Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Dec 19;9(12):e030234.
doi: 10.1136/bmjopen-2019-030234.

Can risk be predicted? An umbrella systematic review of current risk prediction models for cardiovascular diseases, diabetes and hypertension

Francesca Lucaroni  1 , Domenico Cicciarella Modica  2 , Mattia Macino  2 , Leonardo Palombi  3 , Alessio Abbondanzieri  2 , Giulia Agosti  2 , Giorgia Biondi  2 , Laura Morciano  1 , Antonio Vinci  2
Affiliations

Can risk be predicted? An umbrella systematic review of current risk prediction models for cardiovascular diseases, diabetes and hypertension

Francesca Lucaroni et al. BMJ Open. .

Abstract

Objective: To provide an overview of the currently available risk prediction models (RPMs) for cardiovascular diseases (CVDs), diabetes and hypertension, and to compare their effectiveness in proper recognition of patients at risk of developing these diseases.

Design: Umbrella systematic review.

Data sources: PubMed, Scopus, Cochrane Library.

Eligibility criteria: Systematic reviews or meta-analysis examining and comparing performances of RPMs for CVDs, hypertension or diabetes in healthy adult (18-65 years old) population, published in English language.

Data extraction and synthesis: Data were extracted according to the following parameters: number of studies included, intervention (RPMs applied/assessed), comparison, performance, validation and outcomes. A narrative synthesis was performed. Data were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Study selection: 3612 studies were identified. After title/abstract screening and removal of duplicate articles, 37 studies met the eligibility criteria. After reading the full text, 13 were deemed relevant for inclusion. Three further papers from the reference lists of these articles were then added.

Study appraisal: The methodological quality of the included studies was assessed using the AMSTAR tool.

Risk of bias in individual studies: Risk of Bias evaluation was carried out using the ROBIS tool.

Results: Sixteen studies met the inclusion criteria: six focused on diabetes, two on hypertension and eight on CVDs. Globally, prediction models for diabetes and hypertension showed no significant difference in effectiveness. Conversely, some promising differences among prediction tools were highlighted for CVDs. The Ankle-Brachial Index, in association with the Framingham tool, and QRISK scores provided some evidence of a certain superiority compared with Framingham alone.

Limitations: Due to the significant heterogeneity of the studies, it was not possible to perform a meta-analysis. The electronic search was limited to studies in English and to three major international databases (MEDLINE/PubMed, Scopus and Cochrane Library), with additional works derived from the reference list of other studies; grey literature with unpublished documents was not included in the search. Furthermore, no assessment of potential adverse effects of RPMs was carried out.

Conclusions: Consistent evidence is available only for CVD prediction: the Framingham score, alone or in combination with the Ankle-Brachial Index, and the QRISK score can be confirmed as the gold standard. Further efforts should not be concentrated on creating new scores, but rather on performing external validation of the existing ones, in particular on high-risk groups. Benefits could be further improved by supplementing existing models with information on lifestyle, personal habits, family and employment history, social network relationships, income and education.

Prospero registration number: CRD42018088012.

Keywords: cardiovascular diseases; diabetes; hypertension; risk prediction models.

PubMed Disclaimer

Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Study workflow.
Figure 2
Figure 2
Quality assessment scores.
Figure 3
Figure 3
Graphical representation of risk of bias according to the ROBIS tool.
See this image and copyright information in PMC

References

    1. Health statistics and information systems Disease burden and mortality estimates. Cause-specific mortality, 2000–2016. Available: http://www.who.int/healthinfo/global_burden_disease/estimates/en/index1.... [Accessed 17 Jan 2019].
    1. Mills KT, Bundy JD, Kelly TN, et al. Global disparities of hypertension prevalence and control: a systematic analysis of population-based studies from 90 countries. Circulation 2016;134:441–50. 10.1161/CIRCULATIONAHA.115.018912 - DOI - PMC - PubMed
    1. Global Health Observatory (GHO) data Raised blood pressure. Situation and trends. Available: http://www.who.int/gho/ncd/risk_factors/blood_pressure_prevalence_text/en/ [Accessed 18 Jun 2018].
    1. WHO - Health statistics and information systems Disease burden, 2000–2016. Available: https://www.who.int/healthinfo/global_burden_disease/estimates/en/index1... [Accessed 17 Jan 2019].
    1. Shaw LJ, Goyal A, Mehta C, et al. 10-Year Resource Utilization and Costs for Cardiovascular Care. J Am Coll Cardiol 2018;71:1078–89. 10.1016/j.jacc.2017.12.064 - DOI - PMC - PubMed

Publication types