Diego Alcivar-Franco1, Scott Purvis2, Marc S Penn1,2, Andrea Klemes3. 1. Summa Cardiovascular Institute, 1080 Summa Health System , Akron, OH, USA. 2. Cleveland HeartLab Inc., Cleveland, OH, USA. 3. MDVIP, Boca Raton, FL, USA.
Cardiovascular disease continues to be the leading cause of mortality in the US,
where nearly one-third of deaths can be directly attributed to a cardiovascular
event. The growing increase in the prevalence of pre-diabetes and diabetes has
changed the underlying risk profile of cardiovascular disease from one focused on
cholesterol levels to one of vascular inflammation. Diabetes is a risk equivalent
for cardiovascular disease because diabetics without a history of acute myocardial
infarction (AMI) have the same likelihood of an AMI as non-diabeticpatients with a
history of AMI. Diabetes has been linked to an increased drive of vascular
inflammation through multiple mechanisms including lipid oxidation, advanced
glycation end-products and increased insulin levels.Assessing risk factors of cardiovascular disease and screening for coronary artery
disease (CAD) and its equivalents like diabetes have been the goal of the American
College of Cardiology and the American Heart Association. They have tried to
implement simple and evidence-based guidelines with high-sensitivity screening at a
relatively low cost. After withdrawing the target goal for low-density lipoprotein
(LDL) treatment in the new guidelines, it remains uncertain how successful we really
are at controlling patients at risk and who would require further treatment and more
aggressive strategies. This is important in light of recent data showing that
approximately 50% of patients admitted with CAD and acute ischemic events have
acceptable cholesterol levels.[1]The link between atherosclerosis, clinical events and inflammation has been
recognized for years and is well established.[2] The recent findings of the Canakinumab Anti-inflammatory Thrombosis Outcomes
Study (CANTOS) validated the concept that targeting inflammation is a good strategy
to prevent clinical events in patients with atherosclerosis.[3] There is growing recognition of the physiology represented by the measurement
of novel markers of oxidation and inflammation.[4] Two markers, lipoprotein-associated phospholipase A2 (Lp-PLA2) and
myeloperoxidase (MPO)), are markers of vulnerable plaque and risk of clinical
events.[2,5-7] Although it is unclear that the
inhibition of either of these enzymes would have clinical benefit,[8,9] increased circulating levels of
these markers are linked to increased risk of stroke and AMI.In this study, we assessed whether the addition of a marker of vascular inflammation
to advanced cholesterol measures annually in a primary-care population would lead to
the long-term, down-regulation of cardiovascular risk. In recognition of the
changing landscape of cardiovascular risk assessment, MD Value In Prevention (MDVIP)
added MPO to their annual wellness panel in 2011. In this study, we present the
findings of >100,000 patients who had these wellness panels yearly. Our
objectives were to examine whether knowledge of vascular inflammation altered
cardiovascular risk over time, and how knowledge of vascular inflammation changed
the cardiovascular risk of non-diabetic, pre-diabetic and diabeticpatients.
Methods
As part of its wellness services, MDVIP implements an annual screening panel to all
enrolled patients. The wellness screening panel focuses on known risk factors for
cardiovascular disease including diabetes (hemoglobin A1C; HbA1C), an advanced lipid
panel, apolipoprotein A1 and MPO. Results from de-identified patients tested from
2011 to 2015 followed by 801 physician practices were captured from Cleveland
HeartLab’s Laboratory Information System and encompassed all MDVIP wellness testing
performed between January 2011 and December 2015. Results for LDL testing were
provided by three laboratories (88% from Atherotech Vertical Auto Profile, 10% from
Liposcience nuclear magnetic resonance profile and 2% from Cleveland HeartLab
standard lipid panel).Extracted data were cleaned by transforming all test results that indicated a value
above or below the test analytical range (using a “<” or “>”) to their numeric
value. Records with test results indicating that the test was not performed (for any
reason) were deleted. Clinical cutoffs for HbA1c used in the study were as follows:
non-diabetic, <5.7%; pre-diabetic, 5.7%–6.4%; and diabetic, >6.4%. Based on
guideline LDL targets for diabetics and non-diabetics without heart disease,
analyses were stratified for LDL <100 mg/dL and <130 mg/dL.Physician experience associated with each test result was calculated by determining
the difference (in months) between the test order date and the date of the first
test order for each ordering physician. The distribution of physician experience
over the entire study was determined to be 24% with 0–12 months of experience, 17%
with 12–24 months, 13% with 25–36 months, 13% with 37–48 months and 32% with 49–60
months.Ethics committee review was not necessary as this study was a retrospective analysis
of Laboratory Information System data with no patient identifiers or information
available. Furthermore, all MDVIP patients in their agreement with MDVIP consent
that their data can be used for blinded analyses.
Results
We studied >100,000 patients per year of the MDVIP annual wellness panels between
2011 and 2015. Overall, approximately 645,000 total patient visits from 285,901
unique patients were analyzed (2011: 104,608 patients; 2012: 115,864 patients; 2013:
125,193 patients; 2014: 140,764; 2015: 159,300 patients). These included
approximately 623,000 LDL, 598,000 HbA1C and 603,000 MPO results. A total of 79.5%
of patient visits were for patients who had testing done in multiple years.The data in Figure 1 depict
the trends for prevalence of diabetic, pre-diabetic and non-diabeticpatients based
on annual HbA1C. The prevalence of diabetes was 9%–11%, pre-diabetes was 41.1%–46.7%
and non-diabetes was 42.3%–47.2%. Thus, in any year, >50% of the patient
population were at risk of or diagnosed with diabetes.
Figure 1.
Population breakdown by hemoglobin A1C (HbA1C). Percentage of patients with
pre-diabetes (gray) and diabetes (dark gray) as a function of year
tested.
Population breakdown by hemoglobin A1C (HbA1C). Percentage of patients with
pre-diabetes (gray) and diabetes (dark gray) as a function of year
tested.As seen in Figure 2, in the
first year of testing diabeticpatients we noted a 21.3% positivity rate for MPO
compared with 14.4% for non-diabetics. The MPO positivity rate in pre-diabetics was
15.2%. Over the 5 years, the rate of MPO positivity steadily decreased to 6.7%, 4.0%
and 4.0% for diabetics, pre-diabetics and non-diabeticpatients, respectively, in
2015; i.e., a 68.5%, 73.7% and 72.2% reduction in risk annually for a cardiovascular
event in these three groups, respectively.
Figure 2.
Risk based on myeloperoxidase (MPO) stratified by hemoglobin A1C (HbA1C).
Percentage of patients with positive MPO test based on HbA1C status as a
function of year tested.
Risk based on myeloperoxidase (MPO) stratified by hemoglobin A1C (HbA1C).
Percentage of patients with positive MPO test based on HbA1C status as a
function of year tested.We investigated the prevalence of patients at typical LDL targets based on National
Cholesterol Education Program Adult Treatment Panel (ATP) III (<100 mg/dL for
diabetics and <130 mg/dL for pre-diabetics and non-diabetics; see Figure 3). The number of
diabeticpatients at LDL goal was always >57% of the population and in 2014
reached a high of 71%. For non-diabetics and pre-diabetics with the higher LDL goal
of 130 mg/dL, the percentage of patients at LDL goal was between 76% and 84%.
Importantly, there was no correlation between lowering of LDL and lowering of the
prevalence of patients with positive MPO in diabetics, pre-diabetics or
non-diabetics, suggesting that modulation of risk associated with presence of a
positive marker of vascular inflammation was distinct from simply lowering
cholesterol levels.
Figure 3.
Patients with guideline target low-density lipoprotein (LDL) levels still
have risk based on inflammation. Percentage of patients at guideline-based
LDL goal with positive myeloperoxidase (MPO) stratified by hemoglobin A1C
(HbA1C) status as a function of year tested.
Patients with guideline target low-density lipoprotein (LDL) levels still
have risk based on inflammation. Percentage of patients at guideline-based
LDL goal with positive myeloperoxidase (MPO) stratified by hemoglobin A1C
(HbA1C) status as a function of year tested.Although the prevalence of patients with evidence of vascular inflammation decreased
from 2011 to 2015 (Figure
4), the percentage of patients with a positive MPO and controlled cholesterol
levels did not. In 2011, 59.2%, 77.0% and 77.1% of diabetics, pre-diabetics and
non-diabeticpatients, respectively, who had a positive MPO also had cholesterol
levels at goal. In 2015, those percentages were 61.2%, 80.0% and 80.0%, and not
significantly changed from 2011 relative to the significant decrease in the overall
prevalence of positive MPO.
Figure 4.
Identification of risk in patients with target low-density lipoprotein (LDL)
levels. Percentage of patients at guideline LDL target with positive
myeloperoxidase (MPO) stratified by hemoglobin A1C (HbA1C) as a function of
year tested.
Identification of risk in patients with target low-density lipoprotein (LDL)
levels. Percentage of patients at guideline LDL target with positive
myeloperoxidase (MPO) stratified by hemoglobin A1C (HbA1C) as a function of
year tested.The data in Figure 5 explore
the relationship between the number of years a physician was aware of and ordered an
MPO test and the prevalence of positive results. Although the prevalence of diabetes
and patients with LDL levels above goal does not appear to change, the prevalence of
positive MPO levels decreases within the year after the physician begins to measure
vascular inflammation.
Figure 5.
Physician experience with inflammation testing and risk reduction. Time from
initiation of inflammation testing with myeloperoxidase (MPO) and decrease
in incidence of MPO within a physician practice.
Physician experience with inflammation testing and risk reduction. Time from
initiation of inflammation testing with myeloperoxidase (MPO) and decrease
in incidence of MPO within a physician practice.
Discussion
The response-to-injury hypothesis of atherosclerosis proposes that the
atherosclerotic process is initiated through arterial injury and is propagated in
response to subsequent inflammation.[10-12] Periods of episodic
inflammation lead to the degradation of stable atherosclerotic plaque and then to
vulnerable plaque formation. Rupture of vulnerable plaque can lead to growth of the
atherosclerotic plaque or intra-arterial thrombosis and end organ ischemia.[13] Multiple studies have shown that knowledge of both the inflammatory state and
lipid status allows additive information for risk.[14,15]The work of Ridker and colleagues has demonstrated the utility of measuring arterial
inflammation in patients with a narrow range of the non-specific marker
high-sensitivity C-reactive protein (hsCRP; <10 mg/L) as a marker of
cardiovascular risk, even after correcting for lipoprotein levels, age, and other
accepted cardiovascular risk factors. The innovative Justification for the Use of
Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin
(JUPITER) randomized double blind trial demonstrated that risk reduction in patients
based on inflammatory markers leads to reduction of events and mortality.[16]Multiple studies have demonstrated the utility of measuring the circulating of free
myeloperoxidase as a correlate of the risk of presence of vulnerable
plaque.[2,5,17] Heslop et al.[2] showed that patients who underwent elective coronary angiography had a 5-fold
increased hazard ratio for mortality if either MPO or hsCRP was elevated, but they
had a further 4.33-fold increase in hazard ratio if both MPO and hsCRP were
elevated.We have previously modeled the potential return on investment for a commercial health
insurance plan with one million members. An estimated 43,693 cardiovascular events
were estimated to occur over 5 years under a standard-of-care scenario, whereas a
biomarker testing approach using hsCRP, MPO and Lp-PLA2 could yield an estimated
reduction of events by 8.9% (3,908 events) over 5 years.[18] The similarity of the decline in the prevalence of patients with positive MPO
in Figure 2 is reminiscent
of the decline in hsCRP seen in the CANTOS trial with the interleukin 1 beta
monoclonal antibody canakinumab.[3] Thus, our findings suggest that vascular inflammation can be significantly
lowered in patients without the need for expensive biologics.[19]The goal of this study was to determine the extent to which a patient’s risk could be
reduced through the measurement of MPO and the knowledge of inflammatory risk. Our
data demonstrate that within one year of using MPO as a marker of cardiovascular
risk, the number of patients at risk decreased. Not surprisingly, our data
demonstrate that the probability of an abnormal MPO is greater in patients with
HbA1C >6.4%. We demonstrate that, based on inflammatory risk as measured by MPO,
by year 5 patients with HbA1C between 5.7% and 6.4% was reduced to that of patients
with HbA1C <5.7%. Furthermore, the percentage of patients positive for MPO in
these two groups was decreased by 73% over the 5-year period of our study. Patients
with HbA1C >6.4% had residual risk based on MPO, but the percentage of patients
with positive MPO was reduced by 69% over the 5 years studied. Finally, the trends
of positive MPO we observed in different groups of patients based on HbA1C were
similar whether or not patients had LDL levels at target based on ATPIII.These data demonstrate that primary-care physicians can and will respond to increased
cardiovascular risk based on inflammatory markers. Future studies need to focus on
strategies implemented by these physicians that led to decreases in MPO. Because the
percentage of patients with LDL levels greater than goal did not change over the 5
years studied, it is unlikely that the medical approach had to do with simply
increasing the use or dosing of lipid-lowering therapies.
Conclusion
There is growing recognition of the need to identify novel strategies to risk
stratify patients for cardiovascular events. With at least 50% of patients
presenting with acute coronary syndromes having LDL levels at guideline levels based
on ATP III or on statin therapy based on current guidelines, there is a growing need
to identify biomarkers other than lipoproteins. Biomarkers based on vascular
inflammation seem to be a rational approach given the increasing prevalence of
obesity and diabetes, both of which are linked to increased levels of inflammation.
Our study shows that vascular inflammation as measured by MPO is modifiable in this
MDVIP population of patients. Future studies will need to define the strategies
implemented to lower vascular inflammation and whether modification of MPO in this
patient group led to a reduction in cardiovascular events.
Authors: Paul M Ridker; Brendan M Everett; Tom Thuren; Jean G MacFadyen; William H Chang; Christie Ballantyne; Francisco Fonseca; Jose Nicolau; Wolfgang Koenig; Stefan D Anker; John J P Kastelein; Jan H Cornel; Prem Pais; Daniel Pella; Jacques Genest; Renata Cifkova; Alberto Lorenzatti; Tamas Forster; Zhanna Kobalava; Luminita Vida-Simiti; Marcus Flather; Hiroaki Shimokawa; Hisao Ogawa; Mikael Dellborg; Paulo R F Rossi; Roland P T Troquay; Peter Libby; Robert J Glynn Journal: N Engl J Med Date: 2017-08-27 Impact factor: 91.245
Authors: Paul M Ridker; Christopher P Cannon; David Morrow; Nader Rifai; Lynda M Rose; Carolyn H McCabe; Marc A Pfeffer; Eugene Braunwald Journal: N Engl J Med Date: 2005-01-06 Impact factor: 91.245
Authors: Paul M Ridker; Eleanor Danielson; Francisco A H Fonseca; Jacques Genest; Antonio M Gotto; John J P Kastelein; Wolfgang Koenig; Peter Libby; Alberto J Lorenzatti; Jean G MacFadyen; Børge G Nordestgaard; James Shepherd; James T Willerson; Robert J Glynn Journal: N Engl J Med Date: 2008-11-09 Impact factor: 91.245
Authors: Amit Sachdeva; Christopher P Cannon; Prakash C Deedwania; Kenneth A Labresh; Sidney C Smith; David Dai; Adrian Hernandez; Gregg C Fonarow Journal: Am Heart J Date: 2008-10-22 Impact factor: 4.749
Authors: Michelle L O'Donoghue; Eugene Braunwald; Harvey D White; Dylan P Steen; Mary Ann Lukas; Elizabeth Tarka; P Gabriel Steg; Judith S Hochman; Christoph Bode; Aldo P Maggioni; KyungAh Im; Jennifer B Shannon; Richard Y Davies; Sabina A Murphy; Sharon E Crugnale; Stephen D Wiviott; Marc P Bonaca; David F Watson; W Douglas Weaver; Patrick W Serruys; Christopher P Cannon; Dylan L Steen Journal: JAMA Date: 2014-09-10 Impact factor: 56.272