Construction and Verification of a Nomogram to Predict the Probability of Venous Thromboembolism in Lung Cancer Patients

BackgroundLung cancer (LC) patients account for 20% of all cancer-related venous thromboembolism (VTE) events, which is the second leading cause of mortality in these patients. However, there are no LC-specific risk scores for VTE prediction. Therefore, we considered that an LC-specific nomogram would more accurately predict VTE probability for these patients than the current widely used VTE risk scores.MethodsA total of 676 patients from the Guizhou Provincial People’s Hospital (January 2016 to September 2021) were included in this study, of which 169 LC patients who developed VTE were time-matched with 507 (1:3 ratio) LC patients without VTE. These patients were randomly divided at a 2:1 ratio to form primary (451) and validation (225) cohorts. The accuracy of six VTE risk scores was assessed by producing area under the receiver operating characteristic (ROC) curves (AUC). A multivariate analysis was employed to select predictive features, which were then used to construct a nomogram for VTE prediction.ResultsAmong the scoring methods, COMPASS-CAT had the highest AUC (0.799). The multivariate analyses revealed that acute infection, bed rest (>3 days), D-dimer level >1.47 μg/mL, adenocarcinoma, and carcinoembryonic antigen (CEA) >10.935 ng/mL were independent predictors of VTE risk for LC patients. The nomogram constructed using these factors enabled VTE prediction with a concordance index of 0.882 and an AUC of 0.894.ConclusionThis article describes the construction and validation of a new nomogram for VTE prediction in LC patients, which has a predictive performance that is higher than any of the widely used conventional risk assessment tools.