Ghadimi Mahmood Reza, Rasouli Mahboobeh, Mahmoodi Mahmood, Mohammad Kazem
Candidate, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
J Res Med Sci. 2011 Oct;16(10):1261-72.
Esophageal 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.
In 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).
Of 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.
Since 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.
在全球范围内，食管癌是第八大常见癌症，也是癌症相关死亡的第六大主要原因。在伊朗，里海地区报告了这种癌症的高发病率。本研究旨在使用参数模型和半参数模型以及单变量伽马脆弱模型，评估里海周边省份食管癌患者生存的影响因素。
在本研究中，我们对1990年至1991年出现的359例食管癌患者进行了前瞻性回顾。数据是利用伊朗巴博尔研究中心现有的癌症登记信息获得的。研究参与者随访至2006年，为期15年。风险比用于解释死亡风险。赤池信息准则（AIC）被视为选择最佳模型的标准。
359例患者中，225例（62.7%）为男性，诊断时平均年龄为60.0岁；134例（37.3%）为女性，平均年龄为55.3岁。诊断后的1年、3年和5年生存率分别为23%、15%和13%。AIC的Cox模型和参数模型之间的比较表明，参数模型下的整体拟合得到了改善。在参数模型中，具有伽马脆弱性的对数逻辑模型比其他模型表现更好。使用该模型，我们发现性别（p = 0.012）和癌症家族史（p = 0.003）是显著的预测因素。
由于Cox模型的比例假设不成立（p = 0.01），Cox回归模型不是分析我们数据的合适选择。根据我们的研究结果，具有伽马脆弱性的对数逻辑模型可被视为食管癌患者生存分析中的一种有用统计模型，而非Cox模型和对数正态模型。
