Evidence map›Paper›PMID 39961709›Full record

ArticleBMJ open2025

National yearly cost of breast cancer screening in the USA and projected cost of advocated guidelines: a simulation study with life table modelling.

Kimberly Badal, James Staib, Jeffrey A Tice, Mi-Ok Kim, Martin Eklund, Leslie Wilson, Stacey Dacosta Byfield, Kierstin Catlett, Liz Maffey, Rashna Soonavala and 2 more

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
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

12 authors.

Kimberly BadalDepartment of Surgery, University of California San Francisco, San Francisco, California, USA kimberly.badal@ucsf.edu.ORCID http://orcid.org/0000-0001-7776-0831
James StaibOptum Labs, Eden Prairie, Minnesota, USA.
Jeffrey A TiceDepartment of Medicine, University of California San Francisco, San Francisco, California, USA.
Mi-Ok KimDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.
Martin EklundDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Leslie WilsonDepartment of Medicine, Department of Clinical Pharmacy, University of California San Francisco, San Francisco, California, USA.
Stacey Dacosta ByfieldOptum Labs, Eden Prairie, Minnesota, USA.
Kierstin CatlettOptum Center for Research and Innovation, UnitedHealth Group, Minnetonka, Minnesota, USA.
Liz MaffeyOptum Labs, Eden Prairie, Minnesota, USA.
Rashna SoonavalaDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Yiwey ShiehDepartment of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA.
Laura J EssermanDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.

Funding

Prediction of interval breast cancer risk using genetic variantsK08CA237829 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SHIEH, YIWEY · 2019 to 2023
$1.3M
NCI NIH HHS K08 CA237829
6 · The paper itself

Abstract

objectiveThe aim of this study was to estimate the total national direct cost of breast cancer screening from 2019 to 2022 and project the total national cost and average lifetime cost of screening per woman for three current guidelines.

designWe estimated the national cost of screening from 2019 to 2022, and per cancer detected in 2022, using real-world data on the number of mammograms performed per year. We also projected the national cost of screening using life table modelling for three guidelines: 2021/2023 American College of Radiology (ACR), 2023 American Cancer Society (ACS) and 2024 United States Preventative Services Task Force (USPSTF). The average lifetime cost to screen one woman until age 74 years with each guideline was also estimated. The Optum Labs Data Warehouse was used to estimate commercial and Medicare costs and recall rates. Sensitivity analyses were used to estimate uncertainty and determine which inputs had the largest impact on total national costs.

settingThis study was conducted for the USA.

participantsWomen eligible for breast cancer screening.

interventionsDigital mammograms (2D) or digital breast tomosynthesis (3D) and/or MRI. PRIMARY OUTCOME MEASURE: Total national cost of screening calculated as the sum of screening and recall costs. Average lifetime cost of screening per woman until 74 years.

resultsNationally, screening cost approximately US$11 billion (B) per year from 2019 to 2022 with approximately 37% of eligible women screened each year. In 2022, screening cost US$55 471 per 3D-detected and US$44 000 per 2D-detected invasive or ductal carcinoma in situ case. Using target yearly participation rates of 54%-78% by age of women, the projected cost of screening was US$30B for ACR, US$18B for ACS and US$8B for USPSTF guidelines. The average lifetime cost to screen an average-risk woman was: US$13 416 for ACR, US$7946 for ACS and US$6931 for USPSTF. Participation rates, the proportion of women with a lifetime risk>20% and commercial MRI and 3D costs had the largest impact on total costs.

conclusionThe cost of screening varies significantly by guideline (US$8B-US$30B) and was most influenced by participation rates, high-risk population proportions and technology costs. Future work can investigate whether risk-based screening strategies being tested in ongoing clinical trials can reduce national screening costs while improving outcomes.Cite Now.

Indexed as

Breast NeoplasmsEarly Detection of CancerHealth Care CostsMammographyMass ScreeningAdultAgedCost-Benefit AnalysisFemaleHumansLife TablesMiddle AgedPractice Guidelines as TopicUnited StatesBreast tumoursHEALTH ECONOMICSMass Screening

Identifiers

PMID39961709
PMCPMC11836805

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.