TITLE:
Usage of Cox-Regression Model for Forecasting of Survival Rate in Patients with the Early Stage of Non-Small Cell Lung Cancer
AUTHORS:
Oleksey P. Kolesnik, Anatoliy I. Shevchenko, Yuriy E. Lyakh, Vitaliy G. Gurianov, Pavel A. Alyoshechkin
KEYWORDS:
Forecasting Model; Survival Rate; Non-Small Cell Lung Cancer
JOURNAL NAME:
Advances in Lung Cancer,
Vol.3 No.1,
March
17,
2014
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.