Evidence map›Paper›PMID 32382844›Full record

ArticleEuropean radiology2020

The cost-effectiveness of digital breast tomosynthesis in a population breast cancer screening program.

Jing Wang, Xuan-Anh Phi, Marcel J W Greuter, Alicja M Daszczuk, Talitha L Feenstra, Ruud M Pijnappel, Karin M Vermeulen, Nico Buls, Nehmat Houssami, Wenli Lu and 1 more

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
1.1field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

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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

11 authors at 7 institutions in 4 countries.

Jing WangDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. j.wang@umcg.nl.
Xuan-Anh PhiDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Marcel J W GreuterDepartment of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Alicja M DaszczukDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Talitha L FeenstraDepartment of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Ruud M PijnappelDepartment of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Karin M VermeulenDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Nico BulsDepartment of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels, Belgium.
Nehmat HoussamiSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Wenli LuDepartment of Epidemiology and Health Statistics, Tianjin Medical University, Tianjin, China.
Geertruida H de BockDepartment of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
University of Groningen · NLUniversity Medical Center Utrecht · NLTianjin Medical University · CNUniversitair Ziekenhuis Brussel · BEUniversity Medical Center Groningen · NLUniversity of Sydney · AUVrije Universiteit Brussel · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate at which sensitivity digital breast tomosynthesis (DBT) would become cost-effective compared to digital mammography (DM) in a population breast cancer screening program, given a constant estimate of specificity.

methodsIn a microsimulation model, the cost-effectiveness of biennial screening for women aged 50-75 was simulated for three scenarios: DBT for women with dense breasts and DM for women with fatty breasts (scenario 1), DBT for the whole population (scenario 2) or maintaining DM screening (reference). For DM, sensitivity was varied depending on breast density from 65 to 87%, and for DBT from 65 to 100%. The specificity was set at 96.5% for both DM and DBT. Direct medical costs were considered, including screening, biopsy and treatment costs. Scenarios were considered to be cost-effective if the incremental cost-effectiveness ratio (ICER) was below €20,000 per life year gain (LYG).

resultsFor both scenarios, the ICER was more favourable at increasing DBT sensitivity. Compared with DM screening, 0.8-10.2% more LYGs were found when DBT sensitivity was at least 75% for scenario 1, and 4.7-18.7% when DBT sensitivity was at least 80% for scenario 2. At €96 per DBT, scenario 1 was cost-effective at a DBT sensitivity of at least 90%, and at least 95% for scenario 2. At €80 per DBT, these values decreased to 80% and 90%, respectively.

conclusionDBT is more likely to be a cost-effective alternative to mammography in women with dense breasts. Whether DBT could be cost-effective in a general population highly depends on DBT costs. KEY POINTS: • DBT could be a cost-effective screening modality for women with dense breasts when its sensitivity is at least 90% at a maximum cost per screen of €96. • DBT has the potential to be cost-effective for screening all women when sensitivity is at least 90% at a maximum cost per screen of €80. • Whether DBT could be used as an alternative to mammography for screening all women is highly dependent on the cost of DBT per screen.

Indexed as

Cost-Benefit AnalysisAgedBiopsyBreastBreast DensityBreast NeoplasmsComputer SimulationEarly Detection of CancerEuropeFemaleHealth Care CostsHumansMammographyMarkov ChainsMass ScreeningMiddle AgedBreast neoplasmsCost-benefit analysisMammographyMass screeningTomosynthesis

Identifiers

PMID32382844
PMCPMC7476964
OpenAlexW3020931746

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.