[Recognition of the factors affecting survival in colon and rectal cancer patients referred to RCGLD center of Shahid Beheshti university of medical sciences: accelerated failure time parametric survival analysis with Frailty]

ABSTRACT

Different diagnostic factors of colon and rectal cancer [CRC] affect the survival of patients, prognosis and consequently treatment application. The rate of colorectal cancer is being increased in Iran, especially in younger ages, made it more valuable to study this type of cancer. However, evaluation of the risk factors of the cancer as a whole would not provide thorough understanding of the cancer. Therefore, the aim of this study was to determine specific risk factors affecting colon and rectum cancers. A total of 1219 patients with CRC diagnosis, according to the pathology report of cancer registry of RCGLD from 1 January 2002 to 1 October 2007, were entered into the study. Data were analyzed using univariate and multivariate Accelerated Failure Time [AFT] parametric survival model with frailty, utilizing STATA statistical software. Based on the results of this analysis, for colon cancer, females, patients without inflammatory bowel disease [IBD], patients with poorly differentiated tumor grade and patients pathologic with stage of I had higher survival probability. For these patients, there was not any correlation between history of alchol consumption and the size tumor. In the rectal cancer, patients with surgery as the kind of first treatment used, had higher survival probability. For these patients personal history and pathologic stage weren't statistically significant. In addition, in both types of cancers, 25-29.9 and over than 30 categories of body mass index [BMI] had higher survival probability, respectively and patients with BMI less than 18.5 had lower survival probability. In general, the survival rate in rectal cancer patients was higher than those with colon cancer. Site-specific evaluation of colon and rectum can lead to a deeper understanding of factors affecting these cancers. It may help design the clinical trials, better diagnosis of diseases and optimal administration of specific treatments