BACKGROUND: The National Institute for Health and Care Excellence guidelines and the Quality Outcomes Framework require practitioners to use cardiovascular risk scores in assessments for the primary prevention of cardiovascular disease.
AIM: To explore GPs understanding and use of cardiovascular risk scores.
DESIGN AND SETTING: Qualitative study with purposive maximum variation sampling of 20 GPs working in Oxfordshire, UK. Method Thematic analysis of transcriptions of face-to-face interviews with participants undertaken by two individuals (one clinical, one non-clinical).
RESULTS: GPs use cardiovascular risk scores primarily to guide treatment decisions by estimating the risk of a vascular event if the patient remains untreated. They expressed considerable uncertainty about how and whether to take account of existing drug treatment or other types of prior risk modification. They were also unclear about the choice between the older scores, based on the Framingham study, and newer scores, such as QRISK. There was substantial variation in opinion about whether scores could legitimately be used to illustrate to patients the change in risk as a result of treatment. The overall impression was of considerable confusion.
CONCLUSION: The drive to estimate risk more precisely by qualifying guidance and promoting new scores based on partially-treated populations appears to have created unnecessary confusion for little obvious benefit. National guidance needs to be simplified, and, to be fit for purpose, better reflect the ways in which cardiovascular risk scores are currently used in general practice. Patients may be better served by simple advice to use a Framingham score and exercise more clinical judgement, explaining to patients the necessary imprecision of any individual estimate of risk.
OBJECTIVES: To assess whether delaying risk reduction treatment has a different impact on potential life years lost in younger compared with older patients at the same baseline short-term cardiovascular risk.
DESIGN: Modelling based on population data.
METHODS: Potential years of life lost from a 5-year treatment delay were estimated for patients of different ages but with the same cardiovascular risk (either 5% or 10% 5-year risk). Two models were used: an age-based residual life expectancy model and a Markov simulation model. Age-specific case fatality rates and time preferences were applied to both models, and competing mortality risks were incorporated into the Markov model.
RESULTS: Younger patients had more potential life years to lose if untreated, but the maximum difference between 35 and 85 years was <1 year, when models were unadjusted for time preferences or competing risk. When these adjusters were included, the maximum difference fell to about 1 month, although the direction was reversed with older people having more to lose.
CONCLUSIONS: Surprisingly, age at onset of treatment has little impact on the likely benefits of interventions that reduce cardiovascular risk because of the opposing effects of life expectancy, case fatality, time preferences and competing risks. These findings challenge the appropriateness of recommendations to use lower risk-based treatment thresholds in younger patients.