Evidence map›Paper›PMID 22973319›Full record

ArticleJournal of research in medical sciences : the official journal of Isfahan University of Medical Sciences2011

Prognostic factors for the survival of patients with esophageal cancer in Northern Iran.

Mahmood Reza Ghadimi, Mahboobeh Rasouli, Mahmood Mahmoodi, Kazem Mohammad

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Article in Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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4 authors.

Mahmood Reza GhadimiCandidate, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mahboobeh Rasouli
Mahmood Mahmoodi
Kazem Mohammad

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEsophageal cancer is the 8(th) most common cancer and the 6(th) leading cause of cancer-related death, worldwide. In Iran, the high incidence rates of this type of cancer have been reported from the Caspian Sea region. This study aimed at assessing the factors affecting survival of patients with esophageal cancer in neighbor provinces around Caspian Sea using parametric and semi-parametric models with univariate gamma frailty model.

methodsIn this study, we performed a prospective review of 359 patients presenting with esophageal cancer from 1990 to 1991. The data were obtained using the Cancer Registry information existed in Babol research center in Iran. Study participants were followed-up until 2006 for a period of 15 years. Hazard ratio was used to interpret the risk of death. The Akaike Information Criterion (AIC) was considered as a criterion to select the best model(s).

resultsOf the 359 patients, 225 (62.7%) were male with a mean age of 60.0 years and 134 (37.3%) were female with a mean age of 55.3 at the time of diagnosis. 1- , 3- and 5-year survival rates after diagnosis were 23%, 15% and 13% , respectively. Comparison between Cox and parametric models of AIC showed that the overall fitting was improved under parametric models. Among parametric models, the log-logistic model with gamma frailty provided better performance than other models. Using this model, we found that gender (p=0.012) and family history of cancer (p= 0.003) were significant predictors.

conclusionsSince the proportionality assumption of the Cox model was not held (p = 0.01), the Cox regression model was not an appropriate choice for analyzing our data. According to our findings, log logistic model with gamma frailty could be considered as a useful statistical model in survival analysis of patients with esophageal cancer rather than Cox and log-normal models.

Indexed as

Esophageal CancerParametric ModelSurvival AnalysisUnivariate Gamma Frailty Model

Identifiers

PMID22973319
PMCPMC3430015

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