Estimating Bleeding Risk in Patients with Cancer-Associated Thrombosis: Evaluation of Existing Risk Scores and Development of a New Risk Score

Abstract

Background Bleeding risk is highly relevant for treatment decisions in cancer-associated thrombosis (CAT). Several risk scores exist, but have never been validated in patients with CAT and are not recommended for practice. Objectives To compare methods of estimating clinically relevant (major and clinically relevant nonmajor) bleeding risk in patients with CAT: (1) existing risk scores for bleeding in venous thromboembolism, (2) pragmatic classification based on cancer type, and (3) new prediction model. Methods In a posthoc analysis of the Hokusai VTE Cancer study, a randomized trial comparing edoxaban with dalteparin for treatment of CAT, seven bleeding risk scores were externally validated (ACCP-VTE, HAS-BLED, Hokusai, Kuijer, Martinez, RIETE, and VTE-BLEED). The predictive performance of these scores was compared with a pragmatic classification based on cancer type (gastrointestinal; genitourinary; other) and a newly derived competing risk-adjusted prediction model based on clinical predictors for clinically relevant bleeding within 6 months after CAT diagnosis with nonbleeding-related mortality as the competing event (“CAT-BLEED”). Results Data of 1,046 patients (149 events) were analyzed. Predictive performance of existing risk scores was poor to moderate (C-statistics: 0.50–0.57; poor calibration). Internal validation of the pragmatic classification and “CAT-BLEED” showed moderate performance (respective C-statistics: 0.61; 95% confidence interval [CI]: 0.56–0.66, and 0.63; 95% CI 0.58–0.68; good calibration). Conclusion Existing risk scores for bleeding perform poorly after CAT. Pragmatic classification based on cancer type provides marginally better estimates of clinically relevant bleeding risk. Further improvement may be achieved with “CAT-BLEED,” but this requires external validation in practice-based settings and with other DOACs and its clinical usefulness is yet to be demonstrated.

Bleeding Risk Assessment in End-Stage Kidney Disease: Validation of Existing Risk Scores and Evaluation of a Machine Learning-Based Approach

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Cancer Histology and Natural History of Patients with Lung Cancer and Venous Thromboembolism

“…Of note, patients with squamous lung cancer presented with a higher prevalence of anemia, and thrombocytopenia, and they were on antiplatelet treatment more frequently than patients with adenocarcinoma. These variables might imply an increased risk of major bleeding events [ 20 ].…”

Unanswered questions in cancer‐associated thrombosis

“…The most complex step in the algorithm is the assessment of bleeding risk. A number of risk assessment models have been evaluated for predicting risk of anticoagulant‐related bleeding in patients with cancer‐associated VTE but none have performed well 33 . Despite the lack of a validated model, risk assessment based on well‐established risk factors for bleeding is helpful to guide the choice of therapy when starting anticoagulation.…”