ESPEYB19 14. Science and Medicine Risk and Outcome (5 abstracts)
14.9. A proteomic surrogate for cardiovascular outcomes that is sensitive to multiple mechanisms of change in risk
Williams SA , Ostroff R , Hinterberg MA , Coresh J , Ballantyne CM , Matsushita K , Mueller CE , Walter J , Jonasson C , Holman RR , Shah SH , Sattar N , Taylor R , Lean ME , Kato S , Shimokawa H , Sakata Y , Nochioka K , Parikh CR , Coca SG , Omland T , Chadwick J , Astling D , Hagar Y , Kureshi N , Loupy K , Paterson C , Primus J , Simpson M , Trujillo NP & Ganz P
Sci Transl Med. 2022 Apr 6;14(639):eabj9625; PMID 35385337 doi: 10.1126/scitranslmed.abj9625https://www.science.org/doi/10.1126/scitranslmed.abj9625
Brief Summary: This international study, led by Dr. Stephens Williams from Boulder, Colorado, USA, developed a surrogate biomarker from 27 circulating proteins to predict the risk of having a cardiovascular disease (CVD) event in the next 4 years.
The study used data from >30 000 plasma samples of >20 000 participants from 9 large clinical studies. From a total of 5,000 proteins measured, a machine learning approach selected 27 proteins with high prognostic ability to predict the 4-year likelihood of myocardial infarction, stroke, heart failure, or death. In a validation cohort, the 27-protein model performed twice as well as previous tests, and also performed well in individuals with pre-existing conditions putting them at high risk for CVD events, including individuals with a previous heart attack or stroke, cancer survivors, individuals with diabetes or smokers.
This test can be used as a marker to monitor whether a patient is optimally treated according to their CVD risk profile. It may also help to accelerate the process of drug development, as it would give an immediate measure of health during clinical trials, rather than having to wait in uncertainty for the benefits or risks that may manifest only after long-term treatment.
Article tools
My recent searches
My recently viewed abstracts
Authors
ESPE Yearbook of Paediatric Endocrinology
ISSN 1662-4009 (Online)
© Bioscientifica 2024 |
Privacy policy |
Cookie settings
BiosciAbstracts
Bioscientifica Abstracts is the gateway to a series of products that provide a permanent, citable record of abstracts for biomedical and life science conferences.
Find out more