Early identification of lung cancer patients with venous thromboembolism: development and validation of a risk prediction model

Thrombosis Journal

Research

Wenjuan Di¹  Haotian Xu²  Chunhua Ling²  Ting Xue² 

[1] Department of Pulmonary and Critical Care Medicine, Kunshan Hospital of Traditional Chinese Medicine, Suzhou City, Jiangsu Province, People’s Republic of China;Department of Pulmonary and Critical Care Medicine, The First Hospital Affiliated of Soochow Unversity, No188, Shizi Street, Gusu district, Suzhou City, Jiangsu Province, People’s Republic of China;

关键词: Lung cancer;    Venous thromboembolism;    Biomarker;    Risk factor;    Risk prediction model;   

DOI  :  10.1186/s12959-023-00544-w

 received in 2023-08-01, accepted in 2023-09-10,  发布年份 2023

来源: Springer

【 摘 要 】

IntroductionVenous thromboembolism(VTE) is a leading cause of death in patients with lung cancer. Furthermore, hospitalization of patients with advanced lung cancer for VTE treatment represents a major economic burden on the national public health resources. Therefore, we performed this prospective study to identify clinical biomarkers for the early identification of VTE in lung cancer patients.MethodsThis prospective study enrolled 158 patients with confirmed lung cancer, including 27 who were diagnosed with VTE within six months of the follow-up after lung cancer diagnosis. Multivariate logistic regression analysis was used to evaluate the diagnostic performancese of all the relevant clinical features and laboratory indicators in identifying lung cancer patients with a higher risk of VTE. A novel risk prediction model was constructed consisting of five clinical variables with the best diagnostic performances and was validated using the receiver operation characteristic(ROC) curves. The diagnostic performances of the new risk prediction model was also compared with the Khorana risk score (KRS) and the Padua risk score (PRS).ResultsThe VTE group of lung cancer patients (n = 27) showed significantly higher serum levels of fibrin degradation products (FDP), D-dimer, thrombomodulin (TM), thrombin-antithrombin-complex (TAT), α2-plasmin inhibitor-plasmin Complex (PIC), and tissue plasminogen activator-plasminogen activator inhibitor complex (t-PAIC) compared to those in the non-VTE group (n = 131). ROC curve analyses showed that the diagnostic efficacy of the new VTE risk prediction model with TM ≥ 9.75 TU/ml, TAT ≥ 2.25ng/ml, t-PAIC ≥ 7.35ng/ml, history of VTE, and ECOG PS score ≥ 2 was superior than the KRS and the PRS in the early identification of lung cancer patients with a higher risk of VTE.ConclusionsThe new risk prediction model showed significantly high diagnostic efficacy in the early identification of lung cancer patients with a high risk of VTE. The diagnostic efficacy of the new risk prediction model was higher than the KRS and the PRS in this cohort of lung cancer patients.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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