[Retrospective Analysis of Risk Factors for Venous Thromboembolism in 283 Patients with Lung Cancer during Systemic Therapy].

BACKGROUND

Patients with lung cancer have high risk of developing venous thromboembolism (VTE), which has been shown to have a significant impact on mortality. This study was to identify the incidence of VTE in lung cancer patients during systemic therapy and to analyze the risk factors associated with it.

METHODS

We retrospectively analyzed the cases of 283 patients with lung cancer who received systemic therapy in the Department of Medical Oncology and Radiation Sickness, Peking University Third Hospital, from January 2016 to December 2018. Chi-square test and multivariate analyses were used to assess the correlation between clinical features and VTE.

RESULTS

Of the patients we observed, 34 developed VTE, with an incidence of 12.01% (34/283). In patients with lower extremity varicose vein (LVV), there was an increase in the incidence of VTE (50.00% vs 9.89%, P=0.001). The incidence VTE in patients with distant metastasis was higher than that in patients without distant metastasis, and higher than that in patients with tumor-free (14.05% vs 14.00% vs 2.08%, P=0.024). The incidence of VTE in patients with active tumor was also significantly higher than that in patients without it (16.93% vs 8.18%, P=0.025). Patients with hypoalbuminemia (albumin <35 g/L) had more VTE events more than those without did (22.00% vs 9.87%, P=0.017), and patients with an elevated D-dimer level (>0.3 µg/mL) developed more VTE than those without did (17.93% vs 5.80%, P=0.006). There were no significant correlations between pathological types, blood cell count before systemic therapy including leukocyte, hemoglobin and platelet, or antiangiogenic drugs and VTE. Multivariate analysis showed that LVV, hypoalbuminemia and elevated level of D-dimer were independent risk factors of VTE.

CONCLUSIONS

LVV, serum albumin and D-dimer level may be potential and more effective predictors of VTE in lung cancer patients during systemic therapy. Basing on these factors, new predictive model can be built, and further study to validate its efficacy is required.