdani Charati J, Janbabaei G, Alipour N, Mohammadi S, Ghorbani Gholiabad S, Fendereski A.
predicting survival of gastric cancer patients by Artificial Neural Network model. Gastroenterol Hepatol Bed Bench




Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA: a

cancer journal for clinicians. 2005 Mar;55(2):74-108. Doi: 10.3322/canjclin.55.2.74.

International Agency for Research on Cancer. All Cancers (excluding nonmelanoma skin cancer) Estimated Incidence, Mortality and Prevalence Worldwide in 2012 [Online]. [cited 2012]; Available from: URL: http://globocan.iarc.fr/Pages/fact_sheets_cancer. aspx. 2015.

Malekzadeh R, Derakhshan MH, Malekzadeh Z. Gastric Cancer in Iran: Epidemiology and Risk Factors. Arch Iran Med. 2009 Nov; 12(6): 576-83 (Persian).

Kolahdoozan S, Sadjadiet A, Radmard AR, Khademi H. Five common cancers in Iran. Arch Iran Med. 2010 Mar; 13(2): 143-6 (Persian).

Kavousi A, Bashiri Y, Mehrabi Y, Etemad K. Modeling High-Risk Areas for Gastric Cancer in Men and Women, 2005-2009. J Isfahan Med Sch 2015; 33(322): 82-92. (Persian).

Hagan MT, Neural network design, PWS, USA; 1995.

Kutner MH, Nachtsheim CJ. and Neter J. Applied linear regression models,4th ed. New York: McGraw-Hill/Irwin; 2004.

Lee ET. and Wang JW. Statistical Methods for Survival Data Analysis, 3rd ed. John Wiley & Sons, Inc, Hoboken, New Jersey: 2003 Aug.

Anderson J.A. An Introduction to Neural Networks. Cambridge, MA: MIT Press, 1995: p. 795-851.

Warner B. and Misra M. Understanding neural networks as statistical tools. Am Stat 1996 Nov; 50(4): 284-293. Doi:10.1080/00031305.1996.10473554

Kay JW, Titterington DM. Statistics and neural networks: advances at the interface. Oxford University Press on Demand; 1999,75-103..

Livingstone DJ. Artificial Neural Networks: Methods and Applications (Methods in Molecular Biology). Humana Press; 2008 Oct.

Yzdanbod A, Samadi F, Malekzadeh R, Babaei M, Azami A, Iranparvar M. Four-year survival rate of patients with upper gastrointestinal cancer in Ardabil. Ardabil University of Medical Sciences 2005; 5(2): 180-4 (Persian).

Moghimi-dehkordi B, Rajayi-fard A, Tabatabaee H, Zeighami B, Safaee A, Tabei Z. Modeling Survival Analysis in Gastric Cancer Patients Using the Proportional Hazards Model of Cox cancer. Iranian Journal of Epidemiology 2007; 3(1): 19-24 (Persian).

Hajian K, Firouzjahi AR, Kia M. Pattern of Age Distribution of Different Cancers Babol, 2001. Pejouhesh 2003; 27(3): 239-45 (Persian).

Hashemi SM, Hagh-Azali M, Bagheri M, Kabir A. Histopathologic and Anatomic Correlation of Primary Gastric Cancers. Razi Journal of Medical Sciences. 2004;11(40):319-26. (Persian).

Sadighi S, Raafat J, Mohagheghi M, Meemary F. Gastric carcinoma: 5 year experience of a single institute. Asian Pac J Cancer Prev. 2005;6(2):195-6. (Persian).

Biglarian A, Hajizadeh E, Kazemnejad A, Mohammad R. Postoperative Survival Prediction in Patients with Gastric Cance. Daneshvar Medicine 2009; 16(81): 55-62 (Persian).

Yazdani J, Sadeghi S, Janbabaei GH, Haghighi F, et al. Applying Survival Analysis to Estimate Survival Time in Gastric Cancer Patients. J Mazand Univ Med Sci 2011; 21(85): 28-36 (Persian).

Khedmat H, Panahian M, Amini M, Izadi M. Armed forces and other official personnel survival of patients with gastric cancer were admitted in the hospital's Baqiatallah Azam. Journal of Military Medicine. 2007;9(3):167-77. (Persian).

Zeraati H, Mahmoudi M, Kazemnejad A, Mohammad K. Postoperative survival in gastric cancer patients and its associated factors: A time dependent covariates model. Iranian J Publ Health. 2006 Jan;35(3):40-6. (Persian).

Esmaeili H. Comparison of survival of patients with cancers of the esophagus and stomach, and the characteristics of the cancer in Mazandaran province. Master's thesis of Biostatistics, School of Medicine. University of Tarbiat Modarres 1994. (Persian).

Landry J, Tepper JE, Wood WC, Moulton EO, Koerner F, Sullinger J. Patterns of failure following curative resection of gastric carcinoma. International Journal of Radiation Oncology Biology Physics. 1990 Dec;19(6):1357-62. Doi:10.1016/0360-3016(90)90344-J

Tian J, Wang XD, Chen ZC. Survival of patients with stomach cancer in Changle city of China. World journal of gastroenterology: World J Gastroenterol. 2004 Jun;10(11):1543-6.Doi: 10.3748/wjg.v10.i11.1543

Desai AM, Pareek M, Nightingale PG, Fielding JW. Improving outcomes in gastric cancer over 20 years. Gastric cancer. 2004 Dec;7(4):196-203. Doi:10.1007/s10120-004-0289-0.

Biglarian A, Hajizadeh E, Kazemnejad A, Zali M. Survival analysis of gastric cancer patients using Cox model: a five year study. Tehran University of Medical Sciences. 2009 Jan 1;67(5). 317-25 (Persian).

Wiseman M. The second World Cancer Research Fund/American Institute for Cancer Research expert report.Food, nutrition, physical activity, and the prevention of cancer: a global perspective. Proc Nutr Soc 2008; 67(3):253-6. Doi: https://doi.org/10.1017/S002966510800712x

Tsugane S. Salt, salted food intake and risk of gastric cancer: epidemiologic evidence. Cancer Sci 2005; 96(1): 1-6 Doi: 10.1111/j.1349-7006.2005.00006.x.

Tsugane S, Sasazuki S. Diet and the risk of gastric cancer: review of epidemiological evidence. Gastric Cancer 2007; 10(2): 75-83. Doi:https://doi.org/10.1007/s10120-007-0420-0

Honsson L, Sparen P, Nyren O. Survival in stomach cancer is improving: results of a nationwide population-based Swedish study. Annals of surgery. 1999 Aug;230(2):162-169.

DOI: https://doi.org/10.22037/ghfbb.v0i0.1246