Quantifying the health benefits of chronic disease prevention: a fresh approach using cardiovascular disease as an example

Current methods of determining the proportion of people who benefit from a preventive intervention and the years of life gained can underestimate the former and overestimate the latter. We describe how to overcome these errors, using two examples relating to the prevention of myocardial infarction (MI) and stroke, one using a specified polypill daily from age 50 and another reducing salt intake in the population. Standard life table analysis was used to calculate the person-years of life gained without an MI or stroke, based on estimates of the incidence of these disorders in England and Wales. The proportion of individuals who benefit was taken as everyone who would, without treatment, have an MI or stroke (holistic model), rather than limiting the benefit to the proportion calculated from the relative risk reduction (reductionist model), as is current practice. Under the holistic model, 33 % of people who take the polypill from age 50 benefit, gaining, on average, 8 years of life without an MI or stroke (19 % and 14 years under the reductionist model). Estimates for reducing salt intake by 6 g/day are 33 % and 2.8 years respectively under the holistic model (6 % and 16 years under the reductionist model). In the prevention of disorders such as stroke by reducing exposure to causal factors such as blood pressure, the use of a holistic model corrects the underestimation of the proportion of people who benefit and the overestimation of their years of life gained associated with current methods.     

A cost-benefit analysis of a cardiovascular disease prevention trial, using folate supplementation as an example.

OBJECTIVES: This study illustrates a cost-benefit analysis of clinical trial design, using as an example a trial of folate supplementation to prevent cardiovascular disease. METHODS: Bayesian statistical and decision-analytic techniques were used to estimate the cost-benefit and sample size of a placebo-controlled trial of folate targeted to US citizens, aged 35 to 84 years, with elevated serum homocysteine levels. The main end point is event-free survival (i.e., survival without new ischemic heart disease or stroke) at 5 years. RESULTS: Because the screening cost and annual cost and inconvenience of taking folate is small compared with the consequences of stroke, ischemic heart disease, or death, the increase in 5-year event-free survival with folate that should compel the use of folate is just 1.1%. The sample size per group needed to establish this level of folate's medical effectiveness is estimated to be 17310. Such a trial would provide an expected societal cost-benefit savings exceeding $11 billion within 15 years. CONCLUSIONS: This study illustrates how Bayesian methods may help in assessing the societal cost-benefit consequences of proposed disease prevention trials, deciding which trials are worth sponsoring, and designing cost-effective trials.     

Use of a marginal structural model to determine the effect of aspirin on cardiovascular mortality in the Physicians' Health Study

The 1982-1988 aspirin component of the Physicians' Health Study, a randomized trial of aspirin and beta-carotene in primary prevention of cardiovascular disease and cancer among 22,071 US male physicians, was terminated early primarily because of a statistically extreme 44% reduction in first myocardial infarction, with inadequate precision and no apparent effect on the primary endpoint, cardiovascular death. Because of the demonstrated efficacy of aspirin in secondary prevention of cardiovascular death, nonfatal cardiovascular events may simultaneously be time-dependent confounders and intermediate variables. Aspirin use is strongly influenced by these as well as other diseases, side effects, and cardiovascular risk factors. The authors used a marginal structural model with time-dependent inverse probability weights to estimate the underlying causal effect of aspirin on cardiovascular mortality. Although intention-to-treat analyses found no effect (rate ratio = 1.00, 95% confidence interval (CI): 0.72, 1.38), the estimated causal rate ratio was altered to 0.75 but remained nonsignificant (95% CI: 0.48, 1.16). As-treated analyses suggested a more modest effect of aspirin use (rate ratio = 0.90, 95% CI: 0.65, 1.25). Although the numbers of cardiovascular deaths were insufficient to evaluate this endpoint definitively, use of such methods holds much potential for controlling time-varying confounders affected by previous exposure.     

Medicalisation,risk and the use of statins for primary prevention of cardiovascular disease: a scoping review of the literature

Primary prevention of cardiovascular disease has been a site of medicalisation, as demonstrated by the significant increase in the use of cholesterol-lowering drugs, statins, over the last thirty years. While this is welcomed by many in the medical community, others have criticised the expansion of statin use to low-risk people. In the context of this debate, the aim of this article is to present a broad scoping review of the literature on how preventative health, risk and ‘candidacy’ for statin treatment are perceived and negotiated by clinicians and patients. We examine how evidence and knowledge about cardiovascular risk reduction is produced, interpreted and communicated and how patients’ gender, socio-demographic and cultural differences may impact patterns of statin use. We found that few studies differentiated between the use of statins in those with and those without established cardiovascular disease, despite the fact that the majority of statin users, and women in particular, fall into the primary prevention category. In this context, the process of medicalisation is predicated on healthy individuals being subject to medical surveillance of risk factors, which have acquired the status of disease in their own right. Central to this process has been the heuristic that identifies elevated cholesterol as a medical problem warranting statin treatment, as well as the difficulties encountered by doctors and patients in understanding, interpreting and communicating risk. This individualised construction of risk and disease has largely ignored the supposedly widely recognised social and political determinants of health and illness.