Mohammadzadeh F, Noorkojuri H, Pourhoseingholi M A, Saadat S, Baghestani A R
Department of Basic Sciences, Faculty of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran.
Ir J Med Sci. 2015 Jun;184(2):277-84. doi: 10.1007/s11845-014-1100-9. Epub 2014 Mar 14.
Gastric cancer is the fourth most common cancer worldwide. This reason motivated us to investigate and introduce gastric cancer risk factors utilizing statistical methods.
The aim of this study was to identify the most important factors influencing the mortality of patients who suffer from gastric cancer disease and to introduce a classification approach according to decision tree model for predicting the probability of mortality from this disease.
Data on 216 patients with gastric cancer, who were registered in Taleghani hospital in Tehran,Iran, were analyzed. At first, patients were divided into two groups: the dead and alive. Then, to fit decision tree model to our data, we randomly selected 20% of dataset to the test sample and remaining dataset considered as the training sample. Finally, the validity of the model examined with sensitivity, specificity, diagnosis accuracy and the area under the receiver operating characteristic curve. The CART version 6.0 and SPSS version 19.0 softwares were used for the analysis of the data.
Diabetes, ethnicity, tobacco, tumor size, surgery, pathologic stage, age at diagnosis, exposure to chemical weapons and alcohol consumption were determined as effective factors on mortality of gastric cancer. The sensitivity, specificity and accuracy of decision tree were 0.72, 0.75 and 0.74 respectively.
The indices of sensitivity, specificity and accuracy represented that the decision tree model has acceptable accuracy to prediction the probability of mortality in gastric cancer patients. So a simple decision tree consisted of factors affecting on mortality of gastric cancer may help clinicians as a reliable and practical tool to predict the probability of mortality in these patients.
胃癌是全球第四大常见癌症。这一原因促使我们利用统计方法调查并介绍胃癌的危险因素。
本研究的目的是确定影响胃癌患者死亡率的最重要因素，并引入一种基于决策树模型的分类方法来预测该疾病的死亡概率。
对伊朗德黑兰塔莱哈尼医院登记的216例胃癌患者的数据进行分析。首先，将患者分为两组：死亡组和存活组。然后，为使决策树模型适用于我们的数据，我们随机选择20%的数据作为测试样本，其余数据作为训练样本。最后，通过敏感性、特异性、诊断准确性和受试者工作特征曲线下面积来检验模型的有效性。使用CART 6.0版和SPSS 19.0版软件进行数据分析。
糖尿病、种族、烟草、肿瘤大小、手术、病理分期、诊断时年龄、接触化学武器和饮酒被确定为影响胃癌死亡率的因素。决策树的敏感性、特异性和准确性分别为0.72、0.75和0.74。
敏感性、特异性和准确性指标表明，决策树模型在预测胃癌患者死亡概率方面具有可接受的准确性。因此，一个由影响胃癌死亡率的因素组成的简单决策树可能有助于临床医生作为一种可靠且实用的工具来预测这些患者的死亡概率。
