Evidence map›Paper›PMID 31352417›Full record

ArticleBMJ open2019

Bragatston study protocol: a multicentre cohort study on automated quantification of cardiovascular calcifications on radiotherapy planning CT scans for cardiovascular risk prediction in patients with breast cancer.

Marleen J Emaus, Ivana Išgum, Sanne G M van Velzen, H J G Desirée van den Bongard, Sofie A M Gernaat, Nikolas Lessmann, Margriet G A Sattler, Arco J Teske, Joan Penninkhof, Hanneke Meijer and 3 more

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03206333 (Automated Quantification of Coronary Artery Calcifications on Radiotherapy Planning CTs for Cardiovascular Risk Prediction in Breast Cancer Patients), which is not on this map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.3field-weighted citation impact, top 11% 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.

NCT03206333 completednot on this map

Automated Quantification of Coronary Artery Calcifications on Radiotherapy Planning CTs for Cardiovascular Risk Prediction in Breast Cancer Patients: the BRAGATSTON Study

TypeobservationalSponsorUMC UtrechtRan2017 to 2020Enrolled16,000ConditionsBreast Cancer, Cardiovascular Diseases
3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
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  8. Academic patterns of practice regarding CT simulation scans and radiology review.Journal of medical imaging and radiation sciences · 2022
    Article
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  10. Generative models for reproducible coronary calcium scoring.Journal of medical imaging (Bellingham, Wash.) · 2022
    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

13 authors at 5 institutions in 2 countries.

Marleen J EmausImaging Division, University Medical Center Utrecht, Utrecht, The Netherlands.
Ivana IšgumImage Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
Sanne G M van VelzenImage Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
H J G Desirée van den BongardDepartment of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
Sofie A M GernaatJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Nikolas LessmannImage Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.ORCID 0000-0001-7935-9611
Margriet G A SattlerDepartment of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Arco J TeskeDepartment of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Joan PenninkhofDepartment of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Hanneke MeijerDepartment of Radiation Oncology, Radboudumc, Nijmegen, The Netherlands.
Jean-Philippe PignolDepartment of Radiation Oncology, Dalhousie University, Halifax, Nova Scotia, Canada.
Helena M VerkooijenImaging Division, University Medical Center Utrecht, Utrecht, The Netherlands.
Bragatston study group
University Medical Center Utrecht · NLErasmus MC Cancer Institute · NLDalhousie University · CARadboud University Nijmegen · NLUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCardiovascular disease (CVD) is an important cause of death in breast cancer survivors. Some breast cancer treatments including anthracyclines, trastuzumab and radiotherapy can increase the risk of CVD, especially for patients with pre-existing CVD risk factors. Early identification of patients at increased CVD risk may allow switching to less cardiotoxic treatments, active surveillance or treatment of CVD risk factors. One of the strongest independent CVD risk factors is the presence and extent of coronary artery calcifications (CAC). In clinical practice, CAC are generally quantified on ECG-triggered cardiac CT scans. Patients with breast cancer treated with radiotherapy routinely undergo radiotherapy planning CT scans of the chest, and those scans could provide the opportunity to routinely assess CAC before a potentially cardiotoxic treatment. The Bragatston study aims to investigate the association between calcifications in the coronary arteries, aorta and heart valves (hereinafter called 'cardiovascular calcifications') measured automatically on planning CT scans of patients with breast cancer and CVD risk. METHODS AND ANALYSIS: In a first step, we will optimise and validate a deep learning algorithm for automated quantification of cardiovascular calcifications on planning CT scans of patients with breast cancer. Then, in a multicentre cohort study (University Medical Center Utrecht, Utrecht, Erasmus MC Cancer Institute, Rotterdam and Radboudumc, Nijmegen, The Netherlands), the association between cardiovascular calcifications measured on planning CT scans of patients with breast cancer (n≈16 000) and incident (non-)fatal CVD events will be evaluated. To assess the added predictive value of these calcifications over traditional CVD risk factors and treatment characteristics, a case-cohort analysis will be performed among all cohort members diagnosed with a CVD event during follow-up (n≈200) and a random sample of the baseline cohort (n≈600). ETHICS AND DISSEMINATION: The Institutional Review Boards of the participating hospitals decided that the Medical Research Involving Human Subjects Act does not apply. Findings will be published in peer-reviewed journals and presented at conferences. TRIAL REGISTRATION NUMBER: NCT03206333.

Indexed as

Breast NeoplasmsCalcinosisCancer SurvivorsCase-Control StudiesCohort StudiesCoronary Artery DiseaseDecision Making, Computer-AssistedDeep LearningFemaleHumansRisk AssessmentTomography, X-Ray Computedbreast cancercardiovascular diseasecoronary artery calcificationsdeep learning algorithmpredictionradiotherapy planning CT-scan

Identifiers

PMID31352417
PMCPMC6661654
OpenAlexW2964838955

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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.