New protein risk score may predict mortality risk in heart failure patients
USA: A tool that measures an array of proteins circulating in the blood can be used to predict the prognosis of patients with heart failure (HF), a recent study has shown. The findings, published in the Annals of Internal Medicine, are the latest to show promise for proteomics as a way to individualize HF treatment choices.
The community-based study of more than 1,000 people in the United States revealed that validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the death risk in HF superior to that of clinical methods.
Heart failure is a complex clinical syndrome with high mortality. There is a lack of precision in the current risk stratification approaches. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of HF patients depends on validation and evidence of clinical benefit.
Kayode O. Kuku, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, and colleagues aimed to develop and validate a protein risk score for mortality in patients with HF.
The researchers studied 1,351 patients with heart failure enrolled in the Rochester Epidemiology Project between 2003 and 2012. The median patient age was 78 years, 48% were women, 29% had an ejection fraction < 40%, the median NT-proBNP level was 8,903 ng/L, and the median MAGGIC score (which uses 13 clinical variables to estimate mortality in HF patients) was 25. During the follow-up that lasted through 2021, 1,013 patients died. The 5-year mortality rate was 52.1%.
To analyze 7,289 plasma proteins, SomaScan Assay (SomaLogic) was used, ultimately creating a risk score based on 38 unique proteins. These included renin, growth/differentiation factor-15, epidermal growth factor receptor, collagen alpha-2[XI] chain, renin, cartilage intermediate layer protein, NT-proBNP, and interleukin-1 receptor-like 1, among others.
The study led to the following findings:
- In the development cohort (n = 855), after adjustment for MAGGIC score, high-risk scores were linked to higher mortality (HR 2.62 per 1-SD increase; 95% CI 2.34-2.93).
- Risk stratification improved with further adjustment for NT-proBNP. Results were consistent in the validation cohort (n = 496).
- The estimated to observed mortality ratio using the protein risk score was 1.01, superior to the ratio obtained with clinical models alone (1.01).
- Calibration also worked well at gauging risk at both the lower and higher extremes, and for both reduced and preserved ejection fraction.
- Adding the protein risk score to the clinical model reclassified patients such that more were in the lowest-risk group (5-year mortality risk ≤ 25%) and more were in the highest-risk group (5-year mortality risk >75%) than when using the clinical model alone.
“By illustrating the potential of high-throughput omics to improve the clinical management of the HF syndrome, our results are directly relevant to clinical practice and strongly support the pursuit of the evaluation of proteomics for this purpose,” the researchers wrote, adding that a potential limitation of their study is that its participants were mainly of European descent.
"There is a need for further studies to prospectively evaluate the score’s performance in diverse populations and determine risk thresholds for interventions," they concluded.
Reference:
Kuku KO, Shearer JJ, Hashemian M, Oyetoro R, Park H, Dulek B, Bielinski SJ, Larson NB, Ganz P, Levy D, Psaty BM, Joo J, Roger VL. Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study. Ann Intern Med. 2024 Jan 2. doi: 10.7326/M23-2328. Epub ahead of print. PMID: 38163367.
