Why are the Risks Factors for
Recurrent Events the Same as
the Risk Factors for Bleeding?
Kenneth W. Mahaffey, MD
Professor of Medicine, Cardiology
Associate Director, Duke Clinical Research Institute
Director, DCRI MegaTrials & CEC
Hemostasis and Thrombosis
Red
Blood
Cells
Platelet
aggregate
Fibrin
Atherosclerotic
Plaque

Pathobiology is
complex

Understanding
relationships is
important

More bleeding
with more
therapies

Balance is
critical
Efficacy vs Safety
Paradigm for Antithrombotic Drug Development
“First, do no harm.”
Hemorrhagic Risk
2
Hippocrates, c 460-370 BC
Increase
ASA

New drugs

Old drugs with new
doses

Old drugs in new
combinations

Combination of
drugs and devices

New drugs and new
devices
1
Goal of New Rx
0
0
Decrease
1
Risk of Thrombosis
2-
Therapies Always Cause a Combination of:
  
Good Effects
 
Bad Effects
Adapted from Furberg, personal slides
Risk Scores
What are they good for……..
Predicting risk
Guiding therapy
Populations
STEMI
NSTE-ACS
AF
DVT/PE
Heart Failure
PCI
CABG
Endpoints
Mortality
Death/MI
Revascularization
Bleeding
Stroke/SE
DVT/PE
Sudden Death
Variables
Clinical
Laboratory
Electrocardiography
Imaging
“Omics”
Statistical Approaches
Univariable
Multivarible
Courtesy, Lopes RD
Stroke Risk in Atrial Fibrillation
AFI
Age >65, h/o TIA/CVA, DM, HTN
If no RF, annual stroke risk <1%
C-Indices*:
AFI: 0.68
SPAF: 0.74
CHADS2: 0.82
CHADS-VASC: 0.61
SPAF
Women >75, h/o TIA/CVA, systolic dysfxn,
SBP >160
CHADS2
CHF, HTN, age ≥75, DM, stroke/ embolic
event
CHADS-VASc
CHF, HTN, age ≥75, DM, h/o
TIA/CVA/embolic event, age ≥75, vascular
dz, female
*In origination cohort
Risk of Hemorrhage with Anticoagulant Therapy
in AF Patients
Pisters R. Euro Heart Survey 2010
Correlation between CHADS2 and
HAS-BLED scores
HAS-BLED
CHADS2
0–1
2
≥3
1
3203
(18%)
2051
(11%)
929
(5%)
2
2807
(15%)
2461
(14%)
1248
(7%)
≥3
1451
(8%)
2056
(11%)
1995
(11%)
Data presented at number (%).
Modified from Lopes RD, et al. Lancet 2012
Mortality Risk Tertiles
Major Bleeding and Mortality Risk in CRUSADE
High
1%
8%
23.5%
(5,199)
(16,044)
9%
15%
8%
(6,403)
(10,320)
(5,762)
23%
10%
2%
(706)
Mod
Low
(15,974)
Low
(6,748)
(1,114)
Mod
High
Bleeding Risk Tertiles
Alexander KA, et. al. ACC 2008
Bleeding and Mortality
Giugliano, JACC 2012
Benefits and Harm: A Complex Interaction
Alexander KA, Circulation 2010
Renal Dysfunction a Potent Predictor
ROCKET AF: R2CHADS2
Piccini, AHA 2011, Abstract
Rapid Evolution
New Agents
PAR-1
P2Y12
Factor Xa
Others …..
The Sweet Spot for Anticoagulation
Patient
Risks
Clinical
Context
Dose
Conclusions

Human disease is complex and multifactorial

Identification of effective and safe therapies requires
testing in the clinical environment

Current risk scores for bleeding and ischemic
events:
 Have common predictors
 Limited by missing of likely key factors
 genetic, instrumental, environmental

Urgent work is needed to better understand the
factors associated with ischemic and bleeding
events to:
 Improve clinical decision making
 Focus further drug development