New Digital ASCVD Risk Prediction Tool and Health Behavioral Changes in Patients

Researchers assessed the effect of a new risk prediction tool on clinical outcomes and behavioral changes in patients with ASCVD.

Web-based communication of personal atherosclerotic cardiovascular disease (ASCVD) risk data can motivate changes in health behavior among middle-aged individuals, according to a study published in Circulation: Genomic and Precision Medicine.

Researchers created a web-based tool for communicating genomic and clinical risks for primary disease prevention of ASCVD and assessed participants’ attitudes and the impact of the information.

A total of 2651 men (mean age, 55.9±5.9 years) and 4691 women (mean age, 55.7±5.7 years) from the GeneRISK study were included and had a baseline health check-up.

Personal risk information for ASCVD was communicated and interpreted for all study participants with use of the web-application. Among the cohort, 89.7% viewed their data at least once.

The participants were then invited to a second health check-up after an average follow-up of 17 months (16.9±5.7 months) and were asked to fill out an e-questionnaire, in which 71% agreed to participate.

The study authors found that 15.4% of participants with a high risk had signed up for health coaching online, 12.4% had weight loss (mean weight loss, -3.9±2.8 kg), 14.2% of smokers reported that they had quit smoking, and 20.8% had visited a doctor. Individuals with an average or low risk signed up for health coaching more frequently compared with those with a high risk (20.2% vs 15.4%, P = .004), although a greater proportion of persons at high risk reported weight loss or saw a physician.

Overall, 42.6% of individuals at high risk for ASCVD had engaged in behavior to lower their disease risk vs 33.5% of individuals in the average to low risk group (P <.001).

Among several study limitations, all participants were aged 45 to 65 years at baseline, did not have prior ASCVD, and were from Finland and of European descent. Also, attendance bias at follow-up may have affected the outcomes.

“Our study demonstrates the power of a digital risk prediction tool facilitating the presentation of polygenic risk information alongside clinical risk factors to patients in a comprehensive way,” the investigators commented. “Not only does combining genomic and clinical information provide a more precise estimate of the overall disease risk on an individual level, our study further shows that both types of risk data independently predict positive health behavior, that is, the higher the risk, the more likely a positive change. Thus, adopting procedures and tools facilitating the use of both genomic and clinical data for ASCVD prediction provides a new basis for enhanced next-generation disease prevention.”

Disclosure: Some of the study authors declared affiliations with biotech, pharmaceutical, and/or device companies. Please see the original reference for a full list of authors’ disclosures.


Widén E, Junna N, Ruotsalainen S, et al. How communicating polygenic and clinical risk for atherosclerotic cardiovascular disease impacts health behavior: an observational follow-up study. Circ Genom Precis Med. Published online February 7, 2022. doi: 10.1161/CIRCGEN.121.003459