The CRUSADE Bleeding Score to Assess Baseline Risk of Major Bleeding in Non – ST-Segment Elevation Myocardial Infarction

1. The CRUSADE Bleeding Score to Assess Baseline Risk of Major Bleeding in Non–ST-Segment Elevation Myocardial Infarction Sumeet Subherwal, Richard G. Bach, Anita Y. Chen, Brian F. Gage, Sunil V. Rao, Tracy Y. Wang, W. Brian Gibler, E. Magnus Ohman, Matthew T. Roe, Eric D. Peterson, Karen P. Alexander

2. Author Disclosure Sumeet Subherwal, MD,1 Richard G. Bach, MD,1 Anita Y. Chen, MS,1 Brian F. Gage, MD, MSc,1 Sunil V. Rao, MD,1 Tracy Y. Wang, MS,1 W. Brian Gibler, MD,2 E. Magnus Ohman, MD,2 Matthew T. Roe, MD, MHS,2 Eric D. Peterson, MD, MPH,3 Karen P. Alexander, MD,4 1No relationships to disclose 2Research grants from Bristol-Myers Squibb/Sanofi Pharmaceuticals Partnership and Schering Corporation 3Research grants from Bristol-Myers Squibb, Bristol-Myers Squibb/Sanofi Pharmaceuticals Partnership; Bristol-Myers Squibb/Merck and Bristol-Myers Squibb/Merck 4Research grants from CV Therapeutics, Honoraria from Schering Plough and Pfizer

3. Background • Treatment with antithrombotics and catheter-based interventions reduces ischemic events in patients with non–ST-segment elevation myocardial infarction (NSTEMI) but at an increased risk of major bleeding • Major bleeding is associated with worse clinical outcomes • Given the impact of both safety (bleeding) and efficacy (ischemia) on patient outcomes, global risk stratification may enhance patient management

4. Background • Validated risk stratification tools predict baseline risk of ischemic events • TIMI, PURSUIT, GRACE ACS Risk Score • Current estimation of baseline risk of bleeding in NSTEMI is difficult because existing risk stratification tools: • include treatment variables (i.e. antithrombotics or invasive procedures) • derived from highly selected patient populations

5. Purpose To develop and validate a risk prediction tool for estimation of baseline risk of in-hospital major bleeding in patients with NSTEMI.

6. Methods • CRUSADE Quality Improvement Initiative • February 15, 2003 to December 31, 2006 • n=89,134 NSTEMI patients at 485 US hospitals • Excluded unstable angina, home warfarin, transfer out, deaths within 48 hours • In-hospital Major Bleeding • Absolute HCT drop of ≥ 12% (Baseline HCT - Nadir HCT ≥ 12%) • Intracranial hemorrhage • Witnessed retroperitoneal bleed • RBC transfusion when Baseline HCT ≥ 28% • RBC transfusion when Baseline HCT < 28% with witnessed bleed • Major bleeding censored at time of CABG

7. Statistical Analysis • Randomly assigned into derivation (n=71,277, 80% of total N) and validation cohorts (n=17,857, 20% of total N) • Explored univariate relationships between potential predictors and the outcome of major bleeding • Incorporated variables with a clinically important and statistically significant univariate association with major bleeding into a multivariable model • Logistic generalized estimating equations (GEE) method accounted for in-hospital clustering • The predictive performance of the model was assessed by calculating c-statistics and comparing observed vs. predicted probability plots

8. Baseline Characteristics *Median (25th, 75th percentile) †Prior vascular disease defined as h/o stroke or peripheral arterial disease ‡ Creatinine clearance as estimated by Cockcroft-Gault Formula

9. Multivariable Predictors of Bleeding Prior vascular disease defined as h/o stroke or peripheral arterial disease Note: Heart rate is truncated @ <70 bpm; CrCl: Cockcroft-Gault is truncated @ >90 mL/min

10. CRUSADE Bleeding Score • The CRUSADE Bleeding Score was developed by assigning a weighted integer to each independent predictor based on the predictor’s coefficient in the reduced regression model • The CRUSADE Bleeding Score equals the sum of the weighted integers for the independent predictors • Range 1-100 points

11. CRUSADE Bleeding Score Nomogram Note: Heart rate is truncated @ <70 bpm; CrCl: Cockcroft-Gault is truncated @ >90 mL/min; Prior Vascular disease is defined as prior PAD or stroke

12. Risk of Major Bleeding Across the Spectrum of CRUSADE Bleeding Score p<0.001 for trend; Derivation: C=0.71 Validation: C=0.70

13. Risk Quintiles • Patients were categorized into quintiles of risk groups based on their CRUSADE Bleeding Score

14. Subgroup Analysis • Performance of the Bleeding Score was tested across four treatment subgroups in the derivation cohort defined by in-hospital antithrombotics and invasive care: • ≥2 Antithrombotic medications (anti-platelet [aspirin or clopidogrel], anti-coagulant, or GP IIb/IIIa inhibitors) (n=50,969) • <2 Antithrombotic medications (anti-platelet, anti-coagulant, or GP IIb/IIIa inhibitors) (n=5,931) • Cardiac catheterization (n=52,048) • No cardiac catheterization (n=6,407)

15. <2 Antithrombotics 2 or more Antithrombotics Rate of Major Bleeding in <2 Antithrombotics vs. 2 or more Antithrombotics 25 19.9 20 15 13.5 12.0 Major Bleeding (%) 10 8.4 6.7 5.5 5.3 5 3.1 2.6 1.9 0 Very Low Low Moderate High Very High Risk Of Bleeding p<0.001 testing for trend Note: Anti-thrombotic defined as (anti-platelet [aspirin or clopidgorel], anti-coagulant, or GP IIb/IIIa inhibitors)

16. No Catheterization Catheterization Rate of Major Bleeding in Catheterization vs. No Catheterization 25 23.1 20 15.1 15 13.3 Major Bleeding )%) 10 8.7 7.2 6.6 5.5 4.6 5 3.1 2.6 0 Very Low Low Moderate High Very High Risk Of Bleeding p<0.001 testing for trend

17. Limitations • Only baseline factors were considered in development of the CRUSADE Bleeding Score • C-index would have been higher if we included post admission treatments and their contribution to risk • History of prior bleeding or bleeding diathesis was not collected • Did not capture bleeding events: • Excluded patients that died within 48 hours • Censored bleeding at the time of CABG

19. Conclusion • The CRUSADE Bleeding Score combines 8 predictors of major bleeding into a simple validated prediction tool that estimates baseline risk of in-hospital major bleeding in patients with NSTEMI • Preserved discrimination across treatment subgroups • Complements ischemic risk prediction tools to better enable clinicians to consider all the potential adverse outcomes in patients with NSTEMI prior to initiation of therapy