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使用脆弱模型研究伊朗北部胃肠道癌症患者的癌症家族史对其生存的影响。

Family history of the cancer on the survival of the patients with gastrointestinal cancer in northern Iran, using frailty models.

机构信息

Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Iran.

出版信息

BMC Gastroenterol. 2011 Oct 1;11:104. doi: 10.1186/1471-230X-11-104.

DOI:10.1186/1471-230X-11-104
PMID:21961837
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3217861/
Abstract

BACKGROUND

Gastrointestinal (GI) tract cancer is one of the common causes of the mortality due to cancer in most developing countries such as Iran. The digestive tract is the major organ involved in the cancer. The northern part of the country, surrounded the Caspian Sea coast, is well known and the region with highest regional incidence of the GI tract cancer. In this paper our aim is to study the most common risk factors affecting the survival of the patients suffering from GI tract cancer using parametric models with frailty.

METHODS

This research was a prospective study. Information of 484 cases with GI cancer was collected from Babol Cancer Registration Center during 1990-1991. The risk factors we studied are age, sex, family history of cancer, marital status, smoking status, occupation, race, medication status, education, residence (urban, rural), type of cancer, migration status (indigenous, non-native). The studied cases were followed up until 2006 for 15 years. Hazard ratio was used to interpret the death risk. The effect of the factors in the study on the patients survival are studied under a family of parametric models including Weibull, Exponential, Log-normal, and the Log-logistic model. The models are fitted using with and without frailty. The Akaike information criterion (AIC) was considered to compare between competing models.

RESULTS

Out of 484 patients in the study, 321 (66.3%) were males and 163 (33.7%) were females. The average age of the patient at the time of the diagnosis was 59 yr and 55 yr for the males and females respectively. Furthermore, 359 (74.2%) patients suffered from esophageal, 110 (22.7%) patients recognized with gastric, and 15 (3.1%) patients with colon cancer. Survival rates after 1, 3, and 5 years of the diagnosis were 24%, 16%, and 15%, respectively. We found that the family history of the cancer is a significant factor on the death risk under all statistical models in the study. The comparison of AIC using the Cox and parametric models showed that the overall fitting was improved under parametric models (with and without frailty). Among parametric models, we found better performance for the log-logistic model with gamma frailty than the others. Using this model, gender and the family history of the cancer were found as significant predictors.

CONCLUSIONS

Results suggested that the early preventative care for patients with family history of the cancer may decrease the risk of the death in the patients with GI cancer. The gender appeared to be an important factor as well so that men experiencing lower risk of death than the women in the study. Since the proportionality assumption of the Cox model was not held (p = 0.0014), the Cox regression model was not an appropriate choice for analysing our data.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/9eabc4f011bf/1471-230X-11-104-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/6efdbadce558/1471-230X-11-104-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/9f5d93d63499/1471-230X-11-104-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/9eabc4f011bf/1471-230X-11-104-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/6efdbadce558/1471-230X-11-104-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/9f5d93d63499/1471-230X-11-104-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/24f9/3217861/9eabc4f011bf/1471-230X-11-104-3.jpg
摘要

背景

在大多数发展中国家,如伊朗,胃肠道(GI)癌症是导致癌症死亡的常见原因之一。消化道是癌症主要涉及的器官。该国北部,环绕里海海岸,是众所周知的,也是胃肠道癌症发病率最高的地区。在本文中,我们的目的是使用带有脆弱性的参数模型研究影响胃肠道癌症患者生存的最常见风险因素。

方法

这是一项前瞻性研究。1990-1991 年间,我们从巴博勒癌症登记中心收集了 484 例胃肠道癌症患者的信息。我们研究的风险因素包括年龄、性别、癌症家族史、婚姻状况、吸烟状况、职业、种族、用药状况、教育程度、居住地(城市、农村)、癌症类型、移民状况(本土、非本土)。对研究病例进行了 15 年的随访,截至 2006 年。风险比用于解释死亡风险。在包括威布尔、指数、对数正态和对数逻辑模型在内的参数模型家族中研究研究因素对患者生存的影响。使用带有和不带有脆弱性的模型进行拟合。采用赤池信息量准则(AIC)比较竞争模型。

结果

在研究的 484 例患者中,321 例(66.3%)为男性,163 例(33.7%)为女性。患者诊断时的平均年龄为 59 岁,男性和女性分别为 55 岁。此外,359 例(74.2%)患者患有食管癌,110 例(22.7%)患者患有胃癌,15 例(3.1%)患者患有结肠癌。诊断后 1、3 和 5 年的生存率分别为 24%、16%和 15%。我们发现,在研究中的所有统计模型中,癌症家族史是死亡风险的一个重要因素。使用 Cox 和参数模型的 AIC 比较表明,参数模型(带有和不带有脆弱性)的整体拟合得到了改善。在参数模型中,我们发现带有伽马脆弱性的对数逻辑模型表现更好。使用该模型,发现性别和癌症家族史是显著的预测因子。

结论

结果表明,对有癌症家族史的患者进行早期预防保健可能会降低胃肠道癌症患者的死亡风险。性别也是一个重要因素,与女性相比,男性的死亡风险较低。由于 Cox 模型的比例假设不成立(p=0.0014),因此 Cox 回归模型不是分析我们数据的合适选择。

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BMC Cancer. 2008 May 14;8:137. doi: 10.1186/1471-2407-8-137.
2
Host and environmental factors for gastric cancer in Babol, the Caspian Sea Coast, Iran.伊朗里海沿岸城市巴博勒胃癌的宿主及环境因素
Eur J Cancer Prev. 2007 Jun;16(3):192-5. doi: 10.1097/01.cej.0000220639.61717.67.
3
Cancer occurrence in Iran in 2002, an international perspective.
胃癌生存分析:一项针对伊朗患者的多中心研究。
BMC Surg. 2020 Jul 13;20(1):152. doi: 10.1186/s12893-020-00816-6.
4
Bayesian and Frequentist Analytical Approaches Using Log-Normal and Gamma Frailty Parametric Models for Breast Cancer Mortality.贝叶斯和频率分析方法在对数正态和伽马变斜率参数模型中的应用:乳腺癌死亡率。
Comput Math Methods Med. 2020 Feb 8;2020:9076567. doi: 10.1155/2020/9076567. eCollection 2020.
5
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