The Diagnostic Value of the Systemic Immune-Inflammation Index for Venous Thromboembolism in Lung Cancer Patients: A Retrospective Study

Background. Venous thromboembolism (VTE) is considered a common complication in lung cancer patients. Despite its widespread use, the Khorana score performed moderately in predicting VTE risk. This study aimed to determine the diagnostic utility of the Systemic Immunoinflammatory Index (SII) and to...

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Published in:Mediators of inflammation Vol. 2022; pp. 1 - 8
Main Authors: Zhang, Lu, Liu, Xiangliang, Yang, Ruihan, Yang, Yi, Chen, Xiao
Format: Journal Article
Language:English
Published: New York Hindawi 22.08.2022
John Wiley & Sons, Inc
Wiley
Subjects:
Body mass index
Cancer
Cancer patients
Disease
Epidermal growth factor
Health aspects
Hematology
Hemoglobin
Inflammation
Laboratories
Lung cancer
Lung carcinoma
Lymphocytes
Lymphoma
Medical records
Metastases
Morbidity
Multivariate analysis
Nomograms
Oncology, Experimental
Patients
Pulmonary embolisms
Risk factors
Sarcoma
Statistical analysis
Thromboembolism
Thrombosis
Tumors
Ultrasonic imaging
Variables
Taiwan
ISSN:0962-9351, 1466-1861, 1466-1861
Online Access:Get full text
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Summary:Background. Venous thromboembolism (VTE) is considered a common complication in lung cancer patients. Despite its widespread use, the Khorana score performed moderately in predicting VTE risk. This study aimed to determine the diagnostic utility of the Systemic Immunoinflammatory Index (SII) and to create a novel nomogram for predicting VTE in patients with pulmonary carcinoma. Materials and Methods. The data, like clinical features and laboratory indicators, of inpatients diagnosed with lung cancer from March 2019 to March 2020 were collected and analyzed. Univariate and multivariate logistic analyses were performed to confirm the risk factors and then construct a nomogram model. The calibration curve and clinical decision curve analysis (DCA) were used to assess the model’s fitting performance. The receiver-operating characteristic (ROC) curve and the area under the ROC curve (AUC) were used to evaluate the diagnostic value of SII and the nomogram. Results. This study enrolled 369 lung patients with a VTE morbidity rate of 23.33%. The patients with VTE had higher SII levels than the non-VTE group (1441.47 ± 146.28 vs. 626.76 ± 26.04, P<0.001). SII is the stronger correlator for VTE among inflammatory markers, of which the optimal cut-off value was 851.51. Univariate and multivariate analysis revealed that the age, metastasis, antitumor treatment, hemoglobin<100 g/L, SII>851.51 × 109/L, and D-dimer>2 folds were independent risk factors for lung cancer-related VTE, and a new prediction nomogram model was constructed based on them. ROC curve analysis showed the AUC of the new model and Khorana score were 0.708 (0.643-0.772) and 0.600 (0.531-0.699). Conclusion. The SII was a simple and valuable biomarker for VTE, and the new nomogram model based on it can accurately forecast the occurrence of VTE. They can be utilized in clinical practice to identify those at high risk of VTE in lung cancer patients.
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Academic Editor: Mirella Giovarelli
ISSN:0962-9351
1466-1861
1466-1861
DOI:10.1155/2022/9215311