The Moli-sani risk score, a new algorithm for measuring the global impact of modifiable cardiovascular risk factors

Background: Cardiovascular (CV) disease is preventable through interventions targeting modifiable factors. Most algorithms based on modifiable CV risk factors (CV-rf) have been developed in US populations and do not account for the role of diet. We aimed to assess an algorithm based on modifiable CV-rf including diet, using data from an Italian population. Methods: To derive the Moli-sani Risk Score (MRS), we used data on 16,656 men and women (age ≥ 35 y) from the population of the Moli-sani Study. The Risk-and-Prevention-Study, Italy (N = 8606) acted as external validation cohort and the Life's-Simple-7 score was used as benchmark. The MRS targeted at fatal or non-fatal CV events and included 9 common modifiable CV-rf. Results: After 8.1 years (median) of follow-up, 816 events occurred in the derivation cohort. The MRS was calculated as a weighted sum of its 9 components, with weights reflecting the strength of the association. In comparison with individuals in the first, those in the fourth quartile of the score had hazard ratio (HR) for CV events equal to 3.18 (95%CI: 2.54-3.97). One more point in the score was associated with 7% (6%-8%) and 4% (3%-5%) higher hazard of events in the derivation and validation cohort, respectively. The MRS performed better than the Life's Simple-7 for discrimination. Conclusion: We propose the Moli-sani Risk Score, a validated, performing algorithm able to measure the combined impact that modifiable CV-rf have on CV risk. The score can be used to design preventive interventions, quantify the effectiveness of interventions, and compare different preventive strategies.