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(Supplemental Digital Content) Cost Effectiveness of Antihypertensive Medication:
Exploring Race and Sex Differences Using Data from the REasons for Geographic and
Racial Differences in Stroke (REGARDS) Study
Gabriel S. Tajeu,1 Stephen Mennemeyer,2 Nir Menachemi,3 Robert Weech-Maldonado,4
Meredith Kilgore2
1
Department of Epidemiology, University of Alabama at Birmingham; 2Department of Health
Care Organization and Policy, University of Alabama at Birmingham; 3Department of Health
Policy and Management, Indiana University; 4Department of Health Services Administration,
University of Alabama at Birmingham
Supplemental Methods. Additional information on State Transition Model development.
Supplemental Table 1. State transition model adverse events and health states.
Supplemental Table 2. Average systolic blood pressure and 10-year risk (expressed as a
percent) of stroke and coronary heart disease in REasons for Geographic and Racial
Differences in Stroke study participants by age, race, sex, and number of antihypertensive
medications.
Supplemental Table 3. Worst-case scenario cost-effectiveness analyses results.
Supplemental Table 4. Average 10-year Framingham Stroke and Coronary Heart Disease risk
by age, systolic blood pressure, race, and sex.
Supplemental Figure 1. One-way sensitivity analyses for the cost effectiveness of
antihypertensive medication treatment versus no-treatment by race and sex, varying costs and
utility estimates by ± 50%.
Supplemental Figure 2. Scatter plot of incremental cost and effectiveness results from
probabilistic sensitivity analysis (1,000 iterations) comparing antihypertensive medication
treatment versus no-treatment by race and sex.
Correspondence to:
Gabriel Tajeu
446 Lister Hill Library
1700 University Boulevard
Birmingham, AL 35294-0022
T: 205-531-2258
[email protected]
1
Supplemental Methods.
Framingham Risk Equations:
We utilized the Framingham Stroke and Hard Coronary Heart Disease (CHD) risk equations to
estimate stroke and CHD transition probabilities in the current model. Framingham risk
equations measure the 10-year risk of suffering cerebrovascular and cardiovascular events.
The Framingham Stroke risk equation estimates the risk of stroke using the following variables:
age, sex, systolic blood pressure (SBP), diabetes mellitus, cigarette smoking, prior
cardiovascular disease, atrial fibrillation, left ventricular hypertrophy, and use of antihypertensive
medication.1 The Framingham CHD risk equation is an estimate of the risk of suffering a
myocardial infarction (MI) or coronary death and is generated using the following variables: age,
sex, total cholesterol, high-density lipoprotein cholesterol, SBP, use of antihypertensive
medication, and cigarette smoking status.2 For more information on the equations used, refer to
https://www.framinghamheartstudy.org/risk-functions.
Stroke and CHD transition probabilities:
REGARDS data was used to determine stroke and CHD transition probabilities for participants
using the Framingham risk equations presented above.3,4 Once risk scores were calculated
using Framingham Stroke and CHD equations, we identified yearly transition probabilities for
participants based on age, race, sex, and number of antihypertensive medications prescribed.
This was accomplished using several steps. First, we determined average SBP of participants
by race, sex, and the number of antihypertensive medications prescribed (Table 1). Second, we
used previously calculated 10-year Framingham stroke and CHD risk among REGARDS
participants3,4 to calculate average stroke and CHD risk scores based on age category (45-64,
65-74, ≥75), race (white, black), sex, and SBP category (SBP≥120 & <130, SBP≥130 & <140,
SBP≥140 & <150, SBP≥150 & <160, SBP≥160) (Supplemental Table 4). Finally, using the
average SBP based on race, sex, and number of antihypertensive medications prescribed found
in Table 1, we assigned participants to SBP categories found in Supplemental Table 4, allowing
us to then determine average stroke and CHD risk based on age, race, sex, SBP, and the
number of antihypertensive medications prescribed. The results of this process are displayed in
Table 3. Similarly, once SBP was estimated for individuals in the no-treatment group, we were
able to assign a Framingham stroke and CHD risk score based on the SBP category their
average SBP based on their age, race, and sex was classified in (Table 3, right panel).
Increased risk following cardiovascular disease (CVD) event:
The risk of future CVD events is influenced by previous CVD. We were able to account for this
increased risk in the State Transition Model (STM). Using estimates from published literature,
we incorporated risk multipliers into the STM. The yearly risk of a stroke following either a
previous stroke or MI was increased by 1.86 times.5,6 The yearly risk of an MI following either a
previous stroke or MI was increased by 2.19 times.5,6 Chronic kidney disease resulted in an
increased risk of 1.4 to 2.0 times depending on stage, and end-stage renal-disease resulted in
an increased risk of 2.8 times for subsequent stroke and MI events.5,7
Number of antihypertensive medications and treatment costs:
We utilized Medicare claims data from 2012 to estimate the cost of seven classes of
antihypertensive medication including angiotensin converting enzyme inhibitors (Lisinopril),
diuretics (hydrochlorothiazide), calcium channel blockers (amlodipine), beta blockers (atenolol),
alpha blockers (prazosin), angiotensin receptor blockers (losartan), and aldosterone receptor
antagonists (spironolactone). Using baseline REGARDS data, we determined the distribution of
the number of antihypertensive medications (1, 2, 3, or ≥4 medications) prescribed to white
2
men, white women, black men, and black females. Because the cost of antihypertensive
medications differ by class, we also determined the distribution of different antihypertensive
medication classes within each category of number of medications prescribed (1, 2, 3, or ≥4
medications). For instance, among participants who were prescribed one antihypertensive
medication, 22.2% were taking a beta blocker, 21.8% were taking a diuretic, 21.9% were taking
an ACE inhibitor, etc. Therefore we multiplied these percentages by the specific cost of each
drug in order to calculate the average yearly cost of antihypertensive medication for a
participant taking one antihypertensive medication (i.e., 0.222*cost of beta blocker + 0.218*cost
of diuretic + 0.219*cost of ACE inhibitor, etc.), thus weighting the yearly cost based on the
percentage of participants who were prescribed a particular drug class among individuals taking
one antihypertensive medication. This process was repeated for each category of number of
antihypertensive medications prescribed (1, 2, 3, or ≥4).
Post-event health states:
We made the assumption that certain combinations of health conditions were not survivable.
For instance, if a participant suffered a severe stroke while already suffering from ESRD or HF,
developed ESRD and subsequently experienced HF, or conversely developed HF and
subsequently developed ESRD, we assumed they transitioned to death. Also, while participants
could suffer both a stroke and an MI, and while costs of all events suffered were accounted for
by the model, we did not create a “post stroke and MI” health state due to logistical
considerations and the limited benefit of creating such a group.
Key Assumptions:
First, while risk of subsequent events is influenced by prior events in the model, we do not
explicitly consider baseline comorbidities when assigning transition probabilities but rather we
assume Framingham risk scores are proxies for the overall health of REGARDS participants.
Second, the comorbidity distribution between the treatment and no-treatment groups were
similar. Third, that hypertension treatment decisions in the REGARDS cohort were based on
guidelines from the Seventh Report of the Joint National Committee on the Prevention,
Detection, Evaluation, and Treatment of High Blood Pressure (JNC7).8 Fourth, that none of the
participants had resistant hypertension. Fifth, we allow age to increase throughout the model,
which influences Framingham risk, but assumed SBP remained constant for participants during
simulation. Similarly, the distribution of number of antihypertensive medications prescribed by
race and sex remained constant at all ages.
3
Supplemental Table 1. State transition model adverse events and health states.
Adverse events*
Myocardial infarction (MI)
Stroke
Heart failure (HF)
Chronic kidney disease (CKD)
End stage renal disease (ESRD)
Health states
No event
Post MI
Post mild stroke
Post severe stroke
HF
CKD
ESRD
Combined health states
CKD HF
Post MI HF
Post MI CKD
Post MI ESRD
Post mild stroke HF
Post mild stroke CKD
Post mild stroke ESRD
Post severe stroke CKD
Fatal events
Fatal MI
Fatal stroke
Fatal HF
Fatal health states
ESRD severe stroke
HF severe stroke
ESRD HF
HF ESRD
*Individuals who transition to “health states” can suffer additional MI and stroke.
Individuals cannot transition to ESRD without first developing CKD.
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Supplemental Table 2. Average systolic blood pressure and 10-year risk (expressed as a percent) of stroke and coronary heart disease in
REasons for Geographic and Racial Differences in Stroke study participants by age, race, sex, and number of antihypertensive medications.
Treatment
No-treatment†
Number of Average SBP
10-year stroke
10-year CHD
Average
10-year stroke
10-year CHD
antihypertensive
(SD)
risk (%)
risk (%)
SBP:
risk (%)
risk (%)
medications
estimated
Age
Age
45-64 65-74 ≥75
45-64 65-74 ≥75
45-64 65-74 ≥75
45-64 65-74 ≥75
White men
1 128.4 (15.6)
7.2
12.5
20.2
10.6
15.3
20.2
137.4
7.3
13.0
21.9
12.1
17.0
21.8
2 129.8 (15.9)
8.6
14.2
24.1
11.0
15.3
22.3
147.8
9.6
15.4
25.2
17.2
21.0
29.1
3 131.0 (17.0)
10.3
17.1
28.2
10.9
16.8
15.2
158.0
11.9
20.8
30.0
17.0
23.4
30.3
≥4 129.4 (17.6)
11.5
18.9
25.9
12.2
26.5
20.6
165.4
15.5
26.9
35.3
22.4
26.5
38.4
White women
1 126.1 (15.7)
3.9
9.6
19.1
5.2
8.3
9.0
135.1
4.8
10.0
21.3
5.1
6.5
7.5
2 127.4 (15.4)
5.8
11.5
21.9
6.3
8.0
9.0
145.4
6.8
13.5
25.8
9.3
11.9
12.2
3 128.7 (16.1)
6.3
13.5
26.5
7.2
9.3
9.4
155.7
8.6
18.5
31.7
9.6
12.6
14.2
≥4 131.8 (17.2)
7.0
18.3
33.2
8.1
11.0
13.6
167.8
12.6
22.5
38.5
13.8
17.9
17.9
Black men
1 132.8 (16.8)
8.1
13.5
22.2
11.0
17.1
25.0
141.8
10.4
17.3
25.1
15.4
23.2
28.2
2 133.2 (16.7)
9.9
15.1
22.4
11.9
16.1
23.4
151.2
14.5
21.3
32.8
16.5
22.6
33.7
3 134.4 (16.8)
11.8
17.6
23.9
12.3
18.3
25.3
161.4
18.2
25.5
34.5
18.5
29.1
33.3
≥4 136.6 (18.5)
13.8
20.9
31.5
11.7
18.4
21.8
172.6
18.2
25.5
34.5
18.5
29.1
33.3
Black women
1 130.5 (16.6)
5.7
11.8
23.5
6.6
9.6
9.6
139.5
8.2
16.6
30.1
10.6
13.0
13.8
2 131.4 (16.9)
6.9
13.7
25.0
7.6
9.9
10.7
149.4
12.4
22.0
32.3
12.2
13.2
14.5
3 133.4 (17.5)
8.3
16.0
30.3
7.7
9.8
11.6
160.4
13.6
27.7
45.4
14.3
20.1
20.2
≥4 135.8 (19.8)
10.6
19.6
34.9
8.3
12.6
13.1
171.8
13.6
27.7
45.4
14.3
20.1
20.2
SBP=systolic blood pressure; SD=standard deviation; CHD=coronary heart disease; MI=myocardial infarction.
CHD consisted of non-fatal MI and fatal CHD.
†Number of antihypertensive medications for participants receiving no-treatment represent the number they should have been receiving. Average
SBP was estimated for this group as described in the Treatment strategies section of the methods.
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Supplemental Table 3. Worst-case scenario cost-effectiveness analyses results.
White men
No-treatment
Antihypertensive medication treatment
White women
No-treatment
Antihypertensive medication treatment
Black men
No-treatment
Antihypertensive medication treatment
Black women
No-treatment
Antihypertensive medication treatment
QALY=quality-adjusted life-year.
Lifetime Cost
Incremental
Cost
QALYs
Incremental
QALYs
$27,836
$27,399
-$436
15.78
16.85
1.07
$22,632
$22,588
-$43
17.52
18.27
0.75
$30,990
$29,923
-$1,067
14.66
16.22
1.56
$28,580
$26,719
-$1,861
15.58
17.23
1.65
6
Supplemental Table 4. Average 10-year Framingham Stroke and Coronary Heart Disease risk by age,
systolic blood pressure, race, and sex.
10-year Framingham Stroke risk (%)
White
Black
Men
Women
Men
Women
10-year Framingham CHD risk (%)
White
Black
Men
Women
Men
Women
SBP (mm Hg)
Age 45 – 64
≥120 & <130
5.4
3.4
6.1
4.3
7.7
6.0
7.8
≥130 & <140
7.3
4.8
8.1
6.4
12.1
5.1
12.6
≥140 & <150
9.6
6.8
10.4
8.2
17.2
9.3
15.4
≥150 & <160
11.9
8.6
14.5
12.4
17.0
9.6
16.5
≥160
15.5
12.6
18.2
13.6
22.4
13.8
18.5
Age 65 – 74
≥120 & <130
10.2
7.9
10.8
9.5
11.4
8.9
11.2
≥130 & <140
13.0
10.0
14.2
12.6
17.0
6.5
17.1
≥140 & <150
15.4
13.5
17.3
16.6
21.0
12.0
23.2
≥150 & <160
20.8
18.5
21.3
22.0
23.4
12.6
22.6
≥160
26.9
22.5
25.5
27.7
26.5
17.9
29.1
Age ≥75
≥120 & <130
18.2
16.4
17.6
17.5
15.3
8.6
15.8
≥130 & <140
21.9
21.3
21.6
24.3
21.8
7.5
25.5
≥140 & <150
25.2
25.8
25.1
30.1
29.1
12.2
28.2
≥150 & <160
30.0
31.7
32.8
32.3
30.3
14.2
33.8
≥160
35.3
38.5
34.6
45.4
38.4
17.9
33.3
SBP=systolic blood pressure; CHD=coronary heart disease; MI=myocardial infarction.
6.5
5.5
10.6
12.2
14.3
9.6
7.1
13.0
13.2
20.2
10.2
7.8
13.8
14.5
20.3
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Supplemental Figure 1. One-way sensitivity analyses for the cost effectiveness of antihypertensive medication treatment versus no-treatment by
race and sex, varying costs and utility estimates by ± 50%. ICER=incremental cost-effectiveness ratio; CKD=chronic kidney disease; MI=myocardial
infarction; HF=heart failure; ESRD=end-stage renal disease; TX=treatment; RX=prescription.
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Supplemental Figure 2. Scatter plot of incremental cost and effectiveness results from probabilistic sensitivity analysis (1,000 iterations) comparing
antihypertensive medication treatment versus no-treatment by race and sex. Ellipses around scatterplot denote observations within the 95%
confidence interval. CE=cost-effectiveness; TX=treatment; QALYs=quality adjusted life years.
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Supplemental References:
1.
D'Agostino RB, Wolf PA, Belanger AJ, et al. Stroke risk profile: adjustment for
antihypertensive medication. The Framingham Study. Stroke; a journal of cerebral
circulation. 1994;25(1):40-43.
2.
D'Agostino RB, Sr., Grundy S, Sullivan LM, et al. Validation of the Framingham
coronary heart disease prediction scores: results of a multiple ethnic groups investigation.
JAMA : the journal of the American Medical Association. 2001;286(2):180-187.
3.
McClure LA, Kleindorfer DO, Kissela BM, et al. Assessing the performance of the
Framingham Stroke Risk Score in the reasons for geographic and racial differences in
stroke cohort. Stroke; a journal of cerebral circulation. 2014;45(6):1716-1720.
4.
Framingham Heart Study. Framingham Heart Study. 2015;
https://www.framinghamheartstudy.org/about-fhs/history.php, 2015.
5.
Hoerger TJ, Wittenborn JS, Segel JE, et al. A health policy model of CKD: 2. The costeffectiveness of microalbuminuria screening. American journal of kidney diseases : the
official journal of the National Kidney Foundation. 2010;55(3):463-473.
6.
Weiner DE, Tabatabai S, Tighiouart H, et al. Cardiovascular outcomes and all-cause
mortality: exploring the interaction between CKD and cardiovascular disease. American
journal of kidney diseases : the official journal of the National Kidney Foundation.
2006;48(3):392-401.
7.
Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death,
cardiovascular events, and hospitalization. The New England journal of medicine.
2004;351(13):1296-1305.
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8.
Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National
Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.
Hypertension. 2003;42(6):1206-1252.
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