Validation of the Role of Thrombin Generation Potential by a Fully Automated System in the Identification of Breast Cancer Patients at High Risk of Disease Recurrence.
Patricia Gomez-RosasMarina PesentiCristina VerzeroliCinzia GiaccheriniLaura RussoRoberta SarmientoGiovanna MasciLuigi CelioMauro MinelliSara GambaCarmen Julia TartariCarlo TondiniFrancesco GiulianiFausto PetrelliAndrea D'AlessioGiampietro GaspariniRoberto LabiancaArmando SantoroFilippo De BraudMarina MarchettiAnna Falanganull nullPublished in: TH open : companion journal to thrombosis and haemostasis (2021)
Background The measurement of thrombin generation (TG) potential by the calibrated automated thrombogram (CAT) assay provides a strong contribution in identifying patients at high risk of early disease recurrence (E-DR). However, CAT assay still needs standardization and clinical validation. Objective In this study, we aimed to validate the role of TG for E-DR prediction by means of the fully automated ST Genesia system. Methods A prospective cohort of 522 patients from the HYPERCAN study with newly diagnosed resected high-risk breast cancer was included. Fifty-two healthy women acted as controls. Plasma samples were tested for protein C, free-protein S, and TG by ST Genesia by using the STG-ThromboScreen reagent with and without thrombomodulin (TM). Results In the absence of TM, patients showed significantly higher peak and ETP compared with controls. In the presence of TM, significantly lower inhibition of ETP and Peak were observed in patients compared with controls. E-DR occurred in 28 patients; these patients had significantly higher peak and endogenous thrombin potential (ETP) in the absence of TM compared with disease-free patients. Multivariable analysis identified mastectomy, luminal B HER2-neg, triple negative subtypes, and ETP as independent risk factors for E-DR. These variables were combined to generate a risk assessment score, able to stratify patients in three-risk categories. The E-DR rates were 0, 4.7, and 13.5% in the low-, intermediate-, and high-risk categories (hazard ratio = 8.7; p < 0.05, low vs. high risk). Conclusion Our data validate the ETP parameter with a fully automated standardized system and confirm its significant contribution in identifying high-risk early breast cancer at risk for E-DR during chemotherapy.
Keyphrases
- newly diagnosed
- end stage renal disease
- ejection fraction
- chronic kidney disease
- risk assessment
- prognostic factors
- patient reported outcomes
- squamous cell carcinoma
- deep learning
- peritoneal dialysis
- machine learning
- adipose tissue
- radiation therapy
- young adults
- polycystic ovary syndrome
- skeletal muscle
- single cell
- binding protein
- artificial intelligence
- heavy metals
- pregnancy outcomes
- recombinant human
- early breast cancer
- clinical evaluation
- childhood cancer