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


Journal

International journal of cardiology
ISSN: 1874-1754
Titre abrégé: Int J Cardiol
Pays: Netherlands
ID NLM: 8200291

Informations de publication

Date de publication:
15 10 2023
Historique:
received: 23 03 2023
revised: 10 06 2023
accepted: 28 07 2023
medline: 8 9 2023
pubmed: 2 8 2023
entrez: 1 8 2023
Statut: ppublish

Résumé

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. 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 37527754
pii: S0167-5273(23)01071-9
doi: 10.1016/j.ijcard.2023.131228
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

131228

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None.

Auteurs

Augusto Di Castelnuovo (A)

Mediterranea Cardiocentro, Napoli, Italy.

Marialaura Bonaccio (M)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Simona Costanzo (S)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Amalia De Curtis (A)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Mariarosaria Persichillo (M)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Teresa Panzera (T)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Francesca Bracone (F)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Damiano Baldassarre (D)

Centro Cardiologico Monzino, IRCCS, Milan, Italy; Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy.

Maria Carla Roncaglioni (MC)

Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Milan, Italy.

Marta Baviera (M)

Laboratory of Cardiovascular Prevention, Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Milan, Italy.

Chiara Cerletti (C)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Maria Benedetta Donati (MB)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Giovanni de Gaetano (G)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy.

Licia Iacoviello (L)

Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli (IS), Italy; Department of Medicine and Surgery, University of Insubria, Varese, Italy. Electronic address: licia.iacoviello@moli-sani.org.

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Classifications MeSH