A New Risk Prediction Model for Venous Thromboembolism and Death in Ambulatory Lung Cancer Patients.

Autor: Gomez-Rosas, Patricia, Giaccherini, Cinzia, Russo, Laura, Verzeroli, Cristina, Gamba, Sara, Tartari, Carmen Julia, Bolognini, Silvia, Ticozzi, Chiara, Schieppati, Francesca, Barcella, Luca, Sarmiento, Roberta, Masci, Giovanna, Tondini, Carlo, Petrelli, Fausto, Giuliani, Francesco, D'Alessio, Andrea, Minelli, Mauro, De Braud, Filippo, Santoro, Armando, Labianca, Roberto
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Zdroj: Cancers; Sep2023, Vol. 15 Issue 18, p4588, 18p
Abstrakt: Simple Summary: The predictive value of existing venous thromboembolism risk assessment models (RAMs) in lung cancer patients is still debated, and the design of new models represents an unmet clinical need. In a prospective cohort of patients with newly diagnosed metastatic lung cancer, clinical characteristics, and hemostatic biomarkers assessed before initiating chemotherapy were used to generate a more accurate RAM. This easy-to-implement RAM was compared to four previously published scores, which were also externally validated in this study. (1) Background: Venous thromboembolism (VTE) is a frequent complication in ambulatory lung cancer patients during chemotherapy and is associated with increased mortality. (2) Methods: We analyzed 568 newly diagnosed metastatic lung cancer patients prospectively enrolled in the HYPERCAN study. Blood samples collected before chemotherapy were tested for thrombin generation (TG) and a panel of hemostatic biomarkers. The Khorana risk score (KRS), new-Vienna CATS, PROTECHT, and CONKO risk assessment models (RAMs) were applied. (3) Results: Within 6 months, the cumulative incidences of VTE and mortality were 12% and 29%, respectively. Patients with VTE showed significantly increased levels of D-dimer, FVIII, prothrombin fragment 1 + 2, and TG. D-dimer and ECOG performance status were identified as independent risk factors for VTE and mortality by multivariable analysis and utilized to generate a risk score that provided a cumulative incidence of VTE of 6% vs. 25%, death of 19% vs. 55%, and in the low- vs. high-risk group, respectively (p < 0.001). While all published RAMs significantly stratified patients for risk of death, only the CATS and CONKO were able to stratify patients for VTE. (4) Conclusions: A new prediction model was generated to stratify lung cancer patients for VTE and mortality risk, where other published RAMs failed. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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