Types of evidence on risk factors

Types of evidence on risk factors

Evidence on risk factors (RF) is obtained from various sources. Studies on autopsy have shown that atherosclerosis can begin to develop even at an early age, if there are the same RF CVDs as in adults. Establishing a link between cause and effect is a major step in determining predictors, and the results of several studies are needed to select a preventive intervention. Fundamental studies of human physiology made it possible to penetrate into the mechanisms of atherogenesis and helped to establish the biological probability of a potential intervention in order to change these effects.

Observational studies involving people (cohort, prospective, case-control) are extremely useful in determining the attributive risk of a particular factor. Randomized trials can help confirm a causal relationship and are necessary for choosing interventions to reduce risk.

Each of these strategies has strengths and weaknesses. Descriptive studies (for example, the description of a single observation, a series of observations, cross-sectional, cross-cultural studies, the study of population temporal trends) have considerable value because of the ability to generate hypotheses. However, their design does not adequately control potential factors that may obscure obvious associations. Observational studies (eg, cohort, prospective, case-control) can better control potential inaccuracies.

Observational studies are particularly important in determining the attributable risk of a particular factor, when this factor has a great effect, as in the case of smoking and lung cancer. However, when small or moderate effects are studied in observational studies, the number of uncontrollable distorting factors can be as great as the probable risk itself.

In such cases, randomized studies are needed to confirm causality. When the causal relationship between RF and the disease is confirmed, appropriate intervention should be selected and applied. Even if the causal relationship is beyond doubt, research will help quantify the effect of the intervention. When the question arises about the choice between risk and benefit of intervention, randomized studies are needed to determine its net clinical effect.

This provision is important because the degree of associated risk is not necessarily related to the magnitude of the benefits obtained as a result of the intervention. This lack of correlation may be due to the inability of a specific intervention to achieve the desired effect, or the magnitude of the change may not lead to a corresponding change in risk. An example is the difference between the risk of an increase in blood pressure pa 1 mm Hg. st. and less than expected benefit for CHD while reducing blood pressure by the same amount. Similarly, elevated Gmc is considered to be FR KBS, and folic acid reduces Gmc levels, but randomized studies have shown that lowering Gmc levels with folic acid does not reduce the risk of KBS.

Meta-analysis allows a better assessment of the risk associated with a specific risk factor (RF), or the benefit of an intervention. For example, an assessment of the benefits of aspirin in secondary prophylaxis was obtained as a result of a large meta-analysis of data from 300 clinical studies, which demonstrated that in patients with CVD, aspirin reduces the risk of major SSSob by 25%.

After obtaining acceptable assessments of the benefits and risks for a specific risk factor (RF), a cost-effectiveness analysis can help develop guidance for an intervention. To compare interventions, a single currency is used, calculating QALY or a year of life adjusted for disability (disability-adjusted life-year, DALY). The estimates obtained from this analysis depend on the assumptions made in this analysis. Due to the fact that preventive measures are long-lasting (lasting for decades), the consequences of the initial assumptions regarding these measures may be more important than with short-term interventions. However, the cost-effectiveness indicators of interventions for CVD prevention are important because the prevalence of CHD and the cost of treating it are high.

The cost-effectiveness indicator is calculated as the ratio of the net cost to the increase in life expectancy. Interventions with a cost-effectiveness ratio <$ 40,000 for QALY are comparable to other permanent interventions, such as control of hypertension and hemodialysis. Interventions with a cost-effectiveness indicator of <$ 20 thousand for QALY are welcome, while with an indicator of> $ 40 thousand for QALY are usually perceived by insurers as intervention above an acceptable level. The economic costs of ineffective primary prevention measures for persons with modifiable DFs> 2 in the United States annually amount to $ 13.2 billion.

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