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已发表论文
纳入营养及脂质代谢指标预测恶性胸腔积液非小细胞肺癌患者生存的列线图的建立与验证
Authors Chen B, Yang L, Shen K, Gao W
Received 7 June 2025
Accepted for publication 8 October 2025
Published 29 October 2025 Volume 2025:17 Pages 2523—2536
DOI https://doi.org/10.2147/CMAR.S536389
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Bilikere Dwarakanath
Binyu Chen,1,* Liu Yang,2,* Kaiyu Shen,2 Wencang Gao3
1Department of Ultrasound, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, 310000, People’s Republic of China; 2Department of Oncology, The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, 310000, People’s Republic of China; 3Department of Oncology, The Second Afliated Hospital, Zhejiang Chinese Medical University, Hangzhou, 310000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Wencang Gao, Department of Oncology, The Second Afliated Hospital, Zhejiang Chinese Medical University, Chaowang Road, Gongshu District, Hangzhou, 310000, People’s Republic of China, Tel +86 13616864326, Email wencanggao2011@126.com
Purpose: Patients with non-small cell lung cancer (NSCLC) complicated by malignant pleural effusion (MPE) face a dismal prognosis. Existing biomarkers (eg, VEGF, CEA) show limited sensitivity, while nutritional indices (eg, PNI) are emerging as prognostic factors. This study aimed to develop a novel nomogram integrating lipid metabolism and nutritional indices to predict survival in NSCLC-MPE patients.
Methods: Multicenter retrospective cohort study enrolling patients with confirmed NSCLC combined with MPE who underwent thoracentesis from 2018 to 2024 from each of two centers. Univariate, multifactorial Cox regression analysis was used to identify five key clinical variables, and a nomogram model was developed. The predictive accuracy of the model was evaluated by calculating the area under the curve of the work characteristics of the recipients.
Results: A total of 250 patients with NSCLC combined with MPE were analyzed in this study, 195 in the training group and 55 in the validation group. The multifactorial COX test showed an interaction between ECOG PS, pleural lactate dehydrogenase (LDH), T stage, low/high-density lipoprotein cholesterol concentration ratio (LHR), and prognostic nutritional index (PNI). At 1, 2, and 3 years, the area under the curve (AUC) values were 0.899, 0.808, and 0.748 for the training set and 0.899, 0.798, and 0.669 for the validation set, respectively.
Conclusion: MPE carries a poor prognosis for NSCLC patients, and the clinical prediction model we constructed shows good promise in predicting OS in this patient, which can assist direct the selection of optimal treatment strategies.
Keywords: non-small cell lung cancer, malignant pleural effusions, prediction model, survival analysis, prognostic nutritional index
1Department of Ultrasound, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, 310000, People’s Republic of China; 2Department of Oncology, The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, 310000, People’s Republic of China; 3Department of Oncology, The Second Afliated Hospital, Zhejiang Chinese Medical University, Hangzhou, 310000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Wencang Gao, Department of Oncology, The Second Afliated Hospital, Zhejiang Chinese Medical University, Chaowang Road, Gongshu District, Hangzhou, 310000, People’s Republic of China, Tel +86 13616864326, Email wencanggao2011@126.com
Purpose: Patients with non-small cell lung cancer (NSCLC) complicated by malignant pleural effusion (MPE) face a dismal prognosis. Existing biomarkers (eg, VEGF, CEA) show limited sensitivity, while nutritional indices (eg, PNI) are emerging as prognostic factors. This study aimed to develop a novel nomogram integrating lipid metabolism and nutritional indices to predict survival in NSCLC-MPE patients.
Methods: Multicenter retrospective cohort study enrolling patients with confirmed NSCLC combined with MPE who underwent thoracentesis from 2018 to 2024 from each of two centers. Univariate, multifactorial Cox regression analysis was used to identify five key clinical variables, and a nomogram model was developed. The predictive accuracy of the model was evaluated by calculating the area under the curve of the work characteristics of the recipients.
Results: A total of 250 patients with NSCLC combined with MPE were analyzed in this study, 195 in the training group and 55 in the validation group. The multifactorial COX test showed an interaction between ECOG PS, pleural lactate dehydrogenase (LDH), T stage, low/high-density lipoprotein cholesterol concentration ratio (LHR), and prognostic nutritional index (PNI). At 1, 2, and 3 years, the area under the curve (AUC) values were 0.899, 0.808, and 0.748 for the training set and 0.899, 0.798, and 0.669 for the validation set, respectively.
Conclusion: MPE carries a poor prognosis for NSCLC patients, and the clinical prediction model we constructed shows good promise in predicting OS in this patient, which can assist direct the selection of optimal treatment strategies.
Keywords: non-small cell lung cancer, malignant pleural effusions, prediction model, survival analysis, prognostic nutritional index