Risk assessment at individual level
In contrast to community-based public health interventions, clinicians are responsible for preventive advice for a particular patient. An important step in determining an individual preventive strategy is to assess the risk of developing a clinically significant outcome, because indicators of the cost-effectiveness ratio of any intervention vary depending on the overall risk of the individual or population.
Since the absolute risk in people with an established disease is high, in order to save one life or prevent one cardiovascular event (SSSob) among them, fewer people with high risk should be treated compared with the number of people with lower risk, even if the decrease in relative risk is the same in both groups.
To illustrate this point, suppose that intervention reduces mortality by 25% in primary and secondary prevention, then a high-risk patient with coronary heart disease (CHD) has a chance to die from cardiovascular disease (CVD) over the next 10 years equal to 20%, while in a patient with a low risk, the chance of dying for the same period is 1%.
To save one life among high-risk individuals, only 20 patients need to be treated for 10 years, and 4 of them will die. Thus, reducing the relative risk by 25% will save one life (3 death instead of 4). In the case of a low risk, so that a 25% reduction in relative risk would lead to 3 deaths instead of 4, 400 people will have to be treated, of whom 4 will also die.
Thus, the total cost of one life saved is significantly lower (1/20 of the cost) among those with a high absolute risk. Costly interventions are usually cost-effective only for high-risk individuals, but with a low intervention cost, the cost-effectiveness relationship can be cost-effective even in low-risk populations.
When forecasting a risk, the “ideal” risk factor (DF) is one whose prevalence prevails in a population that can be easily and safely measured and which has a great predictive value.
The measurement should be inexpensive because cost is a major constraint on the use of imaging techniques such as electron beam tomography (CRT) or MRI. In addition, the frequency of false positives should be low to avoid unnecessary and potentially dangerous consequences. Age and gender are examples of non-modifiable risk factors (RF) that meet these criteria.
Blood pressure and smoking are examples of modifiable risk factors (RF) that are easy to identify. The results of diagnostic tests can also serve as predictors of future cardiovascular events (SSSob).