Big data cohort study pinpointing personalised healthcare

Big data cohort study pinpointing personalised healthcare for New Zealanders

New University of Auckland research is helping to unpack the debate as to whether taking aspirin should be recommended for the prevention of heart attack and stroke.

Led by Dr Vanessa Selak of the University’s School of Population Health, the research is also important as it is an example of how big data can improve the health care of all New Zealanders.

“It’s about making more personalised medicine happen,” Dr Selak says.

New Zealand guidelines recommend aspirin (or an alternative antiplatelet medicine) for people who have already had a heart attack or a stroke. This is because antiplatelet medicine lowers the risk of clots forming inside blood vessels. A clot in a blood vessel can lead to a heart attack or stroke, the most common types of cardiovascular disease (CVD).

The challenge is in determining whether aspirin should also be recommended for people at high risk of their first heart attack or stroke. In this group, it is unclear whether the benefits of aspirin (reduction in heart attack and stroke) are outweighed by their harms (increase in bleeding).

But determining its benefits or harms is difficult because these vary according to individual characteristics.

The study looked into the issue by providing estimates of bleeding risk, by sex and age, among people who have not already had a heart attack or stroke. These estimates can help identify in which people the benefits of aspirin are likely to be outweighed by the harms. The next step is to develop a clinical prediction model that will, by taking into account multiple characteristics at the same time, provide a personalised estimate of bleeding risk. Ultimately an aspirin harm-benefit calculator is planned and this will provide an objective assessment of the balance of benefits and harms of aspirin for the prevention of a first heart attack or stroke for individual patients.

It used anonymous patient data of 359,166 people accessed from PREDICT, a web-based decision support programme used in GP practices, mainly in Auckland and Northland.

“There is considerable confusion about the role of aspirin in the primary prevention of CVD because of the difficulty in identifying people most likely to benefit rather than be harmed by aspirin,” Dr Selak says.

“A decision to initiate aspirin therapy for the primary prevention of CVD requires consideration of both treatment benefits (avoided CVD) and harms (additional bleeds).”

“The findings from this Health Research Council-funded research can be used to enhance population-level guidelines by identifying, more accurately, people most likely to have net-benefit (or net-harm) from aspirin and who are therefore most likely to have their future health and wellbeing improved (or harmed) by aspirin.”

The study, was recently published in JAMA: The Journal of the American Medical Association.

Kath McPherson, chief executive of the Health Research Council of New Zealand says studies using big data like this are creating different approaches to medicine.

“We used to think good healthcare for anyone, was good healthcare for all. But studies such as this are now clarifying just how important it is to target, to personalise, to interrogate population data and make better individual approaches and decisions,” she says.

“It is particularly exciting to see findings like this drive a shift towards the right treatments being given to the right people, and fewer people being given medications that actually don’t work for them. Both will ensure better, more targeted healthcare interventions for all.”

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