Determining Overall Survival and Risk Factors in Esophageal Cancer Using Censored Quantile Regression

Zarean, E and Mahmoudi, M and Azimi, T and Amini, P (2018) Determining Overall Survival and Risk Factors in Esophageal Cancer Using Censored Quantile Regression. Asian Pac J Cancer Prev, 19 (11).


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BACKGROUND: Esophageal cancer is one of the leading causes of death worldwide. The global increasing rate of this type of cancer requires more attention. The purpose of this study was to determine the overall survival probability of esophageal cancer after diagnosis and to assess the potential risk factors in a population of Iranian patients. MATERIALS AND METHODS: This retrospective cohort study was conducted on 127 cases with esophageal cancer in the Azarbaijan province, East of Iran. Participants in the study were diagnosed during 2009-2010 and were followed up for 5 years. The event was considered death due to esophageal cancer and those who survived until the end of the study were assumed as right censored. Censored quntile regression was fitted to find the overall survival of the patients using adjusted effects of variables and was compared with Cox regression model. RESULTS: Patients’ mean and median survival time were 16.99 and 10.06 months respectively and 89% off cases died by the end of the study. The 1, 3, 6, 12 and 36-month survival probabilities were 0.95, 0.76, 0.60, 0.43, and 0.18. The median survival time for females and males without surgery were 21.79 and 14.76 month respectively. The accuracy of predictions were 0.99 and 0.74 for the censored quantile regression and Cox, respectively. CONCLUSION: We concluded that being male, not having surgery, longer wait time between having symptoms and being diagnosed, low socioeconomic status and old age to be significant risk factors in reducing the probability of survival from esophageal cancer.

Item Type: Article
Uncontrolled Keywords: Esophageal cancer, survival analysis, risk factor
Subjects: QU Biochemistry
QZ pathology-Neoplasms
QV pharmacology
Divisions: Faculty of Medicine
Depositing User: Unnamed user with email
Date Deposited: 23 Dec 2018 06:03
Last Modified: 23 Apr 2019 08:46

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