- Predicting cardiovascular risk is important for physicians providing patient care and for scientists developing new drugs.
- Scientists can use biomarker surrogates as signs that the risk of cardiovascular disease (CVD) may increase or decrease.
- In the new study, scientists have developed a blood test that offers an accurate and personalized prediction of CVD.
In a new study, scientists report findings that show that a blood test can be used to predict cardiovascular disease.
The study, published in the journal Science Translational Medicine, opens the door to more individualized treatment plans for CVD. It may also improve the speed at which new CVD drugs can be identified and developed.
When a new drug is developed, scientists need to make sure it is both effective and safe. This is a rigorous process that can often take many years. While important, this significantly slows down the speed at which new drugs can be developed and also increases costs.
One way to speed up and reduce the cost of drug development without sacrificing efficacy or safety is to use a surrogate biomarker as a risk predictor.
If a surrogate can reliably predict risk, some stages of clinical trials can be simplified.
Finding a surrogate that can accurately predict the risk of certain diseases could also directly benefit patients. If a clinician can measure a reliable surrogate, they can potentially prevent a disease before it develops, reducing the risks for the patient.
medical news today talked with Dr. Stephen Williams — chief medical officer at SomaLogic and corresponding author of the present study — who emphasized the importance of surrogates, particularly for CVD risk.
“Substitutes are the ‘holy grail’ in drug development and personalized medicine.”
“For situations where studies of clinical cardiovascular outcomes are needed today, a surrogate allows unsafe or ineffective drug candidates to be terminated early and cheaply and supports the acceleration of safe and effective drugs. Test participants do not need to have events or die to contribute to the signal.”
“In personalized medicine, a surrogate allows cost-effective allocation of treatments to the people who need them most and potentially increases uptake of new, more effective drugs for better outcomes,” said Dr. Williams.
In 2004, the United States Food and Drug Administration (FDA) published
However, in subsequent years, this did not happen. Dr. Williams explained to MNT why it took so long to comply with the FDA recommendation.
“Substitutes are highly valuable, but they also have big consequences for mistakes – for example, the approval of an unsafe or ineffective drug. The weight of evidence required is therefore very high in order to be confident that its value in patient care exceeds the possible consequence of errors.”
Dr. Williams highlighted that a surrogate needs to be able to do three things: first, accurately predict likely clinical outcomes; second, being able to change as potential risks change; and third, work no matter what the risk factor.
“It’s quite common to do Item 1 – for example, risk prediction from artificial intelligence approaches to medical records or combinations of risk factors or genetic factors. But generally these factors also cannot do 2 – be faithful in response to change in risk.”
“This is because they are immutable – for example, genetic, demographic or medical history – or they are reverse causal – for example, artificial intelligence applied to medical records often selects the number of medications a patient is taking as a predictor of risk, so taking someone off all their drugs would paradoxically and erroneously create a lower-risk prediction.”
The Doctor. Williams said he and his team were able to comply with the FDA’s recommendation because SomaLogic’s business model supported the research needed to develop the CVD replacement, based on the FDA’s proposed frameworks.
To develop the test, Dr. Williams and his colleagues analyzed blood plasma samples from 22,849 people.
They studied 5,000 proteins from these samples and, using machine learning, identified 27 proteins that together could predict the risk of stroke, heart attack, heart failure or death over a 4-year period.
Talking to MNT, Dr. Rebekah Gundry – professor and vice chair of the Department of Cellular and Integrative Physiology at the University of Nebraska Medical Center – said that “clinically, these findings are potentially very important.” The Doctor. Gundry, who was not involved in the study, is also the director of the CardiOmics Program at the Center for Heart & Vascular Research atUniversity of Nebraska.
“Having a panel of 27 markers that could be used to predict cardiovascular risk would be an improvement over current risk calculators such as high cholesterol, which can serve as an indicator for all of us as an average but is a poor predictor. for the individual and does not provide good information about when a cardiovascular event is likely to occur,” said Dr. Gundry.
The Doctor. Gundry said the findings would help in the goal of preventing the disease before it requires significant treatment.
“One of the main goals of cardiovascular research is to find new ways to predict patient outcomes as soon as possible after disease onset, because prevention is always easier than reversal. Basically, we want to know what’s going to happen early enough to be able to change the outcome.”
“Having a simple blood test provide information on all major cardiovascular outcomes and deaths would have a tremendous impact on clinical decisions about the timing and nature of interventions to prevent or slow the progression of cardiovascular disease.”
– Dr. gundry
“Proteins play critical roles, which is why they have been used so effectively as indicators. The study by Williams and colleagues provides evidence that simultaneous measurement of a panel of circulating proteins, including proteins previously associated with cardiovascular disease and those with no known prior associations, may provide a pathway to predict cardiovascular outcomes,” said Dr. Gundry.