Evidence map›Paper›PMID 31862737›Full record

SynthesisBMJ open2019

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

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

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 39 citations in OpenAlex.

  1. Pooled it
  2. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2022
    Guideline
  3. Pooled it
  4. Article
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  8. Prediction of early-onset bipolar using electronic health records.Journal of child psychology and psychiatry, and allied disciplines · 2025
    Article
  9. Metabolic syndrome risk prediction in an Australian sample with first-episode psychosis using the psychosis metabolic risk calculator: A validation study.Australasian psychiatry : bulletin of Royal Australian and New Zealand College of Psychiatrists · 2025
    Article
  10. Observational
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  12. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Francesca LucaroniBiomedicine and Prevention, University of Rome Tor Vergata, Roma, Lazio, Italy.
Domenico Cicciarella ModicaBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy.
Mattia MacinoBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy.
Leonardo PalombiBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy palombi@uniroma2.it.ORCID 0000-0003-1806-5278
Alessio AbbondanzieriBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy.
Giulia AgostiBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy.
Giorgia BiondiBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy.
Laura MorcianoBiomedicine and Prevention, University of Rome Tor Vergata, Roma, Lazio, Italy.
Antonio VinciBiomedicine and Prevention, Università degli Studi di Roma Tor Vergata Facoltà di Medicina e Chirurgia, Roma, Lazio, Italy.ORCID 0000-0002-4915-7733
University of Rome Tor Vergata · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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.

designUmbrella 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.

resultsSixteen 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.

conclusionsConsistent 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.

Indexed as

Models, StatisticalCardiovascular DiseasesDiabetes MellitusHumansHypertensionPrognosisReproducibility of ResultsRisk AssessmentRisk Factorscardiovascular diseasesdiabeteshypertensionrisk prediction models

Identifiers

PMID31862737
PMCPMC6937066
OpenAlexW2996239280

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.