Personalized Prediction of Cardiovascular Benefits and Bleeding Harms From Aspirin for Primary Prevention: A Benefit-Harm Analysis

Vanessa Selak, Rod Jackson, Katrina Poppe, Billy Wu, Matire Harwood, Corina Grey, Romana Pylypchuk, Suneela Mehta, Yeun-Hyang Choi, Andrew Kerr, Sue Wells
Annals of Internal Medicine 2019 September 17

Background: Whether the benefits of aspirin for the primary prevention of cardiovascular disease (CVD) outweigh its bleeding harms in some patients is unclear.

Objective: To identify persons without CVD for whom aspirin would probably result in a net benefit.

Design: Individualized benefit-harm analysis based on sex-specific risk scores and estimates of the proportional effect of aspirin on CVD and major bleeding from a 2019 meta-analysis.

Setting: New Zealand primary care.

Participants: 245 028 persons (43.6% women) aged 30 to 79 years without established CVD who had their CVD risk assessed between 2012 and 2016.

Measurements: The net effect of aspirin was calculated for each participant by subtracting the number of CVD events likely to be prevented (CVD risk score × proportional effect of aspirin on CVD risk) from the number of major bleeds likely to be caused (major bleed risk score × proportional effect of aspirin on major bleeding risk) over 5 years.

Results: 2.5% of women and 12.1% of men were likely to have a net benefit from aspirin treatment for 5 years if 1 CVD event was assumed to be equivalent in severity to 1 major bleed, increasing to 21.4% of women and 40.7% of men if 1 CVD event was assumed to be equivalent to 2 major bleeds. Net benefit subgroups had higher baseline CVD risk, higher levels of most established CVD risk factors, and lower levels of bleeding-specific risk factors than net harm subgroups.

Limitations: Risk scores and effect estimates were uncertain. Effects of aspirin on cancer outcomes were not considered. Applicability to non-New Zealand populations was not assessed.

Conclusion: For some persons without CVD, aspirin is likely to result in net benefit.

Primary Funding Source: Health Research Council of New Zealand.

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John Welden

That’s a whole lot of “likely.” Tarot cards would be as predictive.


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