The global risk approach should be better applied in French hypertensive patients: a comparison between simulation and observation studies

Abstract

Background: The prediction of the public health impact of a preventive strategy provides valuable support for decision-making. International guidelines for hypertension management have introduced the level of absolute cardiovascular risk in the definition of the treatment target population. The public health impact of implementing such a recommendation has not been measured.

Methodology/principal findings: We assessed the efficiency of three treatment scenarios according to historical and current versions of practice guidelines on a Realistic Virtual Population representative of the French population aged from 35 to 64 years: 1) BP≥160/95 mm Hg; 2) BP≥140/90 mm Hg and 3) BP≥140/90 mm Hg plus increased CVD risk. We compared the eligibility following the ESC guidelines with the recently observed proportion of treated amongst hypertensive individuals reported by the Etude Nationale Nutrition Santé survey. Lowering the threshold to define hypertension multiplied by 2.5 the number of eligible individuals. Applying the cardiovascular risk rule reduced this number significantly: less than 1/4 of hypertensive women under 55 years and less than 1/3 of hypertensive men below 45 years of age. This was the most efficient strategy. Compared to the simulated guidelines application, men of all ages were undertreated (between 32 and 60%), as were women over 55 years (70%). By contrast, younger women were over-treated (over 200%).

Conclusion: The global CVD risk approach to decide for treatment is more efficient than the simple blood pressure level. However, lack of screening rather than guideline application seems to explain the low prescription rates among hypertensive individuals in France. Multidimensional analyses required to obtain these results are possible only through databases at the individual level: realistic virtual populations should become the gold standard for assessing the impact of public health policies at the national level.

Figure 1. Gains from the simulation of different scenarios for treatment administration in the RVP.

Points signal the number of events prevented thanks to treatment in scenarios I to III for men and women in each age category. Horizontal bars indicate the median, and vertical lines show the inter-quartile range of the predicted number of events.

Figure 2. Comparison of the prevalence of hypertension estimated in the RVP with that reported by ENNS.

Bars represent the percentage of hypertensive individuals in each category of age in both sexes separately, estimated in the RVP, the ENNS survey and the RVP after reconstitution of data including the proportion of hypertensive subjects taking medications in the MONICA-France cohort. Abbreviations: RVPi, the realistic virtual population initial estimates; ENNS, Etude Nationale Nutrition Santé; RVPr, the reconstituted estimates from the RVP.

Figure 3. Theoretical eligibility from implementing the guidelines and treatment of hypertension in a real setting.

Bars signal the proportion of hypertensive individuals eligible and ineligible for treatment according to the ESC guidelines implemented in the RVP and the proportion of hypertensive subjects that are unknown and untreated, those who are known but untreated and those who are treated in the ENNS survey for each category of age in men and women. Results are expressed as a percentage of all the individuals belonging to each class.

Figure 4. Bivariate distributions in two virtual populations, simulated with and without taking into account their covariance.

Contour plots show the distribution of systolic and diastolic blood pressure on the X and Y axes, respectively. Bars beside plots indicate the scales of colours representing the density of individuals at each level of bivariate values. Panel A, taking into account the covariance. Panel B, covariance = 0.

Figure 5. Procedure to determine the proportions eligible for treatment and the number of CVD deaths prevented in each treatment scenario.

Abbreviations: CVD, cardiovascular death; NEP, number of events prevented; NES, number of eligible subjects.