北京生物醫(yī)學(xué)工程

多層線性模型在肺癌患者腫瘤進(jìn)展中的應(yīng)用

Application of hierarchical linear model in thedevelopment of tumor in lung cancer

作者：孫延輝方麗英王普

單位：北京工業(yè)大學(xué)電子信息與控制工程學(xué)院(北京100124)

關(guān)鍵詞：腫瘤縱向數(shù)據(jù)；多層線性模型；腫瘤大小；肺癌;個(gè)體特征

分類號(hào)：R318.04

出版年·卷·期（頁(yè)碼）：2017·36·1（77-81）

摘要：

目的通過(guò)分析肺癌患者以隨訪方式收集的一組縱向數(shù)據(jù)，研究肺癌患者腫瘤大小隨時(shí)間變化的趨勢(shì)，同時(shí)分析這種變化趨勢(shì)的個(gè)體癥狀之間的差異性。方法本文采用多層線性模型，對(duì)腫瘤發(fā)展的縱向數(shù)據(jù)進(jìn)行了深入研究。首先對(duì)213例非小細(xì)胞肺癌患者進(jìn)行了2年的隨訪記錄，記錄患者性別、是否抽煙、癥狀（咳嗽、痰中帶血、胸痛、發(fā)熱、神疲乏力）和腫瘤大小數(shù)據(jù)，然后通過(guò)建立多層線性模型分析腫瘤大小與患者性別、是否抽煙及患者所表現(xiàn)出癥狀之間的關(guān)系。結(jié)果通過(guò)對(duì)肺癌患者數(shù)據(jù)建立多層線性模型并進(jìn)行數(shù)據(jù)分析，發(fā)現(xiàn)患者性別、是否抽煙與腫瘤的大小有密切關(guān)系，且不同個(gè)體特征對(duì)腫瘤大小的影響存在差異。結(jié)論多層線性模型可以分析肺癌患者腫瘤發(fā)展的縱向數(shù)據(jù)，得到腫瘤大小的發(fā)展趨勢(shì)，并可以進(jìn)一步分析這種趨勢(shì)在個(gè)體之間的差異性。

Objective By analyzing a set of longitudinal data collected from patients with lung cancer during follow-up, the trend of tumor size in patients with lung cancer was studied, and the differences between individual symptoms of this trend were analyzed. Methods In this paper, hierarchical linear model (HLM) was used to study the longitudinal data of tumor development. Firstly, we tracked 213 cases of non-small cell lung cancer patients for up to two years and recorded patient gender, the habit of smoking and some other related symptoms (cough, bloody sputum, chest pain, fever, god fatigue) and tumor size data. Then, through the establishment of hierarchical linear model, we analyzed the relationships between tumor size and gender, smoking, symptoms of the patients. Results By establishing HLM and analyzing the longitudinal data of cancer, we found that close relationships existed between the tumor size and the gender, the habit of smoking. Additionally, the effects of different individual characteristics to their tumor size were significantly different. Conclusions HLM can help to dig the longitudinal data of tumor development and obtain the development trend of tumor size, which can be further analyzed.

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