Transcript Slide 1

TREATMENT of HYPERTENSION in the 21st Century
Sir George Pickering Lecture
Peter Sever
International Centre for Circulatory Health
Imperial College London
Sir George Pickering
Professor of Medicine
St Mary’s Hospital Medical School 1939
Regius Professor of Medicine
Oxford 1956
Pickering: “High Blood Pressure” 1955
Terminology
Hypertension – not a well chosen word, a bastard
of Greek and Latin parentage and signifying not
high blood pressure but over-much stretching.
The use of the term has lead to the practice of
distinguishing between normal pressure and
hypertension, and thus by easy stages to the
assumption that those subjects with
hypertension differ qualitatively from the rest of
mankind
Platt’s hypothesis-Pickering’s data !
Platt’s hypothesis
Pickering’s data
If Pickering had had access to
blood pressure responses to
different classes of
antihypertensive drugs, the
unimodality hypothesis would have
been much more persuasive
The frequency distribution of changes in diastolic blood pressure
(DBP) produced by 3 drugs
DBP placebo – atenolol, mmHg
16
16
12
12
Count
Count
DBP placebo – lisinopril, mmHg
8
8
4
4
0
0
20 10 0 -10 -20 -30 -40
20 10 0 -10 -20 -30 -40
Count
16
12
DBP placebo – nifedipine, mmHg
8
Atwood et al
J Hypertens 1994; 12:1053
4
0
20 10 0 -10 -20 -30 -40
Treatment of Hypertension
Does the magnitude of response to an
antihypertensive drug inform on the
mechanism(s) involved in blood pressure
elevation ?
Two important observations :
Blood pressure responses to
Spironolactone and to
Renal denervation
in subjects with resistant hypertension
Frequency distribution of change in SBP after spironolactone or
renal denervation
The Symplicity HTN 2 Trial
ASCOT
Renal Denervation (n=46)
140
30
Atenolol & Amlodipine (n=1411)
0
15
0
20
5
40
10
60
80
Frequency
100
20
120
25
Simulated FD curve
Based on reported mean +/SD in SBP
-100
Decreased
-50
-21.87
0
Change in SBP (mmHg) after Spironolactone
50
Increased
Mean  SBP: -21.87±21.27 mmHg
Chapman et al. Hypertension. 2007 ;49:839-45.
-100
Decreased
-50
-32
0
Change in SBP (mmHg) from baseline
50
Increased
Mean  SBP: -32±23 mmHg
Symplicity HTN-2 Investigators. Lancet 2010; 376:1903-09
Placebo corrected SBP response to monotherapy (
dual therapy ( ) meta analysis of 42 trials
Wald DS et al. Am J Med 2009; 122:290-300
) and
Frequency distribution of change in SBP from baseline
among ASCOT monotherapy users (untreated at baseline)
Atenolol group (n=1568)
Amlodipine group (n=1684)
100
150
Frequency
200
50
100
0
0
Frequency
300
200
400
250
Atenolol & Amlodipine (n=3252)
-100
Decreased
-50
-18.81
0
Change in SBP (mmHg) from baseline
50
Increased
Mean  SBP: -18.81±16.93 mmHg
-100
-50 -17.35 0
50
Change in SBP (mmHg) from baseline
Decreased
Increased
-100
-50
-20.16 0
50
Change in SBP (mmHg) from baseline
Decreased
Increased
Mean  SBP: Atenolol: -17.35±18.36 mmHg;
Amlodipine: -20.16±15.37 mmHg
Frequency distribution of change in SBP from baseline
among ASCOT monotherapy users (untreated at baseline)
Amlodipine group (n=1684)
150
100
50
0
Frequency
Note
Placebo response from
randomised controlled trials
in hypertensive subjects
estimated to be approx
10mmHg systolic pressure
200
250
Atenolol group (n=1568)
-100
-50 -17.35 0
50
Change in SBP (mmHg) from baseline
Decreased
Increased
-100
-50
-20.16 0
50
Change in SBP (mmHg) from baseline
Decreased
Increased
Mean  SBP: Atenolol: -17.35±18.36 mmHg;
Amlodipine: -20.16±15.37 mmHg
Frequency distribution of change in SBP after second drug
( BFZ+K or Perindopril) therapy
Amlodipine Arm (n=815)
80
60
40
20
0
Frequency
100
120
140
Atenolol Arm(n=751)
-100
-50
-9.240
50
Change in SBP (mmHg) after BFZ+K
Decreased
-100
-50
-6.29
0
50
Change in SBP (mmHg) after Perindopril
Increased Decreased
Increased
Mean  SBP: BFZ+K: -9.24 mmHg; Perindopril: -6.29 mmHg
Frequency distribution of change in SBP after third drug
(doxazosin) therapy
Atenolol group (n=5787)
600
Amlodipine group (n=4282)
-100
Decreased
-50
-11.68 0
Change in SBP (mmHg) after doxazosin
50
Increased
Mean  SBP: -11.68±18.81 mmHg
300
0
0
100
100
200
300
200
400
500
Frequency
600
400
700
800
500
900
1000
Atenolon & Amlodipine (n=10069)
-100
-50
-13.380
50
-100
-50
-9.390
50
Change in SBP (mmHg) after doxazosin
Change in SBP (mmHg) after doxazosin
Decreased
Increased Decreased
Increased
Mean  SBP: Atenolol group: -13.38±19.89 mmHg;
Amlodipine group: -9.39±16.98 mmHg
Frequency distribution of change in SBP after
spironolactone therapy
Atenolol Arm(n=1061)
Amlodipine Arm (n=350)
-100
-50 -22.99 0
50
Change in SBP (mmHg) after Spironolactone
-100
-50
-18.51 0
50
Change in SBP (mmHg) after Spironolactone
-100
Decreased
-50
-21.87
0
Change in SBP (mmHg) after Spironolactone
50
Increased
80
0
0
20
20
40
40
60
60
80
Frequency
100
100
120
120
140
140
Atenolol & Amlodipine (n=1411)
Decreased
Mean  SBP: -21.87±21.27 mmHg
Increased
Decreased
Increased
Mean  SBP: Atenolol group: -22.99±21.46 mmHg;
Amlodipine group: -18.51±20.33 mmHg
Frequency distribution of change in SBP after
spironolactone therapy
Amlodipine Arm (n=350)
-100
-50 -22.99 0
50
Change in SBP (mmHg) after Spironolactone
-100
-50
-18.51 0
50
Change in SBP (mmHg) after Spironolactone
80
60
0
20
Note greater response
in the atenolol/thiazide
arm. Effect not influenced
by concomitant diuretic
use
40
Frequency
100
120
140
Atenolol Arm(n=1061)
Decreased
Increased
Decreased
Increased
Mean  SBP: atenolol group: -22.99 mmHg; amlodipine group: -18.51 mmHg
Blood pressure response to renal denervation:
The Symplicity HTN 2 Trial
Symplicity HTN-2 Investigators .Lancet 2010;376:1903-1909
Atenolol & Amlodipine (n=1411)
140
Summary
80
60
40
20
0
-100
Decreased
50
Increased
30
20
15
Denervation
Denervation
0
5
10
Frequency
Do these observations highlight two
separate phenotypes with resistant
hypertension - volume overload and
excess vascular resistance ?
-50
-21.87
0
Change in SBP (mmHg) after Spironolactone
Renal Denervation (n=46)
25
Blocking two apparently different
physiological systems in patients with drug
resistant hypertension leads to substantial
reductions in blood pressure. These
reductions in blood pressure far greater
than expected from renal efferent
sympathetic blockade or the action of
aldosterone blockade on sodium and
water homeostasis
Frequency
100
120
Spiro
-100
Decreased
-50
-32
0
Change in SBP (mmHg) from baseline
50
Increased
Resistant hypertension : Haemodynamics
,
After Brown M. BHS Guideline on Resistant Hypertension ( unpublished)
Resistant hypertension :
Key features
Muscle sympathetic nerve activity
and increasing blood pressure
Blunted natriuresis
severe
Increased extracellular volume
Activation of RAAS
mild-moderate
hypertensive
Increased renal sympathetic nerve activity
Increased sodium reabsorption
normotensive
Grassi G et al. Exp Physiol 2010;95:581-586
,
Response to spironolactone and to
denervation
Or are these observations providing a clue to an
important interaction between sodium homeostasis and
CNS activation which may be relevant not only in the
context of resistant hypertension but also perhaps ,
importantly, more generally in the context of raised blood
pressure
Spironolactone
actions include :• Lowers sympathetic nervous system
activity in older hypertensive subjects
( lowers plasma noradrenaline and reduces
3H –NA release rates - not seen with
thiazides )
• Binds to aldosterone sensitive
mineralocorticoid receptors in the NTS, the
anterior hypothalamus and other brain
stem centres including the RVLM and PVN
(Geerling and Loewy 2009)
• Enhances parasympathetic tone and may
decrease sympathetic activity
Wray and Supiano 2010
Spironolactone
Renal denervation
• Blocks renal efferent sympathetic nerve
activity
• Blocks renal afferent nerve activity
• Induces substantial sodium and water loss
Mosaic 2011
Genetic
Environmental
eg Salt
Haemodynamics
Renal
Humoral
Anatomical
BP
Intrauterine
programming
Adaptive
Endocrine
Modified from Page 1959
Neural
Implication of these observations in
resistant hypertension to
pathophysiology of “essential”
hypertension
Linkage of dietary salt and the CNS
to elevated blood pressure
Interaction hypothesis supported by:Experimental models of hypertension
- SHR and salt loading Koepke et al.Hypertension 1985; 7: 357-363
- DOCA salt model and stress
Koepke et al. Am J Physiol. 1986; 251: R289-294
- Dietary salt enhances excitability and increases the gain of
sympathetic-regulatory neurons in RVLM in salt sensitive animal
models.
Stocker et al. Physiol.Behav. 2010;100: 519-524.
Stress, sodium retention and BP elevation in normotensive human
subjects with family history of hypertension Light et al.Science 1983: 220: 429-43
Linked to genetic polymorphism of the alpha 2 adrenoceptor
Finlay et al. J. Appl Phys 2004; 96: 2231-2239
Longitudinal migration study
Poulter et al. BMJ. 1990 Apr 14;300: 967-72
Kenyan Luo Migration Study
modified from Poulter et al. BMJ. 1990 Apr 14;300: 967-72
SBP levels at 0-24 months
130
migrants
mmHg
120
110
100
non-migrants
Mean pre-migration blood
pressure
0
3
6
12
Males
18
24 months
DBP levels at 0-24 months
70
migrants
mmHg
60
50
Mean pre-migration blood
pressure
0
3
6
non-migrants
12
18
24 months
Sever et al
In Concepts in
hypertension
Springer-Verlag
1989 p 55-66
Body weight, pulse and urinary NaK ratios at 0-24 months
Males
Body weight (kg)
Pulse (bpm)
Urinary NaK ratio
61.0
75
5.0
57.5
69
3.5
54.0
63
0
3
6
12
18
24
2.0
0
3
6
12
18
0
24
3
6
12
18
24
Controls
Migrants
Females
Body weight (kg)
Pulse (bpm)
Urinary NaK ratio
61.0
75
5.0
57.5
69
3.5
63
54.0
0
3
6
12
18
24
2.0
0
3
6
12
18
24
Poulter et al. BMJ. 1990 Apr 14;300: 967-72
0
3
6
12
18
24
Hypothesis required to incorporate:• Early blood pressure elevation
• Rapid increase in body weight ( not
explained by increase in dietary calorie
intake)
• Increase in dietary sodium
• Increase in heart rate
Neuronal genotype (s) influences neuronal
responses to plasma/CSF
sodium
Renal genotype(s)influence tubular
reabsorption of
sodium and/or
renal afferent
nerve responses to
sodium load
Guyton hypothesis
*Impaired if prevented by:
Angiotensin II
Renal sympathetic nerve activity
Aldosterone
Reduced renal mass
The way forward :Integrative physiology
Further understanding of genetic and environmental
factors, the basis of their interaction and their
influence on the neuro/humoral/renal/vascular
mechanisms that are likely to be involved in the
multi-factorial, multi-genetic nature of hypertension.
Improved methods to understand the
integration of biological systems
• Requires more quantitative approaches and modelling of cardiovascular
system dynamics
• Requires advances in medical imaging technology to permit non-invasive
studies of the brain, vasculature and kidney in the whole animal/human.
• A fully integrative mathematical model is essential for the complete
analysis of currently available data
• Data needs to be acquired from long-term minimally invasive observations
of cardiovascular variables in humans and animal models under a variety
of behavioural and environmental conditions.
Challenges to the scientific community
Need for teams of researchers to design studies that draw upon expertise in the fields of
genomics, proteomics, informatics, statistical genetics, cellular and integrative
physiology, mathematics and computer science.
•
Systems biology is the delineation of the elements in a biological system and the
analysis of their interactions after genetics or environmental perturbation.
•
The goal of systems biology is to explain the systems emergent properties (phenotypic
transformation) that are absent when the elements of the system are studied in
isolation, but are only present when multiple elements within a system interact
•
Systems biology should be hypothesis driven, quantitative, integrative and iterative.
•
Bioinformatics and computational biology is necessary to resolve the complex
interrelationships between the multiple organs and systems involved not only in
blood pressure regulation but also in the consequential impact of blood pressure and
other risk factors on target organs
Hypertension treatment
The ASCOT Legacy
ASCOT History
• 1988/9 European Blood Pressure Group- discussion on unmet needs in
hypertension research
• 1991 British Hypertension Society Working Party formed; produced initial
trial design but no funding
• 1993 Furberg and the CCB controversy
• 1993 NHLBI agree to fund ALLHAT
• 1995 Joint discussions between UK, Sweden and Pfizer.
•
1996 ASCOT announcement and Steering Committee established
ASCOT: Rationale
• Insufficient outcome data on newer
types of blood pressure lowering agents
• No data on the evaluation of specific
combination treatment regimens
• Shortfall of CHD prevention using
standard therapy
• Need to evaluate multiple risk factors in
the prevention of CHD
• No data on the benefits of lipid lowering
among hypertensives
ASCOT: Study design
19,257
hypertensive
patients
ASCOT-BPLA stopped
after 5.5 yrs
PROBE
design
atenolol ±
bendroflumethiazide
amlodipine ±
perindopril
10,305 patients
TC ≤ 6.5 mmol/L (250 mg/dL)
atorvastatin 10 mg
Double-blind
ASCOT-LLA stopped
after 3.3 yrs
placebo
Investigator-led, multinational randomised controlled trial
Sever et al J. Hypertension. 2001;19:1139
Lipid-lowering arm
ASCOT-LLA : Nonfatal MI
and Fatal CHD
Cumulative Incidence (%)
4
Atorvastatin 10 mg
Number of events
100
Placebo
Number of events
154
36%
reduction
3
2
1
HR = 0.64 (0.50-0.83)
p=0.0005
0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Years
Relative risk reductions independent of baseline cholesterol
Sever PS, Dahlöf B, Poulter N, Wedel H, et al, for the ASCOT Investigators. Lancet. 2003;361:1149-58
ASCOT-LLA CHD events :early benefits
Risk Reduction
Censoring Time
Hazard Ratios (95% CI)
(%)
*
Event Rate
Atorvastatin
Placebo
83
2.4
14.2
67
5.5
16.6
48
7.5
14.3
45
6.6
12.0
2 Years
38
5.9
9.5
End of Study
36
6.0
9.4
30 days
90 days
180 days
1 Year
Atorvastatin better
* Per 1000 patient years
Placebo better
ASCOT-LLA
Summary of all end points
Risk Ratio
Primary End Points
Nonfatal MI (incl silent) + fatal CHD
Secondary End Points
Total CV events and procedures
Total coronary events
Nonfatal MI (excl silent) + fatal CHD
All-cause mortality
Cardiovascular mortality
Fatal and nonfatal stroke
Fatal and nonfatal heart failure
Hazard Ratio
0.64 (0.50-0.83)
0.79 (0.69-0.90)
0.71 (0.59-0.86)
0.62 (0.47-0.81)
0.87 (0.71-1.06)
0.90 (0.66-1.23)
0.73 (0.56-0.96)
1.13 (0.73-1.78)
Tertiary End Points
Silent MI
Unstable angina
Chronic stable angina
Peripheral arterial disease
Development of diabetes mellitus
Development of renal impairment
0.82 (0.40-1.66)
0.87 (0.49-1.57)
0.59 (0.38-0.90)
1.02 (0.66-1.57)
1.15 (0.91-1.44)
1.29 (0.76-2.19)
Atorvastatin better
0.5
Placebo better
1.0
1.5
Area of squares is proportional to the amount of statistical information
Sever PS, Dahlöf B, Poulter N, Wedel H, et al, for the ASCOT Investigators. Lancet. 2003;361:1149-58
Blood Pressure-lowering arm
ASCOT BPLA Summary of all end points
Primary
Non-fatal MI (incl silent) + fatal CHD
Unadjusted Hazard
ratio (95% CI)
0.90 (0.79-1.02)
Secondary
Non-fatal MI (exc. Silent) +fatal CHD
Total coronary end point
Total CV event and procedures
All-cause mortality
Cardiovascular mortality
Fatal and non-fatal stroke
Fatal and non-fatal heart failure
0.87 (0.76-1.00)
0.87 (0.79-0.96)
0.84 (0.78-0.90)
0.89 (0.81-0.99)
0.76 (0.65-0.90)
0.77 (0.66-0.89)
0.84 (0.66-1.05)
Tertiary
Silent MI
Unstable angina
Chronic stable angina
Peripheral arterial disease
Life-threatening arrhythmias
New-onset diabetes mellitus
New-onset renal impairment
1.27 (0.80-2.00)
0.68 (0.51-0.92)
0.98 (0.81-1.19)
0.65 (0.52-0.81)
1.07 (0.62-1.85)
0.70 (0.63-.078)
0.85 (0.75-0.97)
Post hoc
Primary end point + coronary revasc procs
CV death + MI + stroke
0.86 (0.77-0.96)
0.84 (0.76-0.92)
0.50
0.70
1.00
Amlodipine  perindopril better
1.45
2.00
Atenolol  thiazide better
The area of the blue square is proportional to the amount of statistical information
Synergy of atorvastatin and
amlodipine based treatment arm
ASCOT-LLA 2x2 analyses
Benefits of atorvastatin according to BP lowering strategy
Primary endpoint: Non-fatal MI and fatal CHD
Atenolol-based treatment
Cumulative incidence (%)
4.0
Atorvastatin
Placebo
3.0
53%
2.0
1.0
HR=0.47 (0.32 - 0.69) p<0.001
0.0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Cumulative incidence (%)
Amlodipine-based treatment
4.0
Atorvastatin
Placebo
3.0
16%
2.0
1.0
HR=0.84 (0.60 - 1.17) p=0.30
0.0
0.0
0.5
Years
1.0
1.5
2.0
Years
P for interaction = 0.017
Sever, Poulter, Dahlof, Wedel. Europ.Heart Journal. 2006;27:2982
2.5
3.0
3.5
LLA and BPLA
Combined benefits of lipid- and blood pressure- lowering
Estimated benefits of combined blood pressure and
lipid lowering
from meta-analyses of placebo controlled trials
Blood Pressure
Lowering
(15/10mmHg)
Lipid
Lowering
(1mmol/L)
Combined BP
& Lipid
Lowering
CHD
30%
25-35%
About 50%
Stroke
45%
15-20%
About 55%
Reduction in risk of non-fatal MI and fatal CHD
using Framingham model for baseline estimates **
Framingham risk
Final risk in those Relative risk reduction
estimate from baseline
assigned
data ( n=10,305)
amlodipine/perindopril
and atorvastatin
22.8*
4.8*
79%
*per 1000 patient years
**Variables include SBP, smoking status, total and HDL-cholesterol, presence or
absence of LVH,
age, gender, presence or absence of diabetes. No correction for on- treatment blood
pressure
Sever et al. Int. J. Cardiol.2009. Feb 18, epub ahead of print
A molecular mechanism for synergy
Clunn GF, Sever,P, Hughes A. Int J Cardiol 2009 Jun 10 [Epub ahead of print]
SMC dedifferentiation
to synthetic phenotype
Macrophage
Foam
cells
Cytokine release
SMC
migration
and
proliferation
SMC = smooth muscle cell
Apoptosis
MMPs
Destruction
of intercellular
matrix
Lipid-laden
macrophage
MMP = matrix metalloproteinase
Plaque rupture
SMC DEDIFFERENTIATION
Contractile phenotype
CCB
Ca2+
Synthetic phenotype
Loss of
functionality
of L-type VOC
• CCBs ineffective
L-type VOC
• CCBs effective
Presence of statins
leads to growth arrest
and re-expression
of functioning
L-type VOCs
CCB = calcium channel blocker
VOC = voltage-operated Ca2+ channel
Clunn GF, Sever P, Hughes A. Int J Cardiol 2009 Jun 10 [Epub ahead of print]
An additional mechanism?
SMC: reversion to a more differentiated phenotype
Lipid-lowering arm
Atorvastatin and carotid artery pressure
Atorvastatin lowers carotid artery pressure but not brachial
artery pressure, with evidence of an enhanced
effect in those assigned amlodipine-based treatment
Effect of atorvastatin on carotid systolic pressure in those
assigned amlodipine- or atenolol- based treatment in ASCOT
Aplanation tonometry performed on the right carotid artery .Carotid artery flow
velocity measured by pulsed wave Doppler ultrasound, and wave intensity analysis
also performed
Augmentation pressure and augmentation index were lower in those assigned atorvastatin
Manisty C, Mayet J, Tapp R, Sever P et al. Hypertension 2009:54; e-pub online Aug 31
Lipid-lowering arm
The relationship Between statin therapy and
the progression of renal damage
Background
•
Uncertainty whether the use of statin therapy is effective
in retarding the progression of renal damage among highrisk patients in a primary prevention setting.
• Would the use of statin therapy in combination with
antihypertensive medication, be additive in reducing the
age-related decline in renal function ?
www.ascotstudy.org
Aten-based & Atorvastatin
Amlo-based & Atorvastatin
70
72
74
Aten-based & Placebo
Amlo-based & Placebo
68
Mean eGFR (95% CI), mL/min/1.73 m2
Mean eGFR During Follow-up in the ASCOTLLA, Stratified by Allocated Treatment
Baseline
Aten-based & Placebo:
Aten-based & Atorvastatin:
Amlo-based & Placebo:
Amlo-based & Atorvastatin:
69.0
68.9
69.9
70.3
6 Month
Year 1
Year 2
Year 3
67.7
67.9
70.8
71.4
67.8
68.0
71.1
71.6
68.4
68.8
72.2
72.5
69.5
70.0
73.2
73.7
eGFR: estimated glomerular filtration rate; CI: confidence interval; Aten-based: Atenolol ± thiazide ;
Amlo-based: Amlodipine ± Perindopril
www.ascotstudy.org
Blood Pressure-lowering arm
Substudies
CAFÉ Study: Methods
SP
P1
∆P
Pressure
(mm Hg)
DP
Incisura
• Radial artery waveforms
measured via noninvasive
applanation tonometry
• Augmentation index (AIx)
defined as ratio of
augmentation to central
pulse pressure:
Alx = (∆ P/PP) × 100
ED
Time (msec)
ED = ejection duration
CAFE Investigators. Circulation. 2006;113: epublished Feb 13, 2006.
CAFE: Lower central aortic BP with newer vs
older antihypertensive regimen despite similar
brachial BP
140
Brachial SBP
135
130
Central aortic SBP
mm Hg
125
120
115
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
AUC
Time (years)
Amlodipine ± perindopril
Atenolol ± bendroflumethiazide
CAFE Investigators. Circulation. 2006;113: epublished Feb 13, 2006.
ASCOT Study of LV diastolic function : Treatment effects at I year
Atenolol-Based
Regimen (n = 411)
Amlodipine-Based
Regimen (n = 413)
p Value
Transmitral Doppler
E wave, cm/s
A wave, cm/s
E/A ratio
E-wave
deceleration time,
ms
Tissue Doppler
Systolic velocity
(S′), cm/s
Early diastolic
velocity (E′), cm/s
Late diastolic
velocity (A′), cm/s
*Mean E/E′ ratio
*BNP, pg/ml
60.08 ± 14.87
68.25 ± 14.63
0.91 ± 0.29
63.41 ± 15.01
75.08 ± 15.76
0.86 ± 0.22
0.001
<0.001
0.004
0.20 ± 0.05
0.18 ± 0.05
<0.001
8.2 ± 1.75
9.5 ± 2.21
<0.001
7.91 ± 1.84
8.76 ± 2.04
<0.001
10.76 ± 2.15
12.34 ± 2.31
<0.001
8.14 ± 2.38
37 (20–56)
7.76 ± 2.05
19 (10–34)
0.013
<0.001
Early diastolic velocity (E`)( measure of diastolic relaxation) lower on atenolol, and left
ventricular filling pressure (E/E`) and BNP higher on atenolol
* Both independent predictors of cardiac events
Tapp et al J Am Coll Cardiol. 2010 Apr 27;55(17):1875-81
Blood Pressure Variability
Blood Pressure variability
Background
• Blood pressure variability is increased in
cohorts at high risk of stroke and predicts
stroke independent of mean blood pressure
Rothwell 2005.
Blood pressure variability: methods
(based on over 1 million BP readings)
• Of 19,257 patients, 18,530 had ≥ 2 follow-up visits
(median = 10) from 6 months onwards until the end of
the trial
• 3 blood pressure measurements were recorded at
each visit, using standardised techniques, at 6
monthly intervals for a median follow up of 5.5 years
Within visit variability
164/96
159/92
150/92
173/90
169/89
174/96
164/90
168/94
158/94
156/88
148/86
159/86
Between visit or visit-visit variability
170/92
166/88
174/88
Visit-to-visit mean systolic blood pressure expressed in
deciles, hazard ratios (95% CI) and number of stroke and
coronary events in each decile
Mean SBP
Stroke risk
Coronary risk
Stroke and coronary risk expressed by decile of measure of visit-to-visit SBP variability
Stroke Risk
Coronary Risk
Standard deviation of SBP
Amlodipine
Atenolol
Coefficient of variation of SBP
Variation independent of mean
SBP
Decile of measure
Decile of measure
Group distribution (SD and CV) of measures of
SBP at baseline and at each follow-up visit in the
two treatment groups
Hazard ratios (95% CI) for the effect of treatment
(amlodipine versus atenolol) on risk of stroke
Parameters calculated using all BP measurements from 6 months onwards. Mean, SD, CV,
and VIM are entered into the model as deciles
Stroke
Variables in model
Systolic blood pressure
HR (95% CI)
p value
0.78 (0.67–0.90)
0.001
0.84 (0.72–0.98)
0.025
Rx + mean + SD
0.96 (0.82–1.12)
0.59
Rx + mean + CV
0.95 (0.82–1.11)
0.55
Rx + mean + VIM
0.96 (0.82–1.12)
0.58
Rx + within-visit SD
0.84 (0.72–0.98)
0.024
Rx + mean + VIM + WVSD
0.99 (0.85–1.16)
0.89
Treatment (Rx)
Usual BP
Rx + mean
Visit-to-visit BP variability
Within-visit and visit-to-visit BP variability
SD, standard deviation; CV, coefficient of variation; VIM, variability independent of mean;
WVSD, within-visit standard deviation
Hazard ratios (95% CI) for the effect of treatment
(amlodipine versus atenolol) on risk of coronary events
Parameters calculated using all BP measurements from 6 months onwards. Mean, SD, CV,
and VIM are entered into the model as deciles
Coronary Events
Variables in model
Systolic blood pressure
HR (95% CI)
p value
0.85 (0.77–0.94)
0.002
0.88 (0.80–0.98)
0.019
Rx + mean + SD
1.00 (0.90–1.11)
0.98
Rx + mean + CV
1.00 (0.90–1.11)
0.99
Rx + mean + VIM
1.00 (0.90–1.10)
0.99
Rx + within-visit SD
0.88 (0.79–0.97)
0.013
Rx + mean + VIM + WVSD
1.01 (0.91–1.12)
0.88
Treatment (Rx)
Usual BP
Rx + mean
Visit-to-visit BP variability
Within-visit and visit-to-visit BP variability
SD, standard deviation; CV, coefficient of variation; VIM, variability independent of mean;
WVSD, within-visit standard deviation
Conclusions
• Blood pressure variability is a major predictor
of stroke and coronary events
• In individual trials average (mean) blood
pressures poorly predict outcome
• Increased blood pressure variability is
associated with smoking, increasing age,
diabetes, presence of vascular disease
• There are major differences in the effects of
different drug regimens on blood pressure
variability
Biomarkers and cardiovascular risk prediction
Biomarkers
Inflammation
CRP,IL6,LpPLA2,neopterin
Lipids
ApoA,ApoB1,Lp(a)
Metabolic
proinsulin,insulin,adiponectin,
fructosamine
Thrombosis
aPAF, aPC
Current hot biomarkers
NT-proBNP, cystatin C
Others
cortisol, urate, renin, aldo,
CFH,GDF 15
Vascular
ADMA, t-PA, ICAM-1
ASCOT Biomarker Programme: Although both these biomarkers independently predict risk of future
cardiovascular events in the ASCOT Trial of 19342 hypertensive subjects, Nt-proBNP is the only one
which has predictive ability beyond classical risk factors (Net reclassification improvement 11.8%)
Baseline Nt-BNP and Risk of CV Events
Per 1 SD increase log Nt-BNP
451
1265
1.30
<0.0001
Tertile 1 :<57
128
441
1 (ref)
Tertile 2 :58-141
141
438
1.17
0.30
Tertile 3: >141
182
338
1.70
0.0007
1
1.5
<0.0006
2
Odds ratio and 95% CI (log scale)
Baseline CRP and Risk of CV Events
Per 1 SD increase log CRP
452
1269
1.19
Tertile 1 CRP: <1.74mg/L
131
448
1 (ref)
Tertile 2 CRP: 1.74-4.09mg/L
153
417
1.25
0.14
1.35
0.05
Tertile 3 CRP: >4.09mg/L
168
404
0.5
1.0
1.5
Odds ratio 95% CI
0.006
0.05
2.0
Sever et al Europ Heart J 2011 epub July 28
Multivariable adjustment. Adjusted for current smoking status, diabetes mellitus, randomized BP treatment (atenolol/amlodipine),
randomized atorvastatin/placebo/not in LLA, left ventricular hypertrophy, baseline SBP, total cholesterol and HDL-C BMI, logeglucose, family history of CHD, creatinine and educational attainment
Lipid-lowering arm
The LLA Extension
Changes in total cholesterol over time
mmol/L
mmol/L
Figure 5.3.2
AML-NY-96-008: Anglo-Scandinavian Cardiac60%
Outcomes
trial (ASCOT)
+ of patients
in
Change in Total Cholesterol Over
Time
both arms now on statins
(All LLA Subjects Followed to Final Visit)
mg/Dl
mg/Dl
End of
LLA
5.6
210
5.4
Atorvastatin
Atorvastatin
Placebo
Placebo
5.2
200
5.0
End of
BPLA
4.8
190
180
4.6
170
4.4
4.2
160
4.0
0.0
1.0
2.0
3.0
4.0
Years
S ourc e data: Lis ting 5.3
D ate of R eporting D atas et C reation: 06FE B 2003
P rogram: LLA X Fig53I.s as
5.0
Final
Visit
D ate of Figure G eneration: 27A P R 2006 (15:31)
Sever PS, et al. Eur Heart J 2008;29:499–508
ASCOT-LLA endpoints
3.3 yrs1
Risk ratio
Primary endpoints
Non-fatal MI (incl silent) + fatal CHD
Secondary endpoints
Total CV events and procedures
Total coronary events
Non-fatal MI (excl silent) + fatal CHD
All-cause mortality
Cardiovascular mortality
Fatal and non-fatal stroke
Fatal and non-fatal heart failure
Tertiary endpoints
Silent MI
Unstable angina
Chronic stable angina
Peripheral arterial disease
Development of diabetes mellitus
Development of renal impairment
Atorvastatin better
0.5
5.5 yrs2
Risk ratio
Placebo better
1.0
1.5
Atorvastatin better
0.5
Placebo better
1.0
1.5
Area of each square is proportional to the amount of statistical information
1. Sever PS, et al. Lancet 2003;361:1149–58; 2. Sever PS, et al. Eur Heart J 2008;29:499–508
ASCOT-ON and ASCOT-10
Mortality and morbidity follow up of
UK ASCOT patients
ASCOT-10 Objectives

•
•
•
•
To establish the effect of study interventions on long term
mortality and morbidity outcomes for coronary, stroke and
other vascular diseases in patients from the ASCOT study, five
years after completion of the study.
To ascertain the number of cases of new onset diabetes
amongst the study population.
To ascertain, in patients who developed new onset diabetes
during the main ASCOT study, whether this is associated with
greater vascular morbidity and mortality.
To ascertain whether blood pressure variability during the main
ASCOT trial follow up is a predictor of subsequent
cardiovascular morbidity and mortality
Primary endpoint CV death + non-fatal MI + non-fatal stroke
93
Cumulative Incidence by Cause of Death ‒ 1
All-cause mortality
Non-cardiovascular mortality
Cardiovascular mortality
Cancer mortality
Number at risk
Placebo 2288
Atorvastatin 2317
2191 2052
2228 2091
1208
1226
2288
2317
2191 2052
2228 2091
1208
1226
2288
2317
2191 2052
2228 2091
1208
1226
2288
2317
2191 2052
2228 2091
1208
1226
Cumulative Incidence by Cause of Death ‒ 2
Mortality due to
infection
Mortality due to
respiratory illness
Mortality due to infection
and respiratory illness
Number at risk
Placebo 2288
Atorvastatin 2317
2191 2052
2228 2091
1208
1226
2288
2317
2191 2052
2228 2091
1208
1226
2288
2317
2191 2052
2228 2091
1208
1226
Hypertension treatment in the 21st
century
ASCOT Legacy
www.ascotstudy.org
96
Guidelines influenced by ASCOT-LLA
• BHS IV and JBS 2
• Taskforce of ESH and ESC 2007 and 2009.
Advocate lipid-lowering in primary
prevention based on absolute risk assessment
• ATP III Update 2004
Influence on Blood Pressure
Guidelines
• The demise of the beta-blocker
ASCOT BPLA
Less protection against stroke
More new onset diabetes
(Higher central aortic blood pressures)
( Increase in BP variability )
(Less effect on LV dysfunction)
• Pre-eminence of CCB over thiazide in treatment
• strategies
• Importance of CCB/ACEI combination
2
Step 1
2003
Younger (e.g.<55yr)
and Non-Black
Older (e.g.55yr)
or Black
A (or B*)
X
C orX
D
A (or X
B*)
Step 2
Step 3
A (or X
B*)
Step 4
Resistant
Hypertension
C or X
D
+
+
C
+
D
Add: either -blocker or spironolactone or other diuretic
A: ACE Inhibitor or angiotensin receptor blocker
C: Calcium Channel Blocker
B: b - blocker
D: Diuretic (thiazide)
* Combination therapy involving B and D may induce more new onset diabetes compared with other combination therapies
Adapted from: ‘Better blood pressure control: how to combine drugs’ Journal of Human Hypertension (2003) 17, 8186
Acknowledgment
Colleagues
Collaborators
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Neil Poulter
Simon Thom
Alun Hughes
Neil Chapman
Jamil Mayet
Ajay Gupta
Limmie Chang
Andrew Whitehouse
Judy Mackay
Mike Schachter
Alison Adderkin
and many others
Jill Bunker
Wendy Callister
Nursing team at St Marys
•
•
•
•
•
•
•
•
•
•
Graham MacGregor
Mark Caulfield
Bryan Williams
Eoin O’Brien
Alice Stanton
Gareth Beevers
Gordon McInnes
David Collier
Naveed Sattar
Peter Rothwell
Nordic ASCOT Investigators
Bjorn Dahlof, Hans Wedel, Jan
Ostergren, Marku Niemenen, Sverre
Kjeldsen, Arni Kristensson, Jesper
Mehlsen
Pfizer Jan Buch, Rachel Laskey, Mogens
Westergard