The index of this PhD thesis is available here.
What is the significance of this PhD
thesis?
When you come
to a doctor, the doctor will usually ask for two types of cholesterol to be
measured: the ‘good’ HDL cholesterol and the ‘bad’ LDL cholesterol. From a
technical point of view, this approach is outdated, since for quite some time
we have been able to measure many more types or ‘subfractions’ of cholesterol;
now measurements can distinguish up to forty such subfractions. Yet from a
medical perspective, these detailed measurements are hard to relate to cardiovascular
risk in a straightforward way. So if any of this detailed information is
reported to a doctor, it is reported in a simplified fashion.
The research in
this PhD thesis set out to construct a mathematical model that is able to make
the most out of the information contained in the detailed cholesterol
measurements. The model is able to report information about the status of
cholesterol metabolism, in a form we call ‘lipoprotein metabolic ratios’. We
have found that by using a combination of two such ratios, we are able to
significantly improve cardiovascular risk prediction. The one ratio, called the
‘extrahepatic lipolysis ratio’ is especially important to determine risk when
someone is taking blood pressure medication. If someone takes such medication,
but the body is not handling fat well, that person might be at high risk for a
cardiovascular event. The second ratio, the ‘hepatic turnover ratio’, indicates
how well the liver works. If someone is on the border between low and medium
risk, this ratio can make the difference between having to take cholesterol-lowering
medication yes or no.
We have shown
this improved risk prediction using subjects from the classical ‘Framingham
Heart Study’ cohort; the results will need to be replicated in other trials.
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