Melbourne-based researchers have developed a novel health economic model to inform different health interventions and treatment plans for people at risk of heart attack and stroke by taking into account the cumulative effects of key risk factors throughout their adult life.
Unlike current decision-making models designed to inform primary prevention of cardiovascular disease based on short-term information derived from clinical trials, the new Monash-designed model looks at the impact of multiple 'modifiable risks' in individuals aged between 30 and 84, including low-density lipoprotein-cholesterol ("bad" cholesterol), lipoprotein (a), high blood pressure, smoking and diabetes.
Cardiovascular diseases (CVDs) are the leading cause of death globally. An estimated 17.9 million people died from CVDs in 2019 and of these deaths, 85 per cent were due to heart attack and stroke. Concurrently, most cardiovascular diseases can be prevented by addressing behavioural and environmental risk factors.
Co-lead author and Research Fellow at the Centre for Medicine Use and Safety (CMUS) within the Monash Institute of Pharmaceutical Sciences (MIPS), Dr Jedidiah Morton, said this is the first health economic model to incorporate the long-term cumulative effect of risk factors potentially leading to heart attack or stroke. "Many health economic models for cardiovascular diseases, including heart attack and stroke, are based on randomised clinical trials; however, because they don't incorporate the cumulative effect of changes in risk factors over time, they may underestimate the benefit of therapies as the time horizon of the studies increases," Dr Morton said.
"Our new model will complement evidence from clinical trials because it can also provide estimates of economic costs and benefits of different health interventions relative to an individual's various risk factors spanning over several decades."
Professor Zanfina Ademi, co-lead and senior author also from CMUS, said the model has potential in public health and clinical decision-making when a clinical trial for the intervention simulated is not possible or practical.
"For most long-term studies on the primary prevention of CVD, clinical trials are too costly and limited to pursue. This is where epidemiological modelling using the next best evidence from Mendelian Randomisation plays an important role," Professor Ademi said.
"We believe that this model will appropriately capture all costs and value health outcomes of existing and new health interventions and this approach will identify at-risk individuals early when we take into consideration the cumulative impact of modifiable risk factors, and as such has the potential to save many lives and provide efficient access to prevention."
Professor Ademi said scaling the model up to be implemented at population level would require a systemic change in thinking about prevention.
"If we were to think of modifying risk factors for CVD in the same way we think about clean drinking water, seat belts and vaccination, for example, it could be a game-changer for CVD outcomes in millions of people around the world."
