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Usage of Cox-Regression Model for Forecasting of Survival Rate in Patients with the Early Stage of Non-Small Cell Lung Cancer

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DOI: 10.4236/alc.2014.31004    3,940 Downloads   6,900 Views  

ABSTRACT

In the past decades a lot of investigations were focused on searching for more accurate markers of lung cancer progression. Researchers indicate that molecular markers may be useful in forecasting of treatment outcome and overall survival rate in patients with non-small cell lung cancer. The aim of our research was to create a forecasting model in order to identify patients with stage I-II of non-small cell lung cancer and dismal prognosis. Our research covered 254 patients with the early stage of non-small cell lung cancer who underwent a cure from June 2008 till December2012 inthe Department of Thoracic Surgery of Zaporizhzhia Regional Clinical Oncologic Dispensary. Surgery was performed for all patients. Adjuvant chemotherapy was performed for 101 patients. In order to carry out multivariate Cox-regression analysis, STATISTICA 6.0 (StatSoft Inc.) program was used. The most significant from 39 variables were selected (tumor size, histological form of tumor, volume of surgical intervention, volume of conducted lymph node dissection, Ki-67 expression, EGFR expression, E-cadherin expression). We propose the computer system which can forecast survival rate in patients with the early stage of non-small cell lung cancer.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Kolesnik, O. , Shevchenko, A. , Lyakh, Y. , Gurianov, V. and Alyoshechkin, P. (2014) Usage of Cox-Regression Model for Forecasting of Survival Rate in Patients with the Early Stage of Non-Small Cell Lung Cancer. Advances in Lung Cancer, 3, 26-33. doi: 10.4236/alc.2014.31004.

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