基于决策树模型分析肺癌化疗患者睡眠障碍发生的危险因素及护理对策

胡菲; 阳华; 阳婷; 李璐

doi:10.16766/j.cnki.issn.1674-4152.003820

基于决策树模型分析肺癌化疗患者睡眠障碍发生的危险因素及护理对策

doi: 10.16766/j.cnki.issn.1674-4152.003820

南昌大学第一附属医院肿瘤医学中心，江西南昌 330001

基金项目:

江西省教育厅科学研究计划项目 GJJ2200122

详细信息

通讯作者:
阳华，E-mail：55533193@qq.com

中图分类号: R734.2 R473.73
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- 文章访问数: 23
- HTML全文浏览量: 11
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- 被引次数: 0
出版历程
- 收稿日期: 2024-05-18
- 网络出版日期: 2025-01-20

Analysis of risk factors and nursing strategies for sleep disorders in lung cancer chemotherapy patients based on decision tree model

Cancer Medical Center of the First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330001, China

摘要

摘要: 目的分析肺癌化疗患者睡眠障碍的影响因素，制定护理对策以降低肺癌化疗患者睡眠障碍发生风险。方法选取2023年1—12月南昌大学第一附属医院收治的110例肺癌患者作为研究对象。根据阿森斯失眠量表(AIS)评分将患者分为睡眠障碍组(44例)及非睡眠障碍组(66例)。比较2组基线资料、实验室指标；采用二元logistic回归分析肺癌化疗患者睡眠障碍的影响因素，构建决策树模型，绘制受试者工作特征曲线(ROC)验证决策树模型预测效能。结果肺癌化疗患者睡眠障碍发生率[40.00%(44/110)]；睡眠障碍组化疗周期、视觉模拟评分法(VAS)评分、白细胞介素-6(IL-6)、肿瘤坏死因子-α(TNF-α)、C反应蛋白(CRP)高于非睡眠障碍组，Ⅲ~Ⅳ分期、使用紫杉醇+铂类化疗方案占比高于非睡眠障碍组(P＜0.05)；二元logistic回归分析结果显示，Ⅲ~Ⅳ分期、紫杉醇+铂类化疗方案、化疗周期、VAS评分、IL-6是肺癌化疗患者睡眠障碍的影响因素(OR＞1，P＜0.05)；纳入以上因素生成决策树模型，共筛出VAS评分、IL-6、TNM分期3个解释变量，VAS评分为最重要根节点变量、预测因子。决策树预测模型曲线下面积为0.915，P＜0.001，预测价值较高。结论 TNM分期、化疗方案、化疗周期、VAS评分、IL-6构建的决策树模型对肺癌化疗患者睡眠障碍具有较高的预测价值。
- 肺癌 /
- 睡眠障碍 /
- 化疗 /
- 影响因素 /
- 决策树
Abstract: Objective To analyze the influencing factors of sleep disorders in lung cancer chemotherapy patients and develop nursing strategies to reduce the risk of sleep disorders in lung cancer chemotherapy patients. Methods A total of 110 lung cancer patients admitted to the First Affiliated Hospital of Nanchang University from January 2023 to December 2023 were selected as the research subjects. Patients were divided into a sleep disorder group (n=44) and a non-sleep disorder group (n=66) based on the Athens insomnia scale (AIS) score. Baseline data and laboratory indicators were compared between the two groups; Binary logistic regression was used to analyze the influencing factors of sleep disorders in lung cancer chemotherapy patients, build a decision tree model, and draw receiver operating characteristic curves (ROC) to verify the predictive efficiency of the decision tree model. Results The incidence of sleep disorders in lung cancer chemotherapy patients [40.00% (44/110)]; The chemotherapy cycle, visual analog scale (VAS) score, interleukin-6 (IL-6), tumor necrosis factor -α (TNF -α), and C-reactive protein (CRP) in the sleep disorder group were higher than those in the non-sleep disorder group. The proportion of stage Ⅲ-Ⅳ and the use of paclitaxel+platinum chemotherapy regimen was higher in the sleep disorder group than in the non-sleep disorder group (P<0.05); According to binary logistic regression analysis, stages Ⅲ-Ⅳ, paclitaxel+platinum chemotherapy regimen, chemotherapy cycle, VAS score, and IL-6 were the influencing factors of sleep disorders in lung cancer chemotherapy patients (OR>1, P<0.05). A decision tree model was generated by incorporating these factors, and three explanatory variables including VAS score, IL-6, and TNM staging were screened out. VAS score was the most important root node variable and predictor. The AUC of the decision tree prediction model was 0.915, P<0.001, indicating a high predictive value. Conclusion The decision tree model constructed by TNM staging, chemotherapy regimen, chemotherapy cycle, VAS score, and IL-6 has a high predictive value for sleep disorders in lung cancer chemotherapy patients.
- Lung cancer /
- Sleep disorders /
- Chemotherapy /
- Influencing factors /
- Decision tree

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表 1 2组肺癌患者基线资料比较

Table 1. Comparison of baseline data between the two groups of lung cancer patients

项目	睡眠障碍组 (n=44)	非睡眠障碍组 (n=66)	统计量	P值
年龄(x±s，岁)	56.71±3.89	57.12±3.73	0.555^a	0.580
性别[例(%)]
男性	29(65.91)	46(69.70)	0.175^b	0.676
女性	15(34.09)	20(30.30)
TNM分期[例(%)]
Ⅰ~Ⅱ期	12(27.27)	45(68.18)	19.063^b	＜0.001
Ⅲ~Ⅳ期	32(72.73)	21(31.82)
病理类型[例(%)]
小细胞癌	9(20.45)	16(24.24)	0.216^b	0.642
非小细胞癌	35(79.55)	50(75.76)
糖尿病[例(%)]
有	10(22.73)	20(30.30)	0.764^b	0.382
无	34(77.27)	46(69.70)
高血压[例(%)]
有	8(18.18)	18(27.27)	1.209^b	0.272
无	36(81.82)	48(72.73)
吸烟史[例(%)]
有	15(34.09)	27(40.91)	0.520^b	0.471
无	29(65.91)	39(59.09)
饮酒史[例(%)]
有	18(40.91)	35(53.03)	1.554^b	0.213
无	26(59.09)	31(46.97)
化疗方案[例(%)]
伊立替康+铂类	9(20.45)	26(39.39)	15.708^b	＜0.001
依托泊苷+铂类	7(15.91)	23(34.85)
紫杉醇+铂类	28(63.64)	17(25.76)
PFS评分[M(P₂₅, P₇₅)，分]	4(4，5)	4(4，5)	0.596^c	0.551
化疗周期[M(P₂₅, P₇₅)，疗程]	5(4，5)	3(2，4)	6.048^c	＜0.001
VAS评分(x±s，分)	8.57±1.02	7.24±0.93	7.047^a	＜0.001
实验室指标(x±s)
IL-6(pg/mL)	68.12±7.81	62.89±7.94	3.401^a	0.001
TNF-α(ng/L)	18.14±1.39	17.52±1.53	2.139^a	0.035
CRP(mg/L)	23.24±1.10	22.59±1.21	2.895^a	0.005
Hb(g/L)	117.13±7.52	117.28±7.61	0.102^a	0.919
WBC(×10⁹/L)	3.89±0.71	4.06±0.75	1.190^a	0.267
PLT(×10⁹/L)	114.42±11.08	116.03±10.98	0.751^a	0.455
注：^a为t值，^b为χ²值，^c为U值。

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表 2 肺癌患者化疗后发生睡眠障碍的影响因素分析

Table 2. Analysis of influencing factors of sleep disorders in patients with lung cancer after chemotherapy

变量	B	SE	Waldχ²	P值	OR	95% CI
TNM分期	1.672	0.799	4.381	0.036	5.322	1.112~25.465
化疗方案	0.917	0.456	4.036	0.045	2.502	1.023~6.121
化疗周期	1.192	0.370	10.403	0.001	3.294	1.569~6.797
VAS评分	1.276	0.378	11.364	0.001	3.581	1.076~7.517
IL-6	0.123	0.047	6.968	0.008	1.131	1.032~1.240
TNF-α	0.515	0.293	3.086	0.079	1.674	0.942~2.974
CRP	0.569	0.324	3.097	0.078	1.767	0.937~3.332

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表 3 不同阈值下决策树模型预测肺癌化疗患者发生睡眠障碍的ROC

Table 3. ROC curve analysis for predicting sleep disturbances in lung cancer chemotherapy patients using decision tree models at different thresholds

AUC	cut-off值	95% CI	P值	特异度	灵敏度	约登指数
0.915	0.299	0.859~0.950	＜0.001	0.864	0.886	0.750
0.915	0.661	0.859~0.950	＜0.001	0.924	0.795	0.719

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