Volume 28, Issue 161 (6-2018)                   J Mazandaran Univ Med Sci 2018, 28(161): 66-74 | Back to browse issues page

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Babanejhad F, Yazdani Charati J, Shbankhani B, Aliyannejhad R, Saber S, Ghasemkhani S. Survival Analysis of Patients with Lung Cancer Using Cox Regression Model . J Mazandaran Univ Med Sci. 2018; 28 (161) :66-74
URL: http://jmums.mazums.ac.ir/article-1-10630-en.html
Abstract:   (1310 Views)
Background and purpose: Lung cancer is the third cause of death and amongst the five common cancers in Iran. The aim of this study was to analyze the survival rate of patients with lung cancer and identifying the variables influencing their survival.
Materials and methods: In a retrospective cohort study, the data was extracted from the medical records of 259 patients with lung cancer who had attended Tehran Shariati Hospital during 2005-2015. The survival rate was estimated using the Kaplan-Meier method and log-rank test was applied for comparison of survival function. The event was specified as death due to lung cancer. The Cox’s proportional hazard model was used to investigate the effect of various variables on patient survival time using the R software.
Results: The mean age of the patients was 62.86±12.46 and the estimated median survival time was 2.4 years (2.93±3.33). Hundred and forty patients (54%) died. According to the Kaplan-Meier method, 1, 2, and 3 years survival rates were estimated to be 63%, 53%, and 46%, respectively. Based on Cox proportional hazards analysis, the patient’s survival time was significantly associated with PCO2 (HR= 1.021), age at diagnosis (HR= 0.805), type of tumor (NSCLC vs. SCLC) (HR= 0.567), and brain metastasis (HR= 1.792).
Conclusion: The survival time for patients with lung cancer was found to be quite short. This time decreases by increase in patients’ age. Also, the risk of death in a patient either with SCLC or metastasis was higher than other patients.
 
 
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Type of Study: Research(Original) | Subject: Biostatistics

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