Development and validation of a predictive score for venous thromboembolism in newly diagnosed non-small cell lung cancer

Introduction: The risk of venous thromboembolism (VTE) varies among tumour types, and different cancer type-specific risks for VTE prediction remain undefined. We aimed to establish a prediction model for non-small lung cancer (NSCLC)-associated VTE. Materials and methods: We analysed data from a prospective cohort of patients with newly diagnosed NSCLC. We then developed a VTE risk prediction model using data of patients who were recruited from 2013 to 2017 (n = 602, development cohort) and validated this model using date of patients recruited from 2018 to 2019 (n = 412, validation cohort). The cumulative 6 months VTE incidence observed in both cohorts was calculated. Results: The parameters in this new model included Eastern Cooperative Oncology Group (ECOG) performance status >2 (1 point), EGFR mutation (-1 point), neutrophil count >= 7.5 x 10(9)/L (2 points), hemoglobin <115 g/L (1 point), CEA >= 5.0 ng/mL (2 points), and D-dimer level >= 1400 ng/mL (4 points). The cross-validated concordance indices of the model in the development and validation cohorts were 0.779 and 0.853, respectively. Furthermore, the areas under the curve in the two cohorts were 0.7563 (95% confidence interval [CI]: 0.6856-0.8129, P < 0.001) and 0.8211 (95% CI: 0.7451-0.8765, P < 0.001) for development and validation cohorts, respectively. Conclusions: The new VTE risk prediction model incorporated patient characteristics, laboratory values, and oncogenic status, and was able to stratify patients at high risk of VTE in newly diagnosed NSCLC within 6 months of diagnosis.

Automated summary

A prediction model for VTE risk in patients with non-small cell lung cancer was developed and validated using data from prospective cohorts. The model incorporated patient characteristics, laboratory values, and oncogenic status, demonstrating high predictive accuracy and stability in two separate cohorts.