The WISE Study:
The NHLBI-Sponsored Women’s
Ischemia Syndrome Evaluation
Methods and Findings
B. Delia Johnson, Ph.D.
Research Associate, EDC
Epidemiology Seminar Series, October 6, 2005
Graduate School of Public Health, University of Pittsburgh
1
Outline
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Background
WISE Overview
Key Findings
Implications / Impact
2
Background
3
Women and Heart Disease - 1
4
Women and Heart Disease - 2
520
500
480
460
440
420
400
01
99
97
95
93
91
89
87
85
83
81
380
79
Deaths in Thousands
Cardiovascular Disease Mortality Trends for Males and Females
United States: 1979-2002
Years
Males
Females
5
Women and Heart Disease - 3
Prevalence of Obstructive CAD at Angiography in Women
100
80
60
50
59
52
40
40
20
0
CASS
1982
Sullivan Bell 1995
1994
WISE
1998
6
What is Myocardial Ischemia?
• Insufficient amount of oxygen reaching the heart muscle;
• Often exercise or anxiety induced;
• Reversible dysfunction or prolonged & severe;
• Chest pain or “silent;”
• Transient ECG abnormalities;
• Over time, the affected heart tissue may die;
• Many possible causes:
– Obstructed coronary arteries (CAD)
– Endothelial dysfunction
– coronary vasoconstriction
– Microvascular insufficiency.
7
WISE Overview
The Women’s Ischemia Syndrome Evaluation
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WISE Goals
1. Develop accurate diagnostic approaches for CAD
detection in women.
2. Determine the frequency, pathophysiology, and
significance of myocardial ischemia in the absence
of significant CAD in women.
3. Evaluate the influence of hormones on
pathophysiology and diagnostic test response.
9
In Brief
• A four-center NHLBI-sponsored study
• 936 women undergoing clinically
ordered coronary angiography
• Observational study
10
Observational Study
• A type of study in which individuals are observed
or certain outcomes measured;
• No attempt to affect the outcome (e.g. no
treatment);
• Advantage: natural setting;
• Drawbacks: - Hawthorne effect;
- Association vs. causality;
• Low in “Hierarchy of Evidence” - ???*
*Concato 2004, NeuroRx 1:341-7.
11
Data Collection - 1
1.
All Sites: WISE Core Data
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Core lab quantitative angiographic analysis
Demographics (age, race)
CAD risk factors (smoking, diabetes)
Medical hx (comorbidities, meds)
Reproductive hx (hysterectomy, HRT use)
Physical exam (weight, BP)
DASI (functional capacity)
Symptom history
Psychological inventories (Beck, Spielberger)
Block dietary data
Baseline ECG
Annual follow-up (adverse events, resource use)
Study termination (lost to FU, withdrew consent).
12
Data Collection - 2
2.
All Sites – Core Lab Blood Assays
•
Lipids (HDL, triglycerides)
•
Reproductive hormones (estradiol, FSH)
•
Androgens (testosterone, androsteindione)
•
Inflammatory markers (hs-CRP, SAA)
•
Phytoestrogens (genistein, daidzein)
•
Insulin, fasting glucose.
13
Data Collection - 3
3. Site-Specific Diagnostic Tests (# done)
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Provocative coronary reactivity (coronary diameter
change, flow reserve) (166)
Brachial artery ultrasound (381)
Exercise ECG (289)
Pharmacological ECG (289)
Dobutamine stress echo (171)
SPECT (radionuclide perfusion) (452)
MRI perfusion (177)
LV mass (107)
Holter monitoring (163)
P-31 (MRI spectroscopy) (292)
PROCEDURAL SYMPTOM QUESTIONNAIRE
14
WISE Organization
Steering
Committee
NHLBI
DSMB
Core Laboratories
P&P
Committee
Subcommittees
Symptoms &
Psychosocial
Hormones
Mortality classification
P31
Ischemia
Coordinating
Center
Angiographic
Hormones, androgens,
insulin, glucose
Coronary reactivity
Clinical Centers
Brachial Artery
Univ. Alabama Medical
Center Birmingham
ECG
Univ. Florida, Gainesville
Lipids
UPMC, Pittsburgh
Phytoestrogens
Allegheny General Hosp.
Pittsburgh
Inflammatory markers
P31
15
WISE Timeline - 1
Sept.
1996
Oct.
8557 women screened
22% eligible; 50% of
these enrolled (N=936)
2005
2000
WISE Extension:
Annual Follow-Ups
WISE Extension Goals:
• Determine incremental prognostic value of novel WISE tests
• Determine prognostic value of female reproductive variables
• Determine cost effectiveness of WISE tests
• Genetics
16
• Inflammatory markers
WISE Timeline - 2
Sept.
1996
Oct.
8557 women screened
22% eligible; 50% of
these enrolled (N=936)
2005
2000
WISE Extension:
Annual Follow-Ups
ARIC
FemHRT
IVUS
QWISE
WTH
Sildenafil
WISE Ancillary Studies
EWISE
YWISE
17
Population Characteristics - 1
Age – years [mean + SD (range)]
58 + 12 (21-86)
Postmenopausal (%)
76
Ethnic minority (%)
19
Chest pain or other symptoms (%)
94
CAD (50%+ stenosis) (%)
39
Prior MI or revascularization (%)
BMI [mean + SD (range)]
29
29.7+6.6 (14.0-57.2)
Obese (BMI > 30) (%)
41
Metabolic syndrome (%)
47
18
Population Characteristics - 2
Rx: Lipid Lowering (%)
29
Rx: Anti-Hypertensive (%)
48
Rx: Psychoactive (%)
30
Hx smoking (%)
53
Current smoking (%)
20
Diabetes (%)
25
Hx hypertension (%)
59
Hx dyslipidemia (%)
55
19
Reasons for Catheterization
Chest pain
92%
Shortness of breath
58%
Abnormal stress test
45%
Syncope
10%
Preoperative clearance
4%
Unknown
1%
Other (e.g. fatigue, dizziness, nausea, EKG changes)
12%
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Key Findings
21
WISE Goals
1. Develop accurate diagnostic approaches
for CAD detection in women.
•
Is classic angina diagnostic for CAD in women?
2. Determine the frequency, pathophysiology,
and significance of myocardial ischemia in
the absence of significant CAD in women.
3. Evaluate the influence of hormones on
pathophysiology and diagnostic test
response.
22
Chest Pain / Angina
• 481 WISE women
• Symptomatic in prior year
• No prior MI or procedure
• 26% with CAD
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Angina Determination
Ask: are your symptoms
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Substernal
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Exertional / strong emotion
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Relieved w/in 10 minutes by rest/nitroglycerin
Definitions of Angina:
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Typical Angina: all 3 present
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Atypical Angina: 2 out of 3 present
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Nonanginal chest pain: 1 present
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“Asymptomatic:” 0 present
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Probability* CAD
by Anginal Classification and Age in Women
100
100
Age 35-45
80
60
80
60
45
40
3
1
0
20
7
2
NA
Asymp
0
TA
100
32
40
16
20
Age 45-55
68
AA
84
NA
Asymp
Age 55-65
TA
100
AA
95
Age 65-75
80
80
60
54
60
46
40
40
13
20
5
20
17
12
NA
Asymp
0
0
TA
AA
NA
Asymp
TA
*Data from Diamond (1980 J Clin Invest. 65:1210-21)
AA
25
Probability vs. WISE Prevalence* of CAD by Anginal
Classification and Age
50
45
80
40
Age 45-55, n=141
60
30
16
20
10
32
40
12
10
22
12
3
1 0
0
20
18
20
7
2
8
0
TA
90
80
70
60
50
40
30
20
10
0
68
Age 35-45, n=57
AA
NA
Asymp
TA
84
Age 55-65, n=137
100
AA
NA
Asymp
95
Age 65-75, n=114
80
46
60
34
21
24
13
51
36
40
5 7
54
30
17
20
12
22
0
TA
AA
NA
Asymp
TA
AA
NA
Asymp
* Adjusted for diabetes, dyslipidemia, smoking, SBP
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Source: Johnson et al. Chapter 10 in Shaw & Redberg (Eds.) Contemporary Cardiology:
Coronary Disease in Women. Humana Press 2004.
Angina - Conclusions
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Overall, typical angina is not a good diagnostic
indicator of CAD in women;
•
After age 55, classic angina classification is
moderately predictive of CAD.
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WISE Goals
1. Develop accurate diagnostic approaches
for CAD detection in women.
2. Determine the frequency, pathophysiology,
and significance of myocardial ischemia in
the absence of significant CAD in women.
–
Is metabolic dysfunction in the heart predictive
of cardiovascular outcomes?
3. Evaluate the influence of hormones on
pathophysiology and diagnostic test
response.
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P-31 Spectroscopy: Metabolic
Dysfunction
Spectra from Woman Volunteer:
A)
LV chamber
B)
Interventricular septum
C)
LV anterior wall
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Phosphorus-31 nuclear magnetic resonance spectroscopy (MRS);
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Normal PCr/ATP ratio ≈ 1.6
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74 WISE women w/o CAD.
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PCr/ATP ratio measured before & after handgrip stress
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Abnormal defined <20% change
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Measure of metabolic function in heart muscle
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P-31 Normal vs. Abnormal
Normal MRS
n=60
Abnormal MRS
n=14 (23%)
p
56 (50-63)
57 (48-65)
0.72
<20% Stenosis
63
64
0.91
Diabetes
18
7
0.44
BMI > 30
30
50
0.21
Hx HTN
59
36
0.11
Fam Hx CAD
78
43
0.02
Hx Dyslipidemia
49
25
0.13
Ever Smoked
48
78
0.04
Current HT Use
52
64
0.43
Medians (IQ Range) or %
Age
No consistent relationship of CAD risk factors in normal vs abnormal MRS
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P-31 Spectroscopy & Outcomes
1
No CAD/Normal MRS
(n=60)
No CAD/Abnormal
MRS (n=14)
CAD (n=352)
Freedom from Events
0.9
0.8
0.7
0.6
0.5
0.4
Risk adjusted
p=0.02
0.3
0.2
0.1
0
0
6
12
18
24
Months to First Event
30
36
Source: Johnson,
Circulation 2004
31
P-31 Spectroscopy - Conclusion
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Abnormal MRS spectroscopy results
are found in about 20% of women
with chest pain but no CAD;
•
This abnormality is predictive of
cardiovascular events – ischemiarelated hospitalization.
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WISE Goals
1. Develop accurate diagnostic approaches for
CAD detection in women.
2. Determine the frequency, pathophysiology,
and significance of myocardial ischemia in
the absence of significant CAD in women.
3. Evaluate the influence of hormones on
pathophysiology and diagnostic test
response.
–
Is there a relationship between endogenous
reproductive hormones and CAD?
33
Hypothalamic Hypoestrogenemia
• 95 premenopausal WISE women
• No exogenous hormones (OC)
• HypoE defined as: E2<50 pg/mL +
FSH<10 mlU/mL + LH<10 mlU/mL
• 13 (14%) had CAD
• 33 (35%) had hypoE
• 26% non-white (mostly AA)
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HypoE & CAD
100
% With HypoE
80
p=0.01
69
60
40
29
20
0
No CAD N=82
CAD N=13
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HypoE & CAD
Reproductive Hormones
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HypoE & CAD
Multivariate Models
Independent Predictors of CAD
HR
95% CI
p
HypoE
7.4
1.7, 33.3
0.008
Asp. Use
7.6
1.7, 33.7
0.008
ATPIII
Risk>3%
8.3
1.2, 59.6
0.04
c = 0.86
NS variables: age, race, HTN, diabetes,
BMI, WHR, smoking, family Hx, lipids,
Beck depression, stress, typical angina.
Independent Predictors of HypoE
HR
95% CI
p
Anti-Anx.
Meds
4.6
1.3, 15.7
0.02
Anti-Dep.
Meds
0.1
.01, .92
0.04
Diabetes
3.4
1.1, 10.2
0.03
c = 0.70
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Hypoestrogenemia - Conclusions
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Premenopausal women with obstructive
CAD are highly likely to have hypothalamic
hypoestrogenemia;
•
This condition is related to anxiety (as
suggested by anti-anxiety medications)
and diabetes.
38
Summary of Key Findings
• Diagnostic approaches for CAD Detection:
– Chest pain is not a good indicator of CAD in women;
• Myocardial Ischemia:
– Coronary metabolic dysfunction occurs in about 20% of
women with chest pain and no CAD;
– It is highly predictive of CV events in these women;
• Influence of Hormones:
– Angiographic PRE women with CAD are highly likely to
have hypothalamic hypoestrogenemia.
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Publications / Publicity - 1
57 peer-reviewed publications. Additional topics:
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Markers of ischemia
Psychosocial / socioeconomic / ethnicity
Obesity / metabolic syndrome
Functional capacity
Inflammatory markers / biomarkers
Genetics
Quality of care
Cost assessment
Renal insufficiency / anemia / diabetes
WISE menopausal algorithm
Novel risk factors
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Publications / Publicity - 2
• WISE workshops:
– AHA Scientific Conference on Molecular,
Integrative and Clinical Approaches to
Myocardial Ischemia, August 2001.
– Women’s Ischemic Syndrome Evaluation.
Current Status & Future Research
Directions (NIH/NHLBI), October 2-4,
2002.
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Publications / Publicity - 3
• 118 abstracts at scientific meetings:
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American Heart Association
American College of Cardiology
Society for Cardiovascular Magnetic Resonance
International Congress on Coronary Artery Disease
North American Menopause Society
Inter-American Society of Hypertension
American Psychosomatic Society
AHA Forum on Quality of Care and Outcomes Research in
Cardiovascular Disease and Stroke
European Society of Cardiology
International Society for Magnetic Resonance in Medicine
Society for Cardiac Angiography and Interventions
AHA Council on Cardiovascular Disease Epidemiology
International Symposium on Women’s Health and Menopause
American Society for Clinical Pharmacology and Therapeutics
Heart Failure Society of America
First International Conference on Women, Heart Disease and Stroke 42
World Congress of Cardiology
Publications / Publicity - 4
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Impact
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Future Plans
• WISE 3 –
– A new cohort
– Apply new knowledge
– Learn from past mistakes
– Validate our findings
– generate new hypotheses
• Clinical Trials
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WISE Women and Men
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Sherry Kelsey, PhD
Kevin Kip, PhD
Richard Holubkov, PhD
Marian Olson, MS
Genevieve Barrow, MS
Candace McClure, BS
Gretchen Gierach, MPH
Angela Pattison, BS
Joe Bondi, BA
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Back-Up Slides
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WISE Exclusion Criteria
• Comorbidity compromising 1-year follow-up;
• Pregnancy;
• Contra-indications to provocative diagnostic
testing;
• Cardiomyopathy;
• NY Heart Association functional Class III-IV
congestive heart failure;
• Recent MI;
• Significant valvular / congenital heart disease;
• Language barrier to questionnaire testing.
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