Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but assessment of the patient’s individual risk of VTE prior to chemotherapy is generally advocated. In recent years, efforts have been devoted to building accurate predictive tools for VTE risk assessment in cancer patients. This review focuses on candidate biomarkers and prediction models currently under investigation, considering their advantages and disadvantages, and discussing their diagnostic performance and potential pitfalls.

Riondino, S., Ferroni, P., Zanzotto, F.m., Roselli, M., Guadagni, F. (2019). Predicting VTE in cancer patients: Candidate biomarkers and risk assessment models. CANCERS, 11(1), 95 [10.3390/cancers11010095].

Predicting VTE in cancer patients: Candidate biomarkers and risk assessment models

Riondino, Silvia;Zanzotto, Fabio Massimo
Membro del Collaboration Group
;
Roselli, Mario;
2019-01-01

Abstract

Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but assessment of the patient’s individual risk of VTE prior to chemotherapy is generally advocated. In recent years, efforts have been devoted to building accurate predictive tools for VTE risk assessment in cancer patients. This review focuses on candidate biomarkers and prediction models currently under investigation, considering their advantages and disadvantages, and discussing their diagnostic performance and potential pitfalls.
2019
Pubblicato
Rilevanza internazionale
Recensione
Esperti anonimi
Settore MED/06 - ONCOLOGIA MEDICA
Settore ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI
Settore INF/01 - INFORMATICA
English
Biomarkers; Clinical decision systems; Machine learning; Risk assessment models; Venous thromboembolism; Oncology; Cancer Research
https://www.mdpi.com/2072-6694/11/1/95/pdf
Riondino, S., Ferroni, P., Zanzotto, F.m., Roselli, M., Guadagni, F. (2019). Predicting VTE in cancer patients: Candidate biomarkers and risk assessment models. CANCERS, 11(1), 95 [10.3390/cancers11010095].
Riondino, S; Ferroni, P; Zanzotto, Fm; Roselli, M; Guadagni, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/210977
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