Transcript Slides - Clinical Trial Results

Importance of Bleeding in Patients with
Cardiovascular Disease
Roxana Mehran, MD, FACC, FAHA, FESC, FSCAI
Professor of Medicine
Director, Interventional Cardiovascular Research
and Clinical Trials
Mount Sinai School of Medicine
Disclosure Statement of Financial Interest
Within the past 12 months, I or my spouse/partner have had a financial
interest/arrangement or affiliation with the organization(s) listed below.
Affiliation/Financial Relationship
Company
• Grant/Research Support
• Sanofi/BMS- Significant
• Consulting Fees/Honoraria
• Astra Zeneca, Cardiva,
Cordis, The Medicines
Company, Regado
Biosciences
Impact of Therapies on Outcomes
Ischemic events:
MI/CKMB↑
Stent Thrombosis
Bleeding
Bleeding and Mortality
Major Bleeding
Hypotension
Cessation of
ASA/Clop
Transfusion
Ischemia
Stent Thrombosis
Inflammation
Mortality
Bhatt DL. In Braunwald EB, Harrison’s
Online. 2005.
Impact of In-hospital Bleeding in ACS
34,146 Pts with ACS in the OASIS-1/2 and CURE
Major bleeding occurred in 2.3% of pts
Mortality (%)
12
12.8%
P<0.0001
10
Bleeding
8
6
4
2.5%
2
Landmark analysis, 1-6 mo
8
Mortality (%)
First 30 days
14
P=0.002
6
4.6%
4
Bleeding
2.9%
2
No bleeding
No bleeding
0
0
0
5
10
15
20
25
30
0
Days
No. at Risk
No bleeding 33376 33419 33157 32990 32879 32769 32710
Bleeding
470
459
440
430
420
410
408
Adj. HR [95%CI] = 5.37 [3.97, 7.26]
P<0.0001
30
60
90
120
150
180
Days
32634
560
32491 32161 31981 31166 30316 29238
559
554
548
533
519
489
Adj. HR [95%CI] = 1.54 [1.02, 2.36]
P=0.047
Eikelboom JW. Circulation 2006;114:774–782
Impact of Major Bleed and MI after
Elective and Urgent PCI
Cumulative % Mortality
1-Year Mortality (N=6,012)
With major bleed 8.8%
With MI 5.7%
Without major bleed 2.0%
Without MI 1.9%
Time from Randomization in Days
Stone GW. J Inv Cardiol 2004;16(suppl G):12–17.
Impact of 30 Day Adverse Events
on 1-Year Mortality after PCI
ISAR REACT-1, -2, -SWEET, -SMART-2 (n=5,384)
Cox model relating 30 day events to mortality at 1 year
Variable
Bleeding w/i 30 days
MI w/i 30 days
Urgent revasc w/i 30 days
Age (per 10 yrs)
Diabetes
MVD
↑ Troponin
LVEF
Creatinine (per 0.25 mg/dl ↑)
HR (95% CI)
2.96 (1.96–4.48)
2.29 (1.52–3.46)
2.49 (1.16–5.35)
2.27 (1.78–2.89)
1.47 (1.11–1.96)
2.72 (1.58–4.67)
1.77 (1.27–2.47)
0.71 (0.60–0.85)
1.10 (1.06–1.14)
P
0.001
0.001
0.02
0.001
0.008
0.001
0.001
0.001
0.001
Ndrepepa et al. JACC 2008;51:690–7
ACUITY: Influence of Major Bleeding and MI in
the First 30 Days on Risk of Death Over 1 Year
Of 13,819 enrolled pts, 524 (3.8%) died within 1 year
Cox model adjusted for 36 baseline predictors, with MI and
major bleeding (non-CABG) as time-updated covariates
HR ± 95% CI
HR (95% CI)
P-value
Myocardial infarction
2.51 (1.95-3.25) <0.0001
Major bleeding without
or before transfusion
2.00 (1.30-3.06) <0.0001
Major bleeding after
transfusion
3.93 (2.95-5.24) <0.0001
Mehran RM et al. EHJ 2009;30:1457-66
ACUITY: Influence of Major Bleeding and MI in
the First 30 Days on Risk of Death Over 1 Year
Of 13,819 enrolled pts, 524 (3.8%) died within 1 year
Cox model adjusted for 36 baseline predictors, with MI and
major bleeding (non-CABG) as time-updated covariates
HR ± 95% CI
HR (95% CI)
Attributable
deaths
P-value
Myocardial infarction
2.51 (1.95-3.25) <0.0001
Major bleeding without
or before transfusion
2.00 (1.30-3.06) <0.0001
Major bleeding after
transfusion
51.5*
66.5**
3.93 (2.95-5.24) <0.0001
*9.8% of all deaths
**12.7% of all deaths
Attributable deaths = N deaths
among pts with the time updated
event (attribute) X (adj. HR – 1)/adj. HR
Mehran RM et al. EHJ 2009;30:1457-66
Influence of MI, Major Bleed and Transfusion in the
First 30 Days on the Risk of Death Over 1 Year
HR (95% CI)
P-value
Day 0-1
Days 2-7
17.6 (10.8 to 28.7)
8.2 (5.0 to 13.6)
<0.001
<0.001
Attributable
deaths
21
19
Days 8-30
2.9 (1.6 to 5.3)
0.001
12
Days 31+
1.4 (0.9 to 2.1)
0.12
25
Major bleed
Day 0-1
5.5 (2.7 to 11.0)
<0.001
9
(non CABG)
Days 2-7
5.8 (3.5 to 9.7)
<0.001
18
Days 8-30
5.6 (3.5 to 8.8)
<0.001
24
Days 31+
2.4 (1.7 to 3.3)
<0.001
42
Day 0-1
6.7 (3.1 to 14.7)
<0.001
7
Days 2-7
8.1 (4.6 to 14.1)
<0.001
15
Days 8-30
6.4 (3.7 to 10.9)
<0.001
17
Days 31+
3.1 (2.1 to 4.5)
<0.001
31
MI
Transfusion
0.5 1 2 4 8 16 32
Hazard ratio (95% CI)
Attributable deaths = N deaths
among pts with the time updated
event (attribute) X (adj. HR – 1)/adj. HR
Mehran RM et al. EHJ 2009;30:1457-66
ACUITY (N=13,819)
Impact of MI and Major Bleeding in the First
30 Days on Risk of Death Over 1 Year
25
1 year
Patients with Major Bleed (N=645)
Mortality (%)
20
Estimate
14.9%
Patients with MI (N=705)
11.4%
Patients w/o Major Bleed (N=13,168)
3.6%
Patients w/o MI (N=13,108)
3.8%
15
14.9%
11.4%
10
3.8%
3.6%
5
0
0
30
60
90
120
150
180
210
240
270
Days from Randomization
300
330
360
390
ACUITY
Costs of In-hospital Complications
Pinto DS et al. JACC 2008;52;1758-1768
Harmonizing Outcomes with Revascularization and Stents in AMI
3602 pts with STEMI with symptom onset ≤12 hours
Aspirin, thienopyridine
R
1:1
UFH + GP IIb/IIIa inhibitor
(abciximab or eptifibatide)
Bivalirudin monotherapy
(± provisional GP IIb/IIIa)
Emergent angiography, followed by triage to…
CABG – Primary PCI – Medical Rx
3006 pts eligible for stent randomization
R
3:1
Paclitaxel-eluting TAXUS stent
Bare metal EXPRESS stent
Clinical FU at 30 days, 6 months, 1 year, and then
yearly through 5 years; angio FU at 13 months
HORIZONS: Time-updated covariate adjusted Cox
model relating MACE events to 1-year mortality
- Complete model with MACE components and major bleeding HR (95% CI)
Risk Factor
HR [95% CI]
Reinfarction
Incidence 138 (3.8%)
16 deaths after event
3.94
[1.73, 8.96]
Major bleeding
(non CABG)
Incidence 268 (7.4%)
44 deaths after event
0.1
3.39
[2.29, 5.03]
1
10
Hazard Ratio [95% CI]
Attributable deaths = N deaths among pts with the
time updated event (attribute) X (adj. HR – 1)/adj. HR
P-value
Attributable
Deaths
0.001
12*
[7, 14]
<0.0001
[25, 35]
31**
*8.2% of 147 total deaths
**21.1% of 147 total deaths
HORIZONS-AMI: Influence of Non-CABG Major
Bleed and MI on the Risk of Death Over 1 Year
HR [95% CI] Attributable P-value
Deaths (%)
MI Day 0-2
20.3 [8.2,50.7]
5
<0.001
Day 3-7
21.9 [7.8,61.0]
4
<0.001
Day 8-30
4.8 [1.2,19.8]
2
0.03
Day >30
1.3 [-0.2, 9.3]
1
0.80
Major Bleed Day 0-2
(non-CABG) Day 3-7
6.7 [3.0,15.1]
7
<0.001
19.9 [9.3,42.4]
10
<0.001
Day 8-30
7.4 [3.7,14.9]
11
<0.001
Day >30
5.5 [3.0,10.2]
14
<0.001
0.1
1.0
10.0
Hazard Ratio [95% CI]
Attributable deaths = N deaths among pts with the
time updated event (attribute) X (adj. HR – 1)/adj. HR
100.0
HORIZONS: 30 Day Adverse Events
30 day event rates (%)
12
Heparin + GPIIb/IIIa inhibitor (N=1802)
Bivalirudin monotherapy (N=1800)
P<0.001
10
8.3
8
6
4.9
P = 0.90
4
2
1.8
1.8
0
Reinfarction
*Not related to CABG
** Plat cnt <100,000 cells/mm3
Major bleeding*
Stone GW et al. NEJM 2008;358:2218-30
HORIZONS: 1-Year All-Cause Mortality
Bivalirudin alone (n=1800)
5
4.8%
Heparin + GPIIb/IIIa (n=1802)
Δ = 1.4%
Mortality (%)
4
3.4%
3
3.1%
2
2.1%
HR [95%CI] =
0.69 [0.50, 0.97]
Δ = 1.0%
P=0.049
1
P=0.029
0
0
1
2
3
4
5
6
7
8
9
10
11
12
Time in Months
Number at risk
Bivalirudin alone
Heparin+GPIIb/IIIa
1800
1802
1705
1678
1684
1663
1669
1646
Mehran R et al. Lancet 2009:on-line
1520
1486
30 Day Stent Thrombosis
(N=3,124 successfully stented pts)
UFH +
Bivalirudin
P
GP IIb/IIIa
(N=1571) Value
(N=1553)
ARC 30d definite or
probable stent thrombosis*
1.9%
2.5%
0.30
- definite
1.4%
2.2%
0.09
- probable
0.5%
0.3%
0.24
- acute (≤24 hrs)
0.3%
1.3%
0.0007
- subacute (>24 hrs – 30d)
1.7%
1.2%
0.28
*Protocol definition
of stent thrombosis,
CEC adjudicated
Stone GW et al. NEJM 2008;358:2218-30
Time-updated covariate adjusted Cox model
relating 30-day events to 30-day mortality
- Complete model in 3,124 pts with successfully implanted stents Attributable
Risk Factor
HR [95% CI]
Stent thrombosis
(definite)
Incidence 57 (1.8%)
10.62
[3.96, 28.48]
P-value
<0.001
Deaths
4.5*
[3.7, 4.8]
5 deaths with event
Major bleeding
(non CABG)
Incidence 195 (6.2%)
6.22
[3.33, 11.60]
<0.001
15.1**
[12.6, 16.4]
18 deaths with event
0.01
0.1
1
10
Hazard Ratio [95% CI]
100
*8.3% of 54 total deaths
**28.0% of 54 total deaths
C-statistic = 0.87. Attributable deaths = N deaths among pts
with the time updated event (attribute) X (adj. HR – 1)/adj. HR
Publication of Primary Results
NEJM 357: 2001-2015, 2007
www.NEJM.org
Wiviott SD, et al. N Engl J Med 2007;357:2001–15
TRITON TIMI 38: Study Design
ACS (STEMI or UA/NSTEMI) & Planned PCI
N= 13,600
ASA
Double-blind
CLOPIDOGREL
300 mg LD/ 75 mg MD
PRASUGREL
60 mg LD/ 10 mg MD
Median duration of therapy – 12 months
1o endpoint:
2o endpoints:
CV death, MI, Stroke
CV death, MI, Stroke, Rehosp-Rec Isch
CV death, MI, UTVR
Stent Thrombosis (ARC definite/prob.)
Safety endpoints: TIMI major bleeds, Life-threatening bleeds
Key Substudies: Pharmacokinetic, Wiviott
Genomic
SD, et al. N Engl J Med 2007;357:2001–15
Primary Endpoint CV Death,MI,Stroke
Primary Endpoint (%)
15
Clopidogrel
12.1
(781)
9.9
(643)
10
Prasugrel
HR 0.81
(0.73-0.90)
P=0.0004
NNT= 46
HR 0.80
P=0.0003
5
HR 0.77
P=0.0001
ITT= 13,608
0
0 30 60 90
180
LTFU = 14 (0.1%)
270
360
450
Days Wiviott SD, et al. N Engl J Med 2007;357:2001–15
Stent Thrombosis
(ARC Definite + Probable)
3
Any Stent at Index PCI
N= 12,844
Endpoint (%)
Clopidogrel
2.4
(142)
2
1.1
(68)
1
Prasugrel
HR 0.48
P <0.0001
NNT= 77
0
0 30 60 90
180
270
Days
360
450
Wiviott SD, et al. N Engl J Med 2007;357:2001–15
Balance of Efficacy and Safety
15
138
events
Clopidogrel
12.1
Endpoint (%)
CV Death / MI / Stroke
9.9
10
HR 0.81
(0.73-0.90)
P=0.0004
NNT = 46
Prasugrel
5
TIMI Major
NonCABG Bleeds
0
0 30 60 90
180
Prasugrel
2.4
HR 1.32
1.8 (1.03-1.68)
Clopidogrel
P=0.03
270
Days
35
events
360
450
NNH = 167
Wiviott SD, et al. N Engl J Med 2007;357:2001–15
PLATO: K-M estimate of time to
first primary efficacy event
(Composite of CV death, MI or stroke)
Cumulative incidence (%)
Completeness of follow-up 99.97% = five patients lost to follow-up
13
12
11
10
9
8
7
6
5
4
3
2
1
0
Clopidogrel
11.7
9.8
Ticagrelor
HR 0.84 (95% CI 0.77–0.92), p=0.0003
0
60
120
180
240
300
360
Days after randomisation
No. at risk
Ticagrelor
9,333
8,628
8,460
8,219
6,743
5,161
4,147
Clopidogrel
9,291
8,521
8,362
8,124
6,743
5,096
4,047
K-M = Kaplan-Meier; HR = hazard ratio; CI = confidence interval
Wallentin et al. N Engl J Med. 2009 Sep 10;361(11):1045-57
PLATO: K-M estimates of time to
primary safety event
(Major Bleeding)
Cumulative incidence (%)
Completeness of follow-up 99.97% = five patients lost to follow-up
15
Ticagrelor
10
Clopidogrel
11.58
11.20
5
HR 1.04 (95% CI 0.95–1.13), p=0.434
0
0
60
120
180
240
300
360
Days from first IP dose
No. at risk
Ticagrelor
9,235
7,246
6,826
6,545
5,129
3,783
3,433
Clopidogrel
9,186
7,305
6,930
6,670
5,209
3,841
3,479
Wallentin et al. N Engl J Med. 2009 Sep 10;361(11):1045-57
Definitions of Major Bleeding in
Clinical Trials: Main Components








Clinical Events
Laboratory Parameters
Intracranial / intracerebral
bleeding
Intraocular bleeding
Bleeding causing
hemodynamic compromise
Cardiac tamponade
Retroperitoneal hematoma
Hematoma
Surgical intervention for
bleeding
Blood product transfusion

Decrease in Hgb ≥3 g/dL
with overt source of
bleeding
 Decrease in Hgb ≥4 g/dL
w/o overt source of
bleeding
 Decrease in Hgb ≥5 g/dL
with or w/o overt source of
bleeding
 Decrease in Hct ≥15% with
overt source of bleeding
Definitions of Major/Severe Bleeding
in Randomized Controlled Clinical Trials
GUSTO
TIMI
phase I
TIMI
phase II
REPLACE-2
OASIS-5
ESSENCE
CURE
STEEPLE
ACUITY
HORIZONS
PLATO
Intracranial/intracerebral
+
+
+
+
+
+
+
+
+
Intraocular
-
-
-
+
+
+
+
+
+
Retroperitoneal
-
-
-
+
+
+
+
+
-
Bleeding causing
hemodynamic
compromise
+
-
-
-
-
+
+
-
+
Cardiac tamponade
-
+
+
-
-
-
-
-
+
Bleeding requiring
surgical intervention
-
-
-
-
-
+
+
+
+
Hematoma >5cm at the
puncture site
-
-
-
-
-
-
-
+
-
≥1
≥1
≥1
≥2
≥2
≥2
≥1
≥1
≥4
Decrease in Hgb with
overt bleeding, g/dL
-
≥5.0*
≥3.0
≥3.0
≥3.0
-
≥3.0
≥3.0
≥5.0
Decrease in Hgb without
overt bleeding, g/dL
-
-
-
≥4.0
-
≥5.0
-
≥4.0
-
Type of bleeding
Transfusion, units
*Or decrease in Hct ≥15%
Bleeding Definitions
TIMI Major
Bleeding with >5 g/dL fall in hgb
Intracranial bleeding
Intraocular bleeding
Access site bleed requiring intervention
≥ 5 cm hematoma at puncture site
Reoperation for bleeding
ACUITY
and HORIZONS
Major Bleeding
Blood product transfusion
Hgb  ≥3g/dL with an overt source
TIMI Minor
Hgb  ≥4g/dL w/o overt source
Retroperitoneal bleeding
Gross hematuria or hematemesis
Rao AK et al. JACC 1988;11:1-11; Stone GW et al. NEJM 2006;355:2203-16
Hierarchical Incidence of Major Bleeding†
Within 30 Days After PCI
REPLACE-2
(N=5894)
ACUITY
(N=7760)
HORIZONS
Total
(N=3348) (n=17,002*)
TIMI major bleed
35 (0.6%)
135 (1.7%)
79 (2.4%)
249 (1.5%)
ACUITY major (non TIMI
major) bleed with blood
transfusion**
81 (1.4%)
120 (1.5%)
41 (1.2%)
242 (1.4%)
ACUITY major (non TIMI
major) bleed without
blood transfusion**
73 (1.2%)
125 (1.6%)
95 (2.8%)
293 (1.7%)
Large hematoma only
100 (1.7%)
82 (1.1%)
13 (0.4%)
195 (1.1%)
Total
289 (4.9%)
462 (6.0%)
228 (6.8%)
979 (5.8%)
* Excluding patients with any bleed prior to the PCI ; ** Excluding hematomas if the only criteria
† Not related to CABG. Each patient is represented only once according to their most severe bleed
Influence of Bleeding Severity within 30 Days After PCI
on the Risk of Death Over 1 Year
Baseline covariate-adjusted time-updated Cox multivariable model
HR (95% CI)
Pvalue
Attributable
deaths
within 1 yr
TIMI major bleed
4.85 (3.56-6.60)
<0.001
53
ACUITY major (non TIMI
major) bleed with
transfusion*
2.98 (2.10-4.24)
<0.001
40
ACUITY major (non TIMI
major) bleed without
transfusion*
1.79 (1.09-2.93)
0.02
17
Hematoma ≥5 cm only
1.30 (0.58-2.92)
0.53
6
Type of Bleed
HR (95%CI)
Mehran, et al. JACC Int 2011- In-Press
* Excluding hematomas if the only criteria
Each patient is represented only once according to their most severe bleed
How Does Access Site Impact Major
Bleeding Rates in PCI Patients?
• Meta-analysis of 18 randomized trials (5 had no
bleeding events) of femoral versus radial access
involving 4,458 patients undergoing angiography or
PCI
Major Bleeding
Radial access reduced
major bleeding by
73%, with a trend for
reductions in the
composite of death,
MI, or stroke (2.5%
vs 3.8%, P = .058)
Jolly SS. Am Heart J 2009;157:132-40.
Percent Protocol Major Bleed
Non-CABG Major Bleeding in
PCI-Treated ACS Patients
7
6
5
88%
Femoral
Access
84%
Radial
Access
3.7
3.7
OASIS 5
9 Days
ABOARD
30 Days
4
3
5.9
2
3.1
1
0.67
1.2
0
ACUITY
30 Days
TRITON
3 Days
EARLY ACS SYNERGY
120 hours
30 Days
Sources and Incidence of Bleeding
Among 17,393 PCI Patients
No Location
Both
Non-Access Site Only
Access Site Only
6
5.3% (n=925)
5.2%
Percentage (%)
5
1.5
1.6 (281)
0.5
0.8 (142)
4
3
0.7
0.8 (145)
1.6%
2
1
Non- access
site bleeds
3.3% are 61.4% of
TIMI bleeding
events
2.5
0.5
0.2
0.2
0.7
Protocol Major
TIMI Major
0
2.1
2.1%
Access site
only accounts
for 38.6%
TIMI Major + Minor
Verheugt JACC Cardio Interv 2011;4:191-7:
Incidence and source of bleeding
excluding access site
50
45.2
45
40
35
% of Patients
30
25
20
17.9
15
15
10.1
10
6.9
3.7
5
0.9
Axis Title
Other
No
Location
Head/Neck Pulmonary ICH
Other
Intracrani
al
Pulmonar
y
GI
Head and
Neck
GU
GI
GU
0
No site
Verheugt JACC Cardio Interv 2011;4:191-7:
Relative Risk of 1-year Mortality Associated
with Bleeding and Source (unadjusted)
P<0.0001 for all bleeding versus none
6.0
Relative Risk 1-Year Mortality
5.7
5.0
5.5
5.2
5.4
4.0
3.0
2.0
2.3
1.0
0.0
Access Only
Both
Non-Access
Only
No Location
All Non-Access
Verheugt JACC Cardio Interv 2011;4:191-7:
Risk for 1 year mortality
● 1-year mortality risk from non-access site bleeding vs access site =
HR 2.27 (95%CI 1.42-3.64), p=0.0007
Relative Risk
P-Value
Unadjusted
Access site
2.33 (1.53 – 3.53) <0.0001
Non-access site
5.40 (4.32 – 6.74) <0.0001
Hazard ratio
Adjusted
Access site
1.82 (1.17–2.83)
0.008
Non-access site
3.94 (3.07–5.15) <0.0001
0 1 2 3 4 5 6 7
No Bleed
TIMI Major + Minor Bleed
Verheugt JACC Cardio Interv 2011;4:191-7:
Impact of Antithrombotic Therapy on
Bleeding by Source
Relative Risk
P-Value
Access Only
0.45 (0.35-0.59)
<0.0001
Both
0.31 (0.19-0.49)
<0.0001
Non Access Only
0.70 (0.47-1.05)
0.08
No Location
0.75 (0.58-0.96)
0.02
All non-access
0.62 (0.51-0.75)
<0.0001
TIMI Major + Minor Bleeding
0
0.5
1
Bivalirudin better
1.5
2
Hep + GPI better
Verheugt JACC Cardio Interv 2011;4:191-7:
Impact of Randomized Antithrombotic
Therapy on TIMI Bleeding by Location
Hep +
GPI (%)
0.04
Bivalirudi
n (%)
0.03
0.66 (0.11-3.97)
GI
0.64
0.28
0.44 (0.26-0.74)
GU
0.64
0.28
0.44 (0.26-0.74)
NEENT
0.33
0.22
0.66 (0.35-1.24)
Pulmonary
0.18
0.05
0.31 (0.10-0.94)
Other
0.3
0.15
0.49 (0.24-1.01)
No location bleed
2.82
1.83
0.65 (0.52-0.80)
All Non-Access
3.66
2.27
0.62 (0.51-0.75)
Intracranial
0
0.5
1
Bivalirudin better
1.5
Relative Risk
2
Hep + GPI better
Verheugt JACC Cardio Interv 2011;4:191-7:
Standardized Bleeding Definitions for
Cardiovascular Clinical Trials: A Consensus
Report from the Bleeding Academic
Research Consortium (BARC)
•
Roxana Mehran, MD, Sunil V. Rao, MD, Deepak L. Bhatt,
MD, MPH, C. Michael Gibson, MS, MD, Adriano Caixeta,
MD, PhD, John Eikelboom, MD, MBBS, Sanjay Kaul, MD,
Stephen D. Wiviott, MD, Venu Menon, MD, Eugenia
Nikolsky, MD, PhD, Victor Serebruany, MD, PhD, Marco
Valgimigli, MD, PhD, Pascal Vranckx, MD, David Taggart,
MD, PhD, Joseph F. Sabik, MD, Donald E. Cutlip, MD,
Mitchell W. Krucoff, MD, E. Magnus Ohman, MD, Philippe
Gabriel Steg, MD, and Harvey White, MB ChB DSc
Circulation 2011 In-press
BARC
• Type 0: No evidence of bleeding.
• Type 1: Bleeding that is not actionable and
does not cause the patient to seek unscheduled
performance of studies, hospitalization, or
treatment by a health care professional.
Examples include, but are not limited to,
bruising, hematoma, nosebleeds, or
hemorrhoidal bleeding for which the patient
does not seek medical attention. Type I
bleeding may include episodes that lead to
discontinuation of medications by the patient
because of bleeding without visiting a health
care provider.
Circulation 2011 In-press
BARC
• Type 2: Any clinically overt sign of hemorrhage (e.g., more
bleeding than would be expected for a clinical circumstance;
including bleeding found by imaging alone) that is actionable,
but does not meet criteria for Type 3 BARC bleeding,
•
The bleeding must require diagnostic studies, hospitalization
or treatment by a health care professional. In particular, the
bleeding must meet at least one of the following criteria:



1) Requiring intervention: defined as a health care
professional-guided medical treatment or percutaneous
intervention to stop or treat bleeding, including temporarily or
permanently discontinuing a medication or study drug.
2) Leading to hospitalization or an increased level of care:
defined as leading to or prolonging hospitalization or transfer
to a hospital unit capable of providing a higher level of care; or
3) Prompting evaluation: defined as leading to an unscheduled
visit to a healthcare professional resulting in diagnostic
testing (laboratory or imaging).
Circulation 2011 In-press
BARC
•
Type 3: Clinical, laboratory, and/or imaging evidence of bleeding
with specific healthcare provider responses, as listed below:
•
•
a. BARC Type 3a Bleeding
Any transfusion with overt bleeding; Overt bleeding plus
hemoglobin drop ≥3 to <5 g/dL* (provided hemoglobin drop is
related to bleeding)
•
•
b. BARC Type 3b Bleeding
Overt bleeding plus hemoglobin drop ≥ 5 g/dL* (provided
hemoglobin drop is related to bleed), Cardiac tamponade,
Bleeding requiring surgical intervention for control (excluding
dental/nasal/skin/hemorrhoid), Bleeding requiring intravenous
vasoactive drugs
•
•
c. BARC Type 3c Bleeding
Intracranial hemorrhage (does not include microbleeds or
hemorrhagic transformation; does include intraspinal). Intraocular bleed compromising vision
Circulation 2011 In-press
BARC Type 4: CABG-Related Bleeding.
• Perioperative intracranial bleeding within 48
•
•
•
•
hours
Reoperation following closure of sternotomy for
the purpose of controlling bleeding
Transfusion of ≥ 5 units of whole blood or packed
red blood cells within a 48 hour period*
Chest tube output ≥ 2L within a 24 hour period.
Notes: If a CABG-related bleed is not adjudicated
as at least a Type 3 severity event, it will be
classified as ‘not a bleeding event.’ If a bleeding
event occurs with a clear temporal relationship to
CABG (i.e. within a 48 hour timeframe) but does
not meet Type 4 severity criteria, it will be
classified as ‘not a bleeding event’. * only
allogenic transfusions are considered as
transfusions for CABG-related bleeds
Circulation 2011 In-press
BARC Type 5: Fatal Bleeding.
• Fatal bleeding is bleeding that directly causes
death with no other explainable cause. BARC
Fatal Bleeding is categorized as either definite
or probable as follows:
• a) Probable fatal bleeding (Type 5a) is bleeding
that is clinically suspicious as the cause of
death, but the bleeding is not directly observed
and there is no autopsy or confirmatory
imaging.
• b) Definite fatal bleeding (Type 5b) is bleeding
that is directly observed (either by clinical
specimen – blood, emesis, stool, etc.- or by
imaging) or confirmed on autopsy.
Circulation 2011 In-press
Possible Mechanisms Linking
Hemorrhagic Complications to Mortality
1. Fatal hemorrhage (e.g. intracranial bleed)
2. Vol. depletion  Hypotension, ischemia, arrhythmias
3. Complications from procedures to manage bleeding
4. Discontinuation of lifesaving medications
(antiplatelet agents, beta blockers, statins)
5. Blood transfusions depleted in NO  systemic
vasoconstriction, inflammation, apoptosis
6. Unmeasured confounders
Impact of Transfusion in ACS
30-Day Survival by Transfusion Group
GUSTO IIb, PURSUIT, PARAGON B trials
N=24,111
Rao SV et. al. JAMA 2004;292:1555–1562
PRBC Transfusion in NSTE ACS
Time-Updated Cox Model for 30-day Death
N=24,111
Adjusted for
transfusion propensity
3.77
(3.13, 4.52)
Adjusted for
baseline
characteristics
3.54
(2.96, 4.23)
Adjusted for baseline
characteristics,
bleeding propensity,
transfusion propensity,
and nadir HCT
3.94
(3.26, 4.75)
-4.0
1.0
Rao SV et. al. JAMA 2004;292:1555–1562
10.0
Impact of the Age of PRBC Transfusion After
Cardiac Surgery on Outcomes
Cleveland Clinic, June 30, 1998 – January 30, 2006
2,872 pts transfused with 8,872 U of blood stored ≤14 days
(mean 11d; “newer blood”) and 3,130 pts transfused with
10,782 U stored 15 days – 42 days (mean 20d; “older blood”)
P<0.001
P<0.001
P=0.01
%
P=0.004
P=0.003
Koch CG et al. NEJM 2008;358:1229-1239
Discharge Medication Use in Patients who
Bleed: PREMIER Registry (STEMI)
1433 STEMI pts treated with primary stenting
P=0.001
P=0.002
P<0.001
Wang TY et. al. Circulation 2008;118:2139-2145
P=0.05
Discharge Medication Use in Patients who
Bleed: HORIZONS-AMI (STEMI)
3,345 STEMI pts in whom primary PCI was performed
P=0.12
P=0.05
P<0.0001
P<0.0001
Balancing Safety and Efficacy
High risk of
ischemic events
“Sweet spot”
High risk of
bleeding events
Inhibition of platelet aggregation
Ischemic risk
Bleeding risk
Ferreiro & Angiolillo. Thromb Haemost 2010 (in press)
Challenges Facing American Medicine
• Costs of Care
• Disparities in Care
• Safety of Care
• Evidence-Based care
• Personalization of
Care
How do we use
evidence to improve
medical decisionmaking?
Traditional EBM Approach
Good
Outcome
Intermediate
Outcome
Bad
Outcome
• Clinical trials and EBM provide
Outcomes
from an for
RCT“average” patients
Mean Treatment Effect
answers
• In real life, however, there are no
average patients
National Cardiovascular Data Registry
Imaging
Registry
ICD Long
Timeline and growth…
IMPACT
Registry
PINNACLE
CathPCI
Registry
1998…..
ICD
Registry
2004
2005
CARE
Registry
2006
ACTION
Registry
2007
AF Abl
Registry
PAD
Registry
Valve
Registry
2008
beyond
National Data Repository for
Comparative Effectiveness Research
Pharm
STS
Registry
NDI
UPI
NCDR
CATHPCI
CLAIMS
Risk-Treatment Paradox
Bleeding Avoidance Rx •inHighest
the risk
Cath
Lab
patients get the
lowest rate of intervention
• Lowest risk patients get the
highest rate of intervention
Low Risk
50%
Medium Risk
High Risk
40%
30%
20%
10%
0%
None
N=1,522,935
Closure
Bivalirudin
Closure + Bival
Marso et al. JAMA 2010; 303: 2156-2164
ePRISM system at MAHI
• John Spertus, M.D., M.P.H.
• David Cohen, MD
• Adam Salisbury, M.D.
• MAHI cardiologists, nurses, and
administration
ePRISM:
Clinical Risk Modeling at the Point-of-Care
Projected Symptoms at
6 Months

0

 x
1 T 1
 x
1 T 1
 
i
i 0




2
,
HI
 x

n T n
 x
n T n
x
i 1 T 1



 i


i 1
   i    j
i

j 1

 i 1
 1   j
 j 1

( LO
Bedside
Decision Support


x
i n T n
i =1
i = 2,
,s
 
where
1
( )
i
i
i = s 1
)    F 1


 1 c
 x   00
  T 1  

 c
 xT n    n0

1 
2



 1

c 
 n n
c
2
2
0 n
x
T 1
x

T
n
Traditional Informed Consent Form
Personalized Medicine: ePRISM Consent
Risk Models Currently Implemented
Model
Data Source
Interventions
• Transfer to main
Mortality
ACC-NCDR
campus
• Surgical consultation
Major bleeding
ACC-NCDR
• Bivalirudin
• Radial Access
• Closure Device
Restenosis/TVR
MASS-DAC
• DES vs. BMS
Personalized PCI Care: Case Examples
Mrs. Jones
A 77-year old woman with
HTN and stable CAD
Mr. Wilson
A 46-year old man with HTN,
diabetes, and NSTEMI
Thienopyridine Selection Model
• Model based on individual-level data from TRITON-TIMI 38
database (n=12,579)
• Separate models for major ischemia (death, MI, stroke) and
bleeding (TIMI major + minor)

Periprocedural MIs excluded (prognostic
importance less certain)

Models include only variables known at time of
procedure

C-statistics ~ 0.70 reasonable discrimination
P2Y12 Selection Model: Potential Application
6 independent RF for non-CABG bleeding
(n=17421, from HORIZONS and ACUITY)
1.
2.
3.
4.
5.
6.
female sex
advanced age
elevated serum creatinine
white blood cell count
anemia
non-ST-segment elevation MI or STsegment elevation MI
Mehran R. JACC 2010;55:2556-66.
ACS Risk Score
Mehran R. JACC 2010;55:2556-66.
A new era of man vs. machine
competition is dawning
Garry Kasparov, the World No. 1 chess player from Russia, makes his move against
Deep Junior, the world computer chess champion. Amir Ban (right), Deep Blue's
operator, physically makes the move when told to do so by the computer.
Conclusions
Pharmacologic treatment of patients with CVD has
improved over the years to decrease ischemic and
bleeding complications
As most drugs which ↓ ischemia also ↑ bleeding, the
offsetting impact of adverse ischemic and
hemorrhagic events must be carefully examined
The net balance of ischemia and bleeding may vary
tremendously with the risk profile of the individual pt
for each complication, and the follow-up duration
Models are needed to assess a patient’s risk for
bleeding as well as ischemic complications to
further enhance treatment of the patients with
therapies that are efficacious and also safe.