肺癌患者并发肌肉减少症的风险预测模型构建

张浩男; 韩缘峰; 夏柳勤; 叶卫国

doi:10.16766/j.cnki.issn.1674-4152.004164

肺癌患者并发肌肉减少症的风险预测模型构建

doi: 10.16766/j.cnki.issn.1674-4152.004164

张浩男^{1, 2},
韩缘峰^{1, 2, ,},
夏柳勤²,
叶卫国²

1.
浙江中医药大学第四临床医学院，浙江杭州 310053
2.
杭州市第一人民医院重症医学科，浙江杭州 310006

基金项目:

浙江省医药卫生科技计划项目 2023KY925

详细信息

通讯作者:
韩缘峰，E-mail: boloer_l@163.com

中图分类号: R734.2
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出版历程
- 收稿日期: 2024-12-08
- 网络出版日期: 2025-11-17

Risk prediction model construction of concurrent sarcopenia in lung cancer patients

ZHANG Haonan^{1, 2},
HAN Yuanfeng^{1, 2
, ,},
XIA Liuqin²,
YE Weiguo²

1.
The Fourth Clinical Medical College of Zhejiang Traditional Chinese Medicine University, Hangzhou, Zhejiang 310053, China

摘要

摘要: 目的探讨肺癌患者发生肌肉减少症的影响因素，构建风险预测模型，为预防或延缓肌肉减少症进程提供参考。方法选取2023年1月—2024年10月杭州市第一人民医院收治的285例肺癌患者为研究对象，采用一般资料调查表、改良版肌肉减少症问卷、微型简易营养评估表、国际体力活动问卷进行调查，根据患者肌肉减少症诊断结果分为肌少症组(119例)和非肌少症组(166例)。通过单因素和多因素logistic回归分析研究肺癌患者肌肉减少症的影响因素，采用R软件建立肌少症的风险预测模型。结果 285例肺癌患者肌肉减少症发生率为41.75%(119/285)。肌少症组年龄≥60岁、女性、BMI＜24.0、有吸烟史、合并糖尿病、睡眠时长＜6 h、营养不良、体力活动低水平占比高于非肌少症组(P < 0.05)，Charson共病指数评分高于非肌少症组(P < 0.05)。Logistic回归分析结果显示，年龄、吸烟史、Charson共病指数、营养状况、体力活动水平均为肺癌患者发生肌少症的影响因素(P < 0.05)。ROC曲线下面积为0.922(95% CI：0.897~0.951)，拟合优度检验显示χ²=1.178，P=0.556。结论风险预测模型对肺癌患者肌肉减少症具有较好的临床预警价值，利于临床医护人员科学、直观地识别肌肉减少症高风险人群，进而有针对性地开展预防与管理工作。
- 肺癌 /
- 肌肉减少症 /
- 影响因素 /
- 预测模型
Abstract: Objective To explore the factors influencing sarcopenia in patients with lung cancer, develop a risk prediction model, and provide reference for preventing or delaying the progress of sarcopenia. Methods From January 2023 to October 2024, 285 patients with lung cancer at Hangzhou First People ' s Hospital were selected as the research objects. Data were collected using a general information questionnaire, improved version of sarcopenia questionnaire, mini-simple nutrition assessment form, and international physical activity questionnaire. According to the diagnosis results of sarcopenia, the patients were divided into a sarcopenia group (119 cases) and a non-sarcopenia group (166 cases). The factors influencing sarcopenia in lung cancer patients were analyzed by univariate and multivariate logistic regression, and the risk prediction model of sarcopenia was established by using R software. Results The incidence of sarcopenia was 41.75% (119/285). The proportion of age≥60 years old, female sex, BMI < 24.0, smoking history, diabetes, sleep duration < 6 hours, malnutrition, and low level of physical activity in the sarcopenia group was higher than those in the non-sarcopenia group (P < 0.05), respectively. Charson comorbidity index score was higher than that of the non-sarcopenia group (P < 0.05). Logistic regression analysis showed that age, smoking history, Charson comorbidity index, nutritional status, and physical activity level were the factors influencing sarcopenia in lung cancer patients (P < 0.05). The area under receiver operating characteristic curve (ROC) was 0.922 (95% CI: 0.897-0.951), and the goodness of fit test showed good model fit (χ²=1.178, P=0.556). Conclusion The developed risk prediction model demonstrates high accuracy and clinical utility for early identification of sarcopenia in lung cancer patients, enabling targeted prevention and management strategies.
- Lung cancer /
- Muscle atrophy /
- Influencing factors /
- Forecasting model

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图 1 肺癌患者肌肉减少症发生风险的列线图预测模型

Figure 1. Nomogram prediction model for the risk of sarcopenia in lung cancer patients

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图 2 肺癌患者肌肉减少症预测模型的ROC曲线

Figure 2. ROC curves of the predictive model for sarcopenia in lung cancer patients

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表 1 肺癌患者肌肉减少症影响因素的单因素分析

Table 1. Univariate analysis of sarcopenia in lung cancer patients

项目	肌少症组 (n=119)	非肌少症组 (n=166)	统计量	P值
年龄[例(%)]			40.241^a	< 0.001
＜60岁	18(15.13)	86(51.81)
≥60岁	101(84.87)	80(48.19)
性别[例(%)]			4.099^a	0.043
男性	61(51.26)	105(63.25)
女性	58(48.74)	61(36.75)
婚姻状况[例(%)]			0.608^a	0.435
有配偶	90(75.63)	132(79.52)
无配偶	29(24.37)	34(20.48)
BMI[例(%)]			2.310^b	0.022
＜24.0	62(52.10)	65(39.16)
24.0~27.9	39(32.77)	59(35.54)
≥28.0	18(15.13)	42(25.30)
吸烟史[例(%)]			16.518^a	< 0.001
有	84(70.59)	77(46.39)
无	35(29.41)	89(53.61)
饮酒史[例(%)]			1.075^a	0.298
有	59(49.58)	72(43.37)
无	60(50.42)	94(56.63)
合并糖尿病[例(%)]			4.252^a	0.039
是	46(38.66)	45(27.11)
否	73(61.34)	121(72.89)
合并高血压[例(%)]			1.753^a	0.185
是	44(36.97)	49(29.52)
否	75(63.03)	117(70.48)
睡眠时长[例(%)]			6.482^a	0.011
＜6 h	61(51.26)	60(36.14)
≥6 h	58(48.74)	106(63.86)
病理类型[例(%)]			1.036^a	0.904
腺癌	63(52.94)	94(56.63)
鳞癌	22(18.49)	31(18.67)
小细胞癌	27(22.69)	35(21.08)
其他	7(5.88)	6(3.62)
肿瘤分期[例(%)]			1.160^b	0.245
Ⅰ~Ⅱ期	26(21.85)	42(25.30)
Ⅲ期	22(18.49)	39(23.49)
Ⅳ期	71(59.66)	85(51.21)
营养不良[例(%)]			31.891^a	< 0.001
是	57(47.90)	28(16.87)
否	62(52.10)	138(83.13)
体力活动水平[例(%)]			5.096^b	< 0.001
低	22(18.49)	11(6.63)
中	68(57.14)	95(57.23)
高	29(24.37)	60(36.14)
Charson共病指数(x±s，分)	3.22±1.30	2.38±1.15	5.756^c	< 0.001
注：^a为χ²值，^b为Z值，^c为t值。

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表 2 变量赋值情况

Table 2. Variable assignment situation

变量	赋值方法
肌少症	否=0，是=1
年龄	＜60岁=0，≥60岁=1
性别	男性=0，女性=1
吸烟史	无=0，有=1
BMI	＜24.0=1，24.0~27.9=2，≥28.0=3
合并糖尿病	否=0，是=1
体力活动水平	低=1，中=2，高=3
Charson共病指数	连续性变量，以实际值赋值
睡眠时长	＜6 h=1，≥6 h=0
营养不良	否=0，是=1

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表 3 肺癌患者肌肉减少症影响因素的logistic回归分析

Table 3. Logistic regression analysis of sarcopenia in lung cancer patients

变量	B	SE	Waldχ²	P值	OR值	95% CI
年龄	1.570	0.495	10.060	＜0.001	4.810	1.822~12.682
吸烟史	0.473	0.231	4.192	0.041	1.605	1.020~2.524
Charson共病指数	0.679	0.282	5.796	0.030	1.972	1.135~3.427
营养不良	1.873	0.506	13.702	＜0.001	6.509	2.414~8.230
体力活动水平	-1.262	0.410	9.474	＜0.001	0.283	0.126~0.632
注：本表仅列出差异有统计学意义的变量。

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