Evidence map›Paper›PMID 34575652›Full record

ArticleJournal of personalized medicine2021

Second-Generation 3D Automated Breast Ultrasonography (Prone ABUS) for Dense Breast Cancer Screening Integrated to Mammography: Effectiveness, Performance and Detection Rates.

Gianluca Gatta, Salvatore Cappabianca, Daniele La Forgia, Raffaella Massafra, Annarita Fanizzi, Vincenzo Cuccurullo, Luca Brunese, Alberto Tagliafico, Roberto Grassi

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 10% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Study on ABUS Applicability for Rural Women With Low Health Resources in China-Large-Scale Population, Non-Opportunistic Screening.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025
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  7. Review
  8. Review
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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 4 institutions in 1 country.

Gianluca GattaDipartimento di Medicina di Precisione Università della Campania "Luigi Vanvitelli", 80131 Napoli, Italy.ORCID 0000-0003-0874-8294
Salvatore CappabiancaDipartimento di Medicina di Precisione Università della Campania "Luigi Vanvitelli", 80131 Napoli, Italy.
Daniele La ForgiaIRCCS Istituto Tumori "Giovanni Paolo II", 70124 Bari, Italy.ORCID 0000-0002-3902-4523
Raffaella MassafraIRCCS Istituto Tumori "Giovanni Paolo II", 70124 Bari, Italy.
Annarita FanizziIRCCS Istituto Tumori "Giovanni Paolo II", 70124 Bari, Italy.ORCID 0000-0002-2729-9896
Vincenzo CuccurulloDipartimento di Medicina di Precisione Università della Campania "Luigi Vanvitelli", 80131 Napoli, Italy.ORCID 0000-0003-0474-7163
Luca BruneseDipartimento di Medicina e Scienze della Salute "Vincenzo Tiberio"-Università degli Studi del Molise, 86100 Campobasso, Italy.
Alberto TagliaficoDepartment of Health Sciences, University of Genoa, 16126 Genoa, Italy.ORCID 0000-0003-1736-0697
Roberto GrassiDipartimento di Medicina di Precisione Università della Campania "Luigi Vanvitelli", 80131 Napoli, Italy.
University of Campania "Luigi Vanvitelli" · ITIstituto Tumori Bari · ITUniversity of Genoa · ITUniversity of Molise · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In our study, we added a three-dimensional automated breast ultrasound (3D ABUS) to mammography to evaluate the performance and cancer detection rate of mammography alone or with the addition of 3D prone ABUS in women with dense breasts. Our prospective observational study was based on the screening of 1165 asymptomatic women with dense breasts who selected independent of risk factors. The results evaluated include the cancers detected between June 2017 and February 2019, and all surveys were subjected to a double reading. Mammography detected four cancers, while mammography combined with a prone Sofia system (3D ABUS) doubled the detection rate, with eight instances of cancer being found. The diagnostic yield difference was 3.4 per 1000. Mammography alone was subjected to a recall rate of 14.5 for 1000 women, while mammography combined with 3D prone ABUS resulted in a recall rate of 26.6 per 1000 women. We also observed an additional 12.1 recalls per 1000 women screened. Integrating full-field digital mammography (FFDM) with 3D prone ABUS in women with high breast density increases and improves breast cancer detection rates in a significant manner, including small and invasive cancers, and it has a tolerable impact on recall rate. Moreover, 3D prone ABUS performance results are comparable with the performance results of the supine 3D ABUS system.

Indexed as

3D prone ABUSbreast cancer detectionbreast cancer screeningbreast density

Identifiers

PMID34575652
PMCPMC8468126
OpenAlexW3196678605

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.