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OSLER JOURNAL CLUB COHORT STUDY 8/12/09 Racial Differences in Incident Heart Failure among Young Adults Bibbins-Domingo K, et al. N Engl J Med 360(12):1179-90 Presented by: Cristina Alewine , Raymond Givens, Zoe Orecki Faculty Advisor: J. Hunter Young

Racial Differences in Incident Heart Failure among Young Adults Bibbins-Domingo K, et al. N Engl J Med 360(12):1179-90 Presented by: Cristina Alewine,

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OSLER JOURNAL CLUBCOHORT STUDY

8/12/09

Racial Differences in Incident Heart Failure among Young Adults

Bibbins-Domingo K, et al. N Engl J Med 360(12):1179-90

Presented by: Cristina Alewine , Raymond Givens, Zoe OreckiFaculty Advisor: J. Hunter Young

Cohort Study

Observational Group of subjects followed over time Non-randomized Compares differences in outcomes

between groups Types of cohort studies

Prospective Retrospective Nested case-control Household panel survey

Cohort Study Design

Defined Population

Exposed

Develop Disease

Do Not Develop Disease

Non-exposed

Develop Disease

Do Not Develop Disease

Group A Group B

Cohort Study Limitations

Expensive Time-consuming Attrition Biases

Assessment bias due to lack of blinding Information bias Bias due to attrition Analytic bias

Lack of causal inference: confounding

Cohort Study Strengths

Can define incidence and possible causes of a condition

Efficient for rare exposures Can establish timing of exposure to

outcome Allow study of outcome when

randomization to exposure is unethical or impractical

Heart Failure Epidemiology 5.7 million Americans with HF 670,000 new cases diagnosed each year U.S. mortality rate related to HF

estimated at 20.2 deaths per 100,000 HF prevalence increases with age Prevalence and etiology differ by

ethnicity and gender HF incidence twice as high among older

African-American as among older Caucasian

American Heart Association: Heart Disease and Stroke

Statistics

Bibbins-Domingo K, et al. N Engl J Med 360(12):1179-90

HF Risk FactorsNHANES I

010203040506070 61.6

17.110.1 9.2 8.9 8.9 8

3.1 2.2

Risk Factor

Popu

lati

on

att

ributa

ble

ri

sk (

%)

Modified from: He J, et al. Arch Intern Med 161:996, 2001

HF Prevalence by Age and Gender

NHANES III

20-24 25-34 35-44 45-54 55-64 65-74 75+0

1

2

3

4

5

6

7

8

9

10

0.1 0.10.7

1.8

6.26.8

9.8

0.1 0.10.5

1.3

3.4

6.6

9.7

MenWomen

Perc

en

t of

popu

lati

on

(%)

American Heart Association: Heart Disease and Stroke Statistics

HF Prevalence by Ethnicity

From: Yancy CW. Heart Failure in African Americans. Am J Cardiol 2005;96[suppl]:3i-12i

Heart Failure Epidemiology

• Limited data about HF incidence among people younger than 50

Better understanding of HF among young adults needed for improving targeting of screening and treatment

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

CARDIA

Coronary Artery Risk Development in Young Adults

Prospective Cohort- initiated in 1984

“Initiated to investigate life-style and other factors that influence , favorably or unfavorably, the evolution of coronary heart disease risk factors during young adulthood.”

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

CARDIA- Recruitment

Population Goal: Obtain a representative sample of underlying

population of black and white adults aged 18 to 30 years

Stratify to achieve equal numbers by race, gender, age, education

Centers: Birmingham Chicago Minneapolis OaklandFriedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol

1988;41:1105-16.

CARDIA- Eligibility

Age - 18-30 years at initial telephone recruitment interview - initial exam before 31st birthday

Race Residence Health/Medical - “free of long-term disease or disability” - excluded if pregnant or up to 3 months post-partum Other

- excluded if “unsuitable subjections” emotional instability, drug effects, or hostility

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

CARDIA- Design

Brief Screening Telephone Interview 16 Questions-

Verification Demographics Medical Eligibility

CARDIA Exam Additional Questionnaires

Sociodemographics, Medical, Psychosocial Interviews

A/B Behavior Patterns, Diet Phlebotomy Blood Pressure Pulmonary Function Testing Anthropometry Treadmill Test

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

CARDIA- Participants

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

CARDIA- Participants

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

CARDIA- Time Line

CARDIA Examination at Baseline and 2, 5, 7, 10, 15, and 20 years

Transthoracic Echo at 5 years

Hospitalizations

Deaths at 6 month intervals

0 2 5 7 10 15

20ECHO

Friedman GD, et al. CARDIA: Study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 1988;41:1105-16.

Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

Study Cohort Retention

Retention at Year 20 Telephone Interview 87.5% Examination 71.8%

Noted- Black Men most likely to be lost to follow-up.

However statistics not supplied by authors.

Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

CHF Related- End Points

questioned about overnight hospitalizations records requested in cases of suspected cv

events classified as heart failure if

physician diagnosis medical treatment (diuretic and digitalis or after-load reducing agent)

deaths reported at 6 month intervals

records requested after getting consent from next of kin

Classified as heart failure if appropriate ICD-9Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

Heart Failure Incidence by Race and Gender

0.9%

1.1%

0 %

0.08%

Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

Which risk factors are important in determining who develops early heart

failure?

20 yr Risk of Heart Failure Based on Demographic Measures

Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

BP, HTN, BMI, DM, HDL and CKD Increased in Participants with Heart

FailureWhite Black participants

Blacks +HF vs.All Participants No HF ***p <0.001, ** <0.01, *<0.05Blacks +HF vs. Blacks No HF ### p <0.001, ## <0.01, 0.05

##

***###

***###***###***###

**#**##

**###

Prevalence of HTN in Participants with HF

Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

20 yr Risk of Heart Failure Based on Baseline Measurements

Hazard Ratio

P value

Bivariate Model

FHx Early CAD, and Substance Use No

Different In Those With Subsequent HF.

White Black participants

Lower EF and Worse Systolic Fxn Seen in Pts with HF

*#

*#

*#

Blacks +HF vs.All Participants No HF ***p <0.001, ** <0.01, *<0.05Blacks +HF vs. Blacks No HF ### p <0.001, ## <0.01, 0.05

White Black participants

Bibbins-Domingo et al. (2009). Racial Differences in Incident Heart Failure among Young Adults. NEJM. 360:12- 1179-1190.

20 yr Risk of Heart Failure Based on Echo Measurements at Year 5

Not statistically significant in Multivariate Model Adjusted for Clinical Measures

Conclusions of the Study

Racial disparity in development of early HF Rates of HF in white pts confirmed earlier

studies Risk factors for heart failure in black pts:

Elevated blood pressure Obesity Chronic kidney disease Systolic dysfunction in early adulthood

Need aggressive screening and intervention in young patients at risk

Need studies to determine best ways to intervene

VALIDITY:

Should we believe the results?

YES ISSUES

Large study size Big Association Long observation Standardization Specific risk factors

associated Result makes sense

given prior studies

Differential drop-out Reliance on self-

report Misdiagnosis

Confounded by Chronic Kidney Disease

Missed cases The missing risk

factors: LDL Cocaine

Chronic Kidney Disease

Heart failure or kidney failure? Hospitalizations (N= 23)

n= 9 kidney dysfunction as a co-existing condition

and 3 of these are ESRD Deaths (n= 5)

n= 1 kidney dysfunction as a co-exisiting condition

and it is classified as ESRD

Missed Cases?

Unreported hospitalizations Subclinical cases

Diagnosis based on review of hospital admissions

Excludes diagnoses in clinic Why not review med lists for drugs like lasix or

digitalis that would suggest failure? Bias

Are the persons on the reviewing committee more likely to diagnose HF in black vs. white patients?

GENERALIZABILITY:

Can results apply to everybody?

YES SOME ISSUES

Multiple study centers

Men and women Black and white

subjects Varied socio-

economics Varied educational

background

Does not give info on HF cases by location

Non-black minority groups excluded

Excludes “unsuitable subjects”

What does this mean in clinic?

“Our data suggest that the number of young, black patients with hypertension that would need to be treated to prevent one case of heart failure before 50 years of age could be as low as 21.”

Any Questions?

HOUSESTAFF JOURNAL CLUB

Evidence of causality

Temporal association Strong association Dose-response Consistency/replication Biologic plausibility No alternate explanation (confounding) Cessation of exposure Specific association

Types of Studies

Trial: Cohort assembled and exposure assigned, usually by randomization

Cohort study: Cohort assembled and followed over time. Exposures are measured.

Case-control study: Subjects selected based on presence or absence of disease

Cross-sectional study: Exposures and outcomes measured at one point in time

From Journal to Bedside

Internal validity: Is the association real and causal?

External validity (generalizability): Do the findings apply to other populations (your patient)?

Statistical significance: It’s unlikely the results occurred by chance

Clinical Significance: Findings are compeling enough to influence your practice

Internal Validity: Sources of error

Bias: Association not real due to systematic error Selection bias Information bias

Chance: Association not real due to random error Small sample size Subgroup analyses

Confounding: Real association; wrong inference Grey hair associated with heart disease

Study type: Trials

Strength: validity Trials provide the stongest evidence of causation

Key: the exposure is assigned, usually through randomization

Weaknesses May not be generalizable

Volunteers Clinically homogeneous Ideal setting (extraneous factors controlled)

Expensive Short duration Bias: Minimize by blinding participants & staff

Study type: Cohort Studies

Strengths Long duration of follow-up Temporal association of exposure with outcome Increased generalizability

Weaknesses: Validity Confounding

Factor related to exposure and outcome Exposure is often a choice (diet, exercise, drug)

Bias Assessment of outcome or exposure can be unduly

influenced by factors unrelated to disease process

Study type: Cross-Sectional Studies

Strengths: Efficient Can address prevalence

Weaknesses: Validity

Confounding Bias

Survivor bias Reverse causality

Cannot address incidence

Study type: Case-Control Studies

Strengths: Efficient

Weaknesses: Validity

Confounding Bias:

Selection bias Recall bias

Cannot address prevalence or incidence

Current Article Bibbins-Domingo et al. NEJM 2009; 360:1179-90 Study question: Association of ethnicity with heart

failure in young adults Results: Young African Americans have greater risk of

heart failure than young Americans of European descent Internal validity:

Is the association real? Yes, but with following caveats Differential drop outs: probably underestimated incidence in AA

men Authors could have assessed effect using baseline characteristics

Diagnostic bias: Ethnicity may have influenced probability of naming a clinical scenario as heart failure

Differential access to care: European-Americans may have been diagnosed in clinic more often

Subclinical heart failure was not assessed and may account for a substantial portion of heart falure cases underestimating incidence

Current Article Internal validity: (continued)

Is the association confounded? Renal disease: High prevalence in African Americans and

could both lead to and mimic heart failure (volume overload) External Validity:

Those more likely to be loss to follow-up were excluded Statistical significance: No question here. Just

lack of power to further explore predictors Clinical significance: Not sure these findings were

not unexpected. Incidence is still low complared to renal disease. Another reason to be aggressive with blood pressure control (although this is extrapolating from the data)