Research and Analysis of Screening Tools for Chronic Obstructive Pulmonary Disease Comorbidity Lung Cancer

doi:10.12114/j.issn.1007-9572.2025.0110

Chinese General Practice ›› 2025, Vol. 28 ›› Issue (30): 3847-3852.DOI: 10.12114/j.issn.1007-9572.2025.0110

• Research Methods and Tools • Previous Articles Next Articles

Research and Analysis of Screening Tools for Chronic Obstructive Pulmonary Disease Comorbidity Lung Cancer

1. Respiratory Department, the First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou 450003, China
2. The First Clinical School of Henan University of Traditional Chinese Medicine, Zhengzhou 450046, China
3. Rehabilitation Diagnosis and Treatment Center, the First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou 450003, China
4. Henan University of Traditional Chinese Medicine Respiratory Disease Diagnosis and Treatment and New Drug Research and Development Collaborative Innovation Center Jointly Established by the Province and the Ministry, Zhengzhou 450046, China
5. International Joint Laboratory of Evidence-based Evaluation for Respiratory Diseases of Henan Province, Zhengzhou 450003, China

Received:2025-04-03 Revised:2025-06-15 Published:2025-10-20 Online:2025-08-18
Contact: XIE Yang

慢性阻塞性肺疾病共病肺癌筛查工具分析

1．450003　河南省郑州市，河南中医药大学第一附属医院呼吸科
2．450046　河南省郑州市，河南中医药大学第一临床医学院
3．450003　河南省郑州市，河南中医药大学第一附属医院康复诊疗中心
4．450046　河南省郑州市，河南中医药大学呼吸疾病诊疗与新药研发省部共建协同创新中心
5．450003　河南省郑州市，河南省呼吸疾病循证评价国际联合实验室

通讯作者: 谢洋
作者简介:
作者贡献：
徐百川负责文章的撰写；王艳负责文献检索及相关资料整理；张彭负责文章的构思与设计；李艺婷负责附表的整理；刘飞来负责文章审校与修订；谢洋负责文章的质量控制与监督管理，对文章整体负责。
基金资助:
国家重点研发计划(2023YFC3502601); 国家科技重大专项(2023ZD0506705); 中原科技创新领军人才计划(254000510041); 河南省科技研发计划联合基金（优势学科培育类）项目(232301420088); 河南省中医药科学研究专项课题(2024ZYZD04，2022ZY1012); 河南省临床研究型医生培养专项(HNCRD202435)

Abstract

Abstract:

Chronic obstructive pulmonary disease (COPD) and lung cancer (LC) are high-incidence and high-mortality diseases of the respiratory system. COPD is an independent high-risk factor for LC, and the two conditions influence each other, posing challenges for clinical diagnosis and treatment. Early detection and early treatment are crucial for improving prognosis, making preliminary screening particularly important. This article starts from the current research status of COPD-LC, comprehensively introducing the existing screening tools, including low-dose computed tomography (LDCT), the COPD-LUCSS score and its improved version, the COPD-LUCSS-DLCO score, as well as other COPD-LC risk prediction models. By objectively analyzing the advantages and limitations of existing screening tools, this article proposes countermeasures and precautions for developing new screening tools and envisions future application prospects, aiming to provide support for future COPD-LC screening research.

Key words: Pulmonary disease, chronic obstructive, Lung neoplasms, Multiple chronic conditions, Screening tools, Risk factors, Predictive model, Clinical application

摘要：

慢性阻塞性肺疾病（COPD）和肺癌（LC）是呼吸系统高发病率、高致死率的疾病，COPD是LC的独立高危因素，二者相互影响，给临床诊疗带来挑战。早发现、早治疗是提高预后的关键，因此前期筛查十分重要。本文从COPD-LC的研究现状出发，全面介绍了现有的筛查工具情况，包括低剂量计算机断层扫描（LDCT）、COPD-LC筛查（LUCSS）评分及其改进版COPD-LUCSS-肺一氧化碳弥散量（DLCO）评分，以及其他COPD-LC风险预测模型等。通过客观分析现有筛查工具的优势与不足，提出开发新筛查工具的对策及注意事项，并展望了未来的应用前景，以期为未来COPD-LC的筛查研究提供助力。

关键词: 肺疾病，慢性阻塞性, 肺肿瘤, 慢性病共病, 筛查工具, 危险因素, 预测模型, 临床应用

CLC Number:

R 563.9　R 734.2

XU Baichuan,WANG Yan,ZHANG Peng, et al. Research and Analysis of Screening Tools for Chronic Obstructive Pulmonary Disease Comorbidity Lung Cancer[J]. Chinese General Practice, 2025, 28(30): 3847-3852. DOI: 10.12114/j.issn.1007-9572.2025.0110.
徐百川,王艳,张彭等. 慢性阻塞性肺疾病共病肺癌筛查工具分析[J]. 中国全科医学, 2025, 28(30): 3847-3852. DOI: 10.12114/j.issn.1007-9572.2025.0110.

Figures/Tables 1

References 44

[1]	CHRISTENSON S A, SMITH B M, BAFADHEL M，et al. Chronic obstructive pulmonary disease[J]. Lancet，2022,399(10342):2227-2242. DOI：10.1016/S0140-6736(22)00470-6.
[2]	GUAN W J, ZHENG X Y, CHUNG K F，et al. Impact of air pollution on the burden of chronic respiratory diseases in China：time for urgent action[J]. Lancet，2016,388(10054):1939-1951. DOI：10.1016/S0140-6736(16)31597-5.
[3]	梁振宇，陈荣昌. 慢性阻塞性肺疾病诊疗指南（2021年修订版）修订历程及思考[J]. 中华结核和呼吸杂志，2021,44(3):165-166.
[4]	ZHENG Y Q, HUANG Y, ZHENG X W，et al. Deaths from COPD in patients with cancer：a population-based study[J]. Aging（Albany NY），2021,13(9):12641-12659. DOI：10.18632/aging.202939.
[5]	FORDER A, ZHUANG R, SOUZA V G P，et al. Mechanisms contributing to the comorbidity of COPD and lung cancer[J]. Int J Mol Sci，2023,24(3):2859. DOI：10.3390/ijms24032859.
[6]	THAI A A, SOLOMON B J, SEQUIST L V，et al. Lung cancer[J]. Lancet，2021,398(10299):535-554. DOI：10.1016/S0140-6736(21)00312-3.
[7]	PATEL B, PRIEFER R. Impact of chronic obstructive pulmonary disease，lung infection，and/or inhaled corticosteroids use on potential risk of lung cancer[J]. Life Sci，2022,294:120374. DOI：10.1016/j.lfs.2022.120374.
[8]	MACHIDA H, INOUE S, SHIBATA Y，et al. The incidence and risk analysis of lung cancer development in patients with chronic obstructive pulmonary disease：possible effectiveness of annual CT-screening[J]. Int J Chron Obstruct Pulmon Dis，2021,16:739-749. DOI：10.2147/COPD.S287492.
[9]	CAPLIN M, FESTENSTEIN F. Relation between lung cancer，chronic bronchitis，and airways obstruction[J]. Br Med J，1975,3(5985):678-680. DOI：10.1136/bmj.3.5985.678.
[10]	SKILLRUD D M, OFFORD K P, MILLER R D. Higher risk of lung cancer in chronic obstructive pulmonary disease. A prospective，matched，controlled study[J]. Ann Intern Med，1986,105(4):503-507. DOI：10.7326/0003-4819-105-4-503.
[11]	TOCKMAN M S, ANTHONISEN N R, WRIGHT E C，et al. Airways obstruction and the risk for lung cancer[J]. Ann Intern Med，1987,106(4):512-518. DOI：10.7326/0003-4819-106-4-512
[12]	HUANG R Y, WEI Y Y, HUNG R J，et al. Associated links among smoking，chronic obstructive pulmonary disease，and small cell lung cancer：a pooled analysis in the international lung cancer consortium[J]. EBioMedicine，2015,2(11):1677-1685. DOI：10.1016/j.ebiom.2015.09.031.
[13]	TAMURA T, MIYAZAKI K, SATOH H. Features of COPD as predictors of lung cancer[J]. Chest，2018,154(3):720-721. DOI：10.1016/j.chest.2018.04.047.
[14]	DE TORRES J P, MARÍN J M, CASANOVA C，et al. Lung cancer in patients with chronic obstructive pulmonary disease—incidence and predicting factors[J]. Am J Respir Crit Care Med，2011,184(8):913-919. DOI：10.1164/rccm.201103-0430OC.
[15]	沈盼晓，秦茵茵，周承志. 肺癌与慢性阻塞性肺疾病共病的临床诊疗浅析[J]. 中华结核和呼吸杂志，2024,47(11):1022-1027.
[16]	ZHOU C Z, QIN Y Y, ZHAO W，et al. International expert consensus on diagnosis and treatment of lung cancer complicated by chronic obstructive pulmonary disease[J]. Transl Lung Cancer Res，2023,12(8):1661-1701. DOI：10.21037/tlcr-23-339.
[17]	郑莉莉，陈恒屹. 慢性阻塞性肺疾病合并肺癌的发病机制与治疗研究进展[J]. 检验医学与临床，2024,21(19):2935-2940.
[18]	ZHANG J, ZHOU J B, LIN X F，et al. Prevalence of undiagnosed and undertreated chronic obstructive pulmonary disease in lung cancer population[J]. Respirology，2013,18(2):297-302. DOI：10.1111/j.1440-1843.2012.02282.x.
[19]	XU W G, ZHU J, LI L，et al. The prognostic role of chronic obstructive pulmonary disease for lung cancer after pulmonary resection[J]. J Surg Res，2022,275:137-148. DOI：10.1016/j.jss.2022.01.014.
[20]	AJIMIZU H, OZASA H, SATO S，et al. Survival impact of treatment for chronic obstructive pulmonary disease in patients with advanced non-small-cell lung cancer[J]. Sci Rep，2021,11(1):23677. DOI：10.1038/s41598-021-03139-5.
[21]	FROST J K, BALL W C Jr, LEVIN M L，et al. Early lung cancer detection：results of the initial（prevalence）radiologic and cytologic screening in the Johns Hopkins study[J]. Am Rev Respir Dis，1984,130(4):549-554. DOI：10.1164/arrd.1984.130.4.549.
[22]	HENSCHKE C I. Early lung cancer action project：overall design and findings from baseline screening[J]. Cancer，2000,89(11 suppl):2474-2482. DOI：10.1002/1097-0142(20001201)89:11+<2474::aid-cncr26>3.3.co;2-u.
[23]	ABERLE D R, ADAMS A M, BERG C D，et al. Reduced lung-cancer mortality with low-dose computed tomographic screening[J]. N Engl J Med，2011,365(5):395-409. DOI：10.1056/nejmoa1102873.
[24]	DE KONING H J, VAN DER AALST C M, DE JONG P A，et al. Reduced lung-cancer mortality with volume CT screening in a randomized trial[J]. N Engl J Med，2020,382(6):503-513. DOI：10.1056/NEJMoa1911793.
[25]	MITCHELL E P. U.S. preventive services task force final recommendation statement，evidence summary，and modeling studies on screening for lung cancer[J]. J Natl Med Assoc，2021,113(3):239-240. DOI：10.1016/j.jnma.2021.05.012.
[26]	Global Strategy for Prevention，Diagnosis and Management of COPD：2025 Report[EB/OL]. [2025-03-07].
[27]	RUPAREL M. Lung cancer screening in advanced chronic obstructive pulmonary disease：helpful or harmful [J]. Thorax，2023,78(7):637-639. DOI：10.1136/thorax-2022-219778.
[28]	DE-TORRES J P, ALCAIDE A B, CAMPO A，et al. Lung cancer screening in people with COPD：the Pamplona-IELCAP experience[J]. Arch Bronconeumol，2024,60(2):95-100. DOI：10.1016/j.arbres.2023.12.012.
[29]	DE-TORRES J P, WILSON D O, SANCHEZ-SALCEDO P，et al. Lung cancer in patients with chronic obstructive pulmonary disease. Development and validation of the COPD Lung Cancer Screening Score[J]. Am J Respir Crit Care Med，2015,191(3):285-291. DOI：10.1164/rccm.201407-1210OC.
[30]	GAGNAT A A, GULSVIK A, BAKKE P，et al. Comparison of two lung cancer screening scores among patients with chronic obstructive pulmonary disease：a community study[J]. Clin Respir J，2019,13(2):114-119. DOI：10.1111/crj.12988.
[31]	NAMBU A, ZACH J, SCHROEDER J，et al. Relationships between diffusing capacity for carbon monoxide（DLCO），and quantitative computed tomography measurements and visual assessment for chronic obstructive pulmonary disease[J]. Eur J Radiol，2015,84(5):980-985. DOI：10.1016/j.ejrad.2015.01.010.
[32]	DE-TORRES J P, MARÍN J M, CASANOVA C，et al. Identification of COPD patients at high risk for lung cancer mortality using the COPD-LUCSS-DLCO[J]. Chest，2016,149(4):936-942. DOI：10.1378/chest.15-1868.
[33]	D'ANNA S E, ASNAGHI R, CARAMORI G，et al. High-resolution computed tomography quantitation of emphysema is correlated with selected lung function values in stable COPD[J]. Respiration，2012,83(5):383-390. DOI：10.1159/000329871.
[34]	陈伊，曾晓丽，包海荣，等. 弥散功能对慢性阻塞性肺疾病合并肺癌的预测价值[J]. 国际呼吸杂志，2022(10):721-729.
[35]	FIGUEIRA GONÇALVES J M, PÉREZ MENDEZ L I, GURBANI N，et al. Applicability of the COPD-LUCSS-DLCO score for patients with chronic obstructive pulmonary disease：Analysis in standard clinical practice conditions[J]. Rev Clin Esp（Barc），2018,218(7):336-341. DOI：10.1016/j.rce.2018.04.008.
[36]	SOUSA S R, CALDEIRA J N, RODRIGUES C，et al. Lung cancer screening in clinical practice：identification of high-risk chronic obstructive pulmonary disease patients[J]. Rev Assoc Med Bras（1992），2022,68(4):502-506. DOI：10.1590/1806-9282.20211106.
[37]	黄菊南. COPD合并肺癌的临床特点分析与预测模型的建立[D]. 长春：吉林大学，2024. DOI：10.27162/d.cnki.gjlin.2024.002525.
[38]	李梦琪，贺丰泰，吴雅楠，等. 基于机器学习方法建立慢性阻塞性肺疾病合并肺癌风险的预测模型[J]. 中国呼吸与危重监护杂志，2022,21(11):782-789.
[39]	张瑶，刘学军. 老年慢性阻塞性肺疾病合并肺癌筛查评分模型建立及相关血清学标志物研究[J]. 国际呼吸杂志，2022(1):62-66. DOI：10.3760/cma.j.cn131368-20201111-01019.
[40]	孙蕾. COPD-LUCSS-DLCO肺癌筛查模型的建立及相关血清学标志物的研究[D]. 太原：山西医科大学，2023. DOI：10.27288/d.cnki.gsxyu.2023.001587.
[41]	秦士想，叶永青. 慢性阻塞性肺疾病合并肺癌的临床特点分析及列线图预测模型的建立[J]. 临床肺科杂志，2023,28(11):1682-1686.
[42]	顾瞻，冯迪，赵严，等. 慢性阻塞性肺疾病合并肺癌的"证候-基因-环境"预测模型的构建[J]. 同济大学学报（医学版），2024,45(5):706-712.
[43]	程玮媛，王晓燕，唐华平. 中老年男性慢性阻塞性肺病合并肺癌患者的临床特征分析及数学预测模型的建立[J]. 临床医学进展，2024,14(3):1813-1823.
[44]	HUMPHREY L L, DEFFEBACH M, PAPPAS M，et al. Screening for lung cancer with low-dose computed tomography：a systematic review to update the US preventive services task force recommendation[J]. Ann Intern Med，2013,159(6):411-420. DOI：10.7326/0003-4819-159-6-201309170-00690.

名称	开发时间（年）	适用对象	高危因素	优势	局限性
LDCT（NLST标准）^[23]	2011	普适性	年龄55~74岁；吸烟≥30包年且戒烟<15年	国际通用，广泛验证	存在辐射暴露，筛查周期长
COPD-LUCSS^[29]	2015	COPD患者（50~79岁）	年龄>60岁；BMI<25 kg/m²；年吸烟包数>60包；肺气肿	针对COPD人群，方便快捷	临床验证灵敏度差
COPD-LUCSS-DLCO^[31]	2015	COPD患者	年龄<60岁；年吸烟包数>60包；BMI<25 kg/m²；DLCO<60%	方便快捷、灵敏度高	相关研究均为回顾性研究，证据质量较低，需进一步临床验证
老年COPD合并肺癌筛查评分模型^[39]	2022	COPD患者（≥60岁）	年龄≥73岁；吸烟指数≥1 100；病程时间≥23年；肺气肿	针对老年COPD人群开发	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
慢性阻塞性肺疾病合并肺癌机器学习预测模型^[38]	2022	COPD患者（50~85岁）	凝血酶原活动度（PT%）>113.0%；全肺气肿指数>0.058 98；全肺平均密度>-839.5 HU；用力肺活量（FVC）>2.84 L；BMI<26.05 kg/m²	临床特征联合胸部定量CT	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD-LUCSS-DLCO肺癌筛查模型^[40]	2023	COPD患者（>50岁）	年龄≥64岁；吸烟指数≥1 120；BMI≤22.45 kg/m²；DLCO≤60%	适合我国COPD人群特征	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD合并肺癌列线图预测模型^[41]	2023	COPD患者	年龄≥65岁；吸烟指数≥800；COPD时间；胸痛；咯血；血小板计数	绘制列线图方便患者罹患LC预测概率的计算	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD罹患肺癌预测模型^[37]	2024	COPD患者	吸烟指数≥400；胸腔积液；咯血；体质量减轻；肺不张；慢性阻塞性肺疾病全球倡议（GOLD）分级	绘制列线图方便患者罹患LC预测概率的计算	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD合并肺癌的"证候-基因-环境"预测模型^[42]	2024	COPD患者（40~85岁）	痰证；rsl489759（基因型AA或GA）；rs56113850（基因型CC或TC）；BMI偏低；吸烟包年数偏高	整合COPD合并LC发病相关的中医证候、遗传因素、环境因素和临床参数多维度指标	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
中老年男性COPD合并肺癌数学预测模型^[43]	2024	男性COPD患者（年龄≤70岁）	红细胞沉降率（ESR）升高；中性粒细胞计数与淋巴细胞计数比值（NLR）升高；碱性磷酸酶（ALP）升高	包含外周血液检测指标信息	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证

名称	开发时间（年）	适用对象	高危因素	优势	局限性
LDCT（NLST标准）^[23]	2011	普适性	年龄55~74岁；吸烟≥30包年且戒烟<15年	国际通用，广泛验证	存在辐射暴露，筛查周期长
COPD-LUCSS^[29]	2015	COPD患者（50~79岁）	年龄>60岁；BMI<25 kg/m²；年吸烟包数>60包；肺气肿	针对COPD人群，方便快捷	临床验证灵敏度差
COPD-LUCSS-DLCO^[31]	2015	COPD患者	年龄<60岁；年吸烟包数>60包；BMI<25 kg/m²；DLCO<60%	方便快捷、灵敏度高	相关研究均为回顾性研究，证据质量较低，需进一步临床验证
老年COPD合并肺癌筛查评分模型^[39]	2022	COPD患者（≥60岁）	年龄≥73岁；吸烟指数≥1 100；病程时间≥23年；肺气肿	针对老年COPD人群开发	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
慢性阻塞性肺疾病合并肺癌机器学习预测模型^[38]	2022	COPD患者（50~85岁）	凝血酶原活动度（PT%）>113.0%；全肺气肿指数>0.058 98；全肺平均密度>-839.5 HU；用力肺活量（FVC）>2.84 L；BMI<26.05 kg/m²	临床特征联合胸部定量CT	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD-LUCSS-DLCO肺癌筛查模型^[40]	2023	COPD患者（>50岁）	年龄≥64岁；吸烟指数≥1 120；BMI≤22.45 kg/m²；DLCO≤60%	适合我国COPD人群特征	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD合并肺癌列线图预测模型^[41]	2023	COPD患者	年龄≥65岁；吸烟指数≥800；COPD时间；胸痛；咯血；血小板计数	绘制列线图方便患者罹患LC预测概率的计算	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD罹患肺癌预测模型^[37]	2024	COPD患者	吸烟指数≥400；胸腔积液；咯血；体质量减轻；肺不张；慢性阻塞性肺疾病全球倡议（GOLD）分级	绘制列线图方便患者罹患LC预测概率的计算	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
COPD合并肺癌的"证候-基因-环境"预测模型^[42]	2024	COPD患者（40~85岁）	痰证；rsl489759（基因型AA或GA）；rs56113850（基因型CC或TC）；BMI偏低；吸烟包年数偏高	整合COPD合并LC发病相关的中医证候、遗传因素、环境因素和临床参数多维度指标	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证
中老年男性COPD合并肺癌数学预测模型^[43]	2024	男性COPD患者（年龄≤70岁）	红细胞沉降率（ESR）升高；中性粒细胞计数与淋巴细胞计数比值（NLR）升高；碱性磷酸酶（ALP）升高	包含外周血液检测指标信息	1.单中心回顾性研究存在选择偏倚；2.样本量较少，无临床验证

Research and Analysis of Screening Tools for Chronic Obstructive Pulmonary Disease Comorbidity Lung Cancer

慢性阻塞性肺疾病共病肺癌筛查工具分析

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 1

References 44

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	SHAO Xiaoying, SHAO Jie, ZHU Yan, SHAO Jinling, SHANG Ling, WU Zhenlian, ZHAO Yu, ZHANG Jiacai. Analysis of the Current Status of Iron Deficiency and Factors Affecting Iron Deficiency Anemia among Children Aged 6-36 Months in Guizhou Province [J]. Chinese General Practice, 2025, 28(27): 3368-3374.
[2]	WU Sha, ZHANG Daiyi, LI Jin, XUAN Qinkao, QIAN Xiaodong, ZHU Chuanwu, PU Jianhong, ZHU Li. Correlation Analysis and Model Construction of Metabolic Associated Fatty Liver Disease and Hyperglycemia Based on a Health Examination Cohort [J]. Chinese General Practice, 2025, 28(23): 2861-2869.
[3]	ZHOU Qian, WU Xiaomin, WANG Baohua, YAN Ruohan, YU Miao, WU Jing. Study on Nomogram Prediction Model for Risk of Gastric Cancer [J]. Chinese General Practice, 2025, 28(23): 2870-2877.
[4]	FU Rong, SHI Lei, HE Feiying. Comorbidity of Diabetes and Depression in Middle-aged and Elderly People: the Impact of Sleep, Exercise, and Social Activities [J]. Chinese General Practice, 2025, 28(20): 2491-2500.
[5]	GUO Shengteng, ZHANG Fenfen, WAN Di, YU Dongmei, WANG Qinghua. Risk Factors for Severe Acute Pancreatitis Complicated with Acute Lung Injury: a Meta-analysis [J]. Chinese General Practice, 2025, 28(20): 2546-2554.
[6]	HAN Zheng, SUN Meng, FU Fanglin, PAN Yaojia, WANG Weiqiang. A Study on the Relationship between the Triglyceride-Glucose Index and Cardiometabolic Multimorbidity in Individuals Aged 50 and Above [J]. Chinese General Practice, 2025, 28(18): 2278-2284.
[7]	SONG Mingsha, WANG Youyun, LI Chunsheng, QIAO Hui. The Influence of Chronic Disease Comorbidity on Activities of Daily Living in Rural Elderly in Mountainous Areas of Southern Ningxia Based on Latent Category Analysis [J]. Chinese General Practice, 2025, 28(16): 2033-2038.
[8]	HUANG Zhijie, MAI Zhihua, WANG Haoxiang, HE Yuming, DENG Qiaoyan, DAI Ranran, ZHOU Zhiheng. Multimorbidity of Hypertension, Diabetes, and Dyslipidemia and Influencing Factors of Family Function among the Elderly [J]. Chinese General Practice, 2025, 28(16): 2001-2010.
[9]	WANG Xiaoyu, FENG Zhenzhen, WANG Jun, GUO Xiaochuan, LI Jiansheng. Risk Factors for Acute Kidney Injury in Acute Respiratory Distress Syndrome: a Systematic Review [J]. Chinese General Practice, 2025, 28(12): 1527-1537.
[10]	CHI Xun, LIU Sisi, CHEN Qiao, HU Yue, WANG Weixian. The Suitability of Four Nutritional Screening Tools for Nutritional Screening in Patients with Cirrhosis: a Network Meta-analysis [J]. Chinese General Practice, 2025, 28(11): 1395-1402.
[11]	ZHU Xianshang, ZENG Hongyu, LYU Fengli, WANG Jiancheng. The Current Status and Influencing Factors of Multiple Chronic Conditions among the Elderly Aged 60 and above in Gansu Province [J]. Chinese General Practice, 2025, 28(10): 1193-1199.
[12]	LIAO Xingyu, TIAN Siyu, CHEN Min. The Disease Burden, Risk Factors and Predictive Analysis of Early-onset Colorectal Cancer of Different Genders between China and the World from 1990 to 2021 [J]. Chinese General Practice, 2025, 28(08): 1004-1011.
[13]	ZOU Songyan, ZHANG Riyi, LI Xiaodong, MU Yinyu. Analysis of Clinical Characteristics and Risk Factors of Systemic Sclerosis Combined with Sjögren's Syndrome [J]. Chinese General Practice, 2025, 28(06): 737-741.
[14]	SHI Xiaotian, WANG Shan, YANG Huayu, YANG Yifan, LI Xu, DOU Guoze, MA Qing. A Predictive Nomogram for the Risk of Frailty/Pre-frailty on Inflammatory Biomarkers in the Elderly [J]. Chinese General Practice, 2025, 28(05): 587-593.
[15]	KONG Linghong, XIE Xiaoxin, FU Yanhua, GAN Lin, YANG Xiaoyan, MA Shujing, LONG Hai. Pre-treatment and Acquired Antiretroviral Drug Resistance among People Living with HIV in Southwest China [J]. Chinese General Practice, 2025, 28(02): 242-249.