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Asian Pac J Cancer Prev. 2013;14(11):6369-73.

Survival analysis of patients with gastric cancer undergoing surgery at the iran cancer institute: a method based on multi-state models.

Author information

  • 1Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Iran E-mail : mahmoodim@tums.ac.ir.

Abstract

BACKGROUND:

Gastric cancer is one of the most common causes of cancer deaths all over the world and the most important reason for its high rate of death is its belated diagnosis at advanced stages of the disease. Events occur in patients which are regarded not only as themselves factors affecting patients' survival but also which can be affected by other factors. This study was designed and implemented aiming to identify these events and to investigate factors affecting their occurrence.

MATERIALS AND METHODS:

Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995-1999 were analyzed. The survival time of these patients was determined after surgery and the effects of various factors including demographic, diagnostic and clinical as well as medical, and post-surgical varuiables on the occurrence of death hazard without relapse, hazard of relapse, and death hazard with a relapse were assessed.

RESULTS:

The median survival time for these patients was 16.3 months and the 5-year survival rate was 21.6%. Based on the results of multi-state model, age and distant metastases affected relapse whereas disease stage, type and extent of surgery, lymph nodes metastases, and number of renewed treatments affected death hazard without relapse. Moreover, age, type and extent of surgery, number of renewed treatments, and liver metastases were identified as factors affecting death hazard in patients with relapse.

CONCLUSIONS:

Most cancer studies pay heed to factors which have effect on death occurrence, but some events occur which should be taken into consideration to better describe the natural process of the disease and provide researchers with more accurate data.

PMID:
24377534
[PubMed - indexed for MEDLINE]
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