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Author Spotlight: Advancing Cancer Associated Thrombosis Research in Rodent Models
Published on: January 5, 2024
Estimating Bleeding Risk in Patients with Cancer-Associated Thrombosis: Evaluation of Existing Risk Scores and
Maria A de Winter1, Jannick A N Dorresteijn2, Walter Ageno3
1Department of Acute Internal Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.
Insights
Existing bleeding risk scores perform poorly in cancer-associated thrombosis (CAT). A new model, "CAT-BLEED," shows promise but needs further validation for clinical use in CAT patients.
Area of Science:
- Hematology
- Oncology
- Clinical Epidemiology
Background:
- Assessing bleeding risk is crucial for managing cancer-associated thrombosis (CAT).
- Current bleeding risk scores lack validation in CAT patients and are not recommended for clinical practice.
- Effective risk stratification is needed to guide treatment decisions and improve patient outcomes.
Purpose of the Study:
- To compare the predictive performance of existing venous thromboembolism (VTE) bleeding risk scores, a pragmatic cancer type classification, and a novel prediction model for clinically relevant bleeding in CAT patients.
- To evaluate the utility of established risk scores and propose improved methods for bleeding risk estimation in this specific population.
Main Methods:
- A posthoc analysis of the Hokusai VTE Cancer study involving 1,046 patients treated for CAT.
- External validation of seven existing bleeding risk scores (ACCP-VTE, HAS-BLED, Hokusai, Kuijer, Martinez, RIETE, VTE-BLEED).
- Comparison with a pragmatic classification based on cancer type and a newly derived competing risk-adjusted prediction model ('CAT-BLEED').
Main Results:
- Existing risk scores demonstrated poor to moderate predictive performance (C-statistics: 0.50-0.57) with poor calibration.
- The pragmatic classification and the 'CAT-BLEED' model showed moderate internal validation performance (C-statistics: 0.61 and 0.63, respectively) with good calibration.
- 149 clinically relevant bleeding events were analyzed within 6 months post-CAT diagnosis.
Conclusions:
- Established bleeding risk scores are inadequate for patients with cancer-associated thrombosis (CAT).
- A pragmatic classification based on cancer type offers marginal improvement in risk prediction.
- The novel 'CAT-BLEED' model shows potential but requires external validation and demonstration of clinical utility with various direct oral anticoagulants (DOACs).
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.
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