Volume 15, Issue 2 (June-July 2012)
J Arak Uni Med Sci 2012, 15(2): 84-92 |
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Maroufizadeh S, Hajizadeh E, Baghestani A R, Fatemi S R. Determining the postoperative survival in patients with gastric cancer and the associated factors using Cox and Lin-Ying additive hazards models. J Arak Uni Med Sci 2012; 15 (2) :84-92
URL: http://jams.arakmu.ac.ir/article-1-1045-en.html
URL: http://jams.arakmu.ac.ir/article-1-1045-en.html
1- Tarbiat Modares University
2- Tarbiat Modares University ,hajizadeh@modares.ac.ir
3- Islamic Azad University - South Tehran Branch
4- Shahid Beheshti University of Medical Sciences
2- Tarbiat Modares University ,
3- Islamic Azad University - South Tehran Branch
4- Shahid Beheshti University of Medical Sciences
Abstract: (12625 Views)
Background: Gastric cancer is a common and lethal disease throughout the world. This study was designed and carried out to determine the five-year survival rate of gastric cancer patients who had undergone surgical treatment at Taleghani Hospital of Tehran, and to assess its associated factors. Materials and Methods: In this historical-cohort study, information obtained from a total of 213 gastric cancer patients who underwent surgery at Taleghani Hospital of Tehran between 2003 and 2008 was included. In the analyses, Kaplan-Meier method, log-rank test, Cox proportional hazards model, and Lin-Ying additive hazards model were used. Results: The five-year survival rate and the median life expectancy in the studied patients were 14.6% and 29.6 months, respectively. Two covariates showed significant impacts on the gastric cancer patients’ data in both models: age at diagnosis and tumor size. We found that pathologic stage was significant under the Lin-Ying model (P=0.043) however, it was not significant under the Cox model (P=0.069). Other clinicopathological characteristics were not statistically significant (P>0.05). Conclusion: Since Cox and Lin-Ying models consider different aspects of the association between risk factors and the study outcome, it seems desirable to use both of them as complementary models but not as alternative models to obtain a more comprehensive understanding of data. This study showed that the early detection of patients in younger ages and in primary stages is important to decrease the risk of death in patients with gastric cancer and to increase the survival rate.
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