CARDIOVASCULAR JOURNAL OF AFRICA • Vol 24, No 9/10, October/November 2013
376
AFRICA
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 cardio-
vascular disease (CVD) risk evaluation in people with diabe-
tes, and discuss the use of accurate and validated absolute
CVD risk tools as an appropriate basis for CVD prevention
in people with diabetes.
Methods
:This was a 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 on 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 popu-
lar Framingham risk equation when tested on the multina-
tional 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:
diabetes mellitus, cardiovascular disease, risk evalu-
ation, ADVANCE, absolute risk
Submitted 6/5/13, accepted 10/6/13
Cardiovasc J Afr
2013;
24
: 376–381
DOI: 10.5830/CVJA-2013-078
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 10 years).
Equipped with this knowledge, patients are more likely to be
motivated to adopt healthy lifestyle measures and/or to observe
prescribed risk-modifying treatments. These patients are also
more 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 10 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 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 or 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 1990s 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 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 levels.
However, the concept of diabetes as a CVD risk equivalent has
been losing ground in recent years, with the accumulating evidence
challenging its validity in all circumstances,
11
and supporting the
South African Medical Research Council, Tygerberg, Cape
Town, South Africa
ANDRE PASCAL KENGNE,
