Abstract 1856P
Background
There is a lack of a validated scoring system for predicting clinically significant bleeding in patients anticoagulated for cancer-associated venous thromboembolism (Ca-VTE). The aim was to validate the B-CAT score, a new tool designed to assess bleeding risk in these patients.
Methods
Data came from the TESEO study, a national, multicenter and prospective registry that documents patients with Ca-VTE. We included patients anticoagulated for Ca-VTE and monitored them over 180 days for major or clinically relevant bleeding events. The variables of B-CAT score were selected: tumor location, metastasis, history of major or clinically relevant bleeding, anaemia, coagulopathies, and cerebrovascular and gastrointestinal disease. Data on minor trauma and minor surgery and clinically relevant bleeding without hospitalization after Ca-VTE could not be included as these were not available. Patients were stratified into three categories of bleeding risk, and a multivariate logistic regression model was developed using these variables to estimate bleeding risk.
Results
The study comprised 2,301 anticoagulated Ca-VTE patients. Over an equivalent period of 848 person-years, we identified 157 significant bleeding events (6.8%; 18.5 per 100 person-years), including 63 major (40.1%; 7.4 per 100 person-years) and 94 clinically relevant bleeding events (59.9%, 11.1 per 100 person-years). Patients classified as low (47.8%), medium (50.5%), and high (1.7%) risk according to the B-CAT score demonstrated different 6-month significant bleeding rates: 11.4, 24.4, and 100 per 100 person-years, respectively (p<0.001). The predictive model exhibited satisfactory calibration (Hosmer-Lemeshow test: p=0.886) and discrimination, as evidenced by C-statistic indices for significant bleeding, major bleeding, and clinically relevant bleeding of 0.63 (95% confidence interval: 0.58-0.67), 0.61 (0.53-0.69), and 0.63 (0.57-0.69), respectively.
Conclusions
We have validated the bleeding risk score B-CAT in patients with Ca-VTE receiving anticoagulation. This model has the potential to standardize decision-making in situations where there is limited robust evidence.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
M. Sanchez Canovas: Financial Interests, Personal, Speaker, Consultant, Advisor: Leo Pharma, Sanofi, Lundbeck, Angelini. I. Fernandez Perez: Financial Interests, Personal, Invited Speaker, training session: Merck; Financial Interests, Personal, Invited Speaker, training session: GSK. E.M. Brozos Vazquez: Financial Interests, Personal, Advisory Board: Pfizer, Servier, Bayer; Financial Interests, Personal, Invited Speaker: Servier, Amgen, LEO Pharma, Rovi, Merck, Roche, AstraZeneca, Kiowa Kirin, BMS, MSD. T. Quintanar Verduguez: Financial Interests, Personal, Advisory Board: Pfizer; Financial Interests, Personal, Invited Speaker: MSD oncology, Daiichi Sankyo, Lilly, Novartis; Financial Interests, Institutional, Local PI, pi clinical trial: AstraZeneca. S. Garcia-Adrian: Financial Interests, Personal, Speaker’s Bureau: AstraZeneca, Novartis, GSK, Pierre Fabre, Sanofi, Pfizer, Eisai. A.J. Munoz Martin: Financial Interests, Personal, Advisory Board: GSK, AstraZeneca, Sanofi, Celgene, Servier, MSD, Pfizer, Leo Pharma, Roche; Financial Interests, Personal, Invited Speaker: Lilly, Rovi, STADA, Menarini, BMS; Financial Interests, Institutional, Advisory Board, VTE risk assessment model: Genincode; Financial Interests, Institutional, Local PI: Celgene. All other authors have declared no conflicts of interest.
Resources from the same session
1832P - Physical condition is associated with quality of life in colorectal cancer survivors: Results from a Portuguese and Spanish cohort of patients
Presenter: Luisa Soares Miranda
Session: Poster session 12
1833P - JUMP_START: Optimization of multiprofessional care for young patients with colorectal cancer
Presenter: Kaiyu Xu
Session: Poster session 12
1834P - Accuracy of recommendations by a conversational Artificial Intelligence (AI) cancer mentor application (app): A multi-disciplinary, multi-institutional evaluation report
Presenter: Talia Golan
Session: Poster session 12
1835P - Multi-centre, randomised controlled trial of digital health cancer solution for cancer patients receiving chemotherapy
Presenter: Agnieszka Michael
Session: Poster session 12
1836P - Patient-reported health behaviors (PRHB) among 1850 patients enrolled in a remote patient monitoring (RPM) pathway
Presenter: Maria Alice Franzoi
Session: Poster session 12
1837P - Assessing care complexity in remote patient monitoring (RPM): A cohort study of 2434 cancer patients across 50 sites in France and Belgium
Presenter: Capucine Baldini
Session: Poster session 12
1838P - AI-based smart oncology follow-up system: Prospective application testing and enhancement of clinical efficacy
Presenter: Chunwei Xu
Session: Poster session 12
1839P - Dynamic reporting of treatment related symptoms via ePROs can reversely identify the type of underlying cancer
Presenter: Andreas Trojan
Session: Poster session 12
1840P - Ready for digital health? A national mirror survey exploring the perspectives of both patients and healthcare professionals
Presenter: Florian Scotté
Session: Poster session 12
1841P - Feasibility of wrist-worn health-tracker data to predict the need for therapy modifications in patients with metastatic cancer
Presenter: Anna Sophie Berghoff
Session: Poster session 12