VOLUME 10 NUMBER 2 • JUNE 2013
59
SA JOURNAL OF DIABETES & VASCULAR DISEASE
REVIEW
Correspondence to: Dr Andre Pascal Kengne
South African Medical Research Council, PO Box
19070, Tygerberg,7505, Cape Town, South Africa
E-mail:
S Afr J Diabetes Vasc Dis
2013;
10
: 59–64
The ADVANCE cardiovascular risk model and current
strategies for cardiovascular disease risk evaluation in
people with diabetes
Andre Pascal Kengne
Abstract
Purpose:
To critically examine existing approaches to
cardiovascular disease (CVD) risk evaluation in people with
diabetes, and discuss the use of accurate and validated
absolute CVD risk tool as an appropriate basis for CVD
prevention in people with diabetes.
Methods:
Narrative review, using evidence from the ADVANCE
study and all relevant publications identified via PubMed
MEDLINE.
Results:
There is sufficient evidence that diabetes does not
confer a CVD risk equivalent to that in non-diabetic people
with existing CVD in all circumstances. In people with
diabetes, CVD risk follows a gradient. Reliably capturing this
gradient depends upon an adequate combination of several
risk factors. Many global CVD risk tools applicable to people
with diabetes have been developed. Those derived from
older cohorts are less accurate in contemporary populations
and many newer tools have not been tested. The ADVANCE
risk engine, recently developed from the large multinational
ADVANCE study, showed acceptable performance on the
ADVANCE population and largely outperformed the popular
Framingham risk equation when tested on the multinational
DIAB-HYCAR cohort of people with type 2 diabetes.
Conclusions:
The high-risk status conferred by diabetes does
not preclude estimation of absolute CVD risk using tools
such as the ADVANCE risk engine and its use as the basis
for initiating and intensifying CVD preventative measures.
Adopting such an accurate and validated tool will likely
improve prescriptions and outcomes of diabetes care.
Keywords:
diabetesmellitus, cardiovascular disease, risk evaluation,
ADVANCE, absolute risk
Submitted 6/5/2013, accepted 10/6/2013
Introduction
Cardiovascular disease (CVD), the leading global killer, is
multifactorial by nature. No single risk factor taken alone is able to
distinguish people who will go on to develop a cardiovascular event
from those who will not. This consideration forms the basis of the
contemporary multifactorial approaches to CVD risk evaluation and
reduction. A key aim of CVD risk evaluation is to identify those in the
population who’s health outcomes can be modified by performing
more medical tests, starting treatments to reduce the level of risk
factors or increasing the doses of prescribed risk reducing therapies.
1,2
Estimated risks are also used to educate patients about their chances
of experiencing a cardiovascular event within a given time period (for
example, five or ten years). Equipped with this knowledge, patients
are likely to be more motivated to adopt healthy lifestyle measures
and/or to observe prescribed risk modifying treatments. These
patients are alsomore likely to regularly report back to their healthcare
provider for monitoring and adaptation of treatments, to lower and
maintain their risk factors at optimal levels. Concerning CVD in
people with diabetes, healthcare providers who see these patients on
a routine basis are interested in gauging the chances of their patients
developing any major CVD event over a reasonable period of time
(often five to ten years); and not just specific components such as
stroke or myocardial infarction. These busy healthcare providers
are also interested in assessing the CVD risk of their patients using
accurate and validated global CVD risk evaluation tools.
3-5
In the general population, efforts to develop reliable tools for
evaluating CVD risk based on a combination of several risk factors
have paralleled efforts to improve our understanding of the
determinants of CVD, and the more efficient ways to control them.
6
These efforts were initially led by the Framingham investigators,
and more recently by investigators from other parts of the world.
6,7
The first attempts to develop such tools from the Framingham
study date back to the year 1967.
8
These first tools however, did
not account for diabetes status, nor for any other indicator of
chronic hyperglycaemia. Although many subsequent Framingham
tools took diabetes status into consideration, the uptake of the
Framingham tools in people with diabetes around the world has
remained very limited, resulting in the adoption of multivariable
CVD tools in people with diabetes to lag behind the general
population. One reason was the lack of trust among researchers
on the validity of the Framingham tools in people with diabetes,
due to the relatively small number of people with diabetes in the
Framingham cohort; and the non-inclusion of other indicators of
exposure to chronic hyperglycaemia in the Framingham tools.
9
Another major reason was the publication in the late 1990’s of a
study from Finland suggesting that people with diabetes but no
history of cardiovascular disease, had a future risk of CVD similar
to the risk of non-diabetic people who have survived from a CVD
event in the past.
10
This study inspired the concept of diabetes as a
‘CVD risk equivalent’ based on which, people with diabetes should
be treated with cardiovascular risk reducing therapies such as statins
or aspirin without taking into consideration their absolute CVD risk
