Evidence map›Paper›PMID 33556275›Full record

ArticleAnnals of internal medicine2021

Incorporating Baseline Breast Density When Screening Women at Average Risk for Breast Cancer : A Cost-Effectiveness Analysis.

Ya-Chen Tina Shih, Wenli Dong, Ying Xu, Ruth Etzioni, Yu Shen

Erratum issuedOpen access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Artificial Intelligence in Breast X-Ray Imaging.Seminars in ultrasound, CT, and MR · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Ya-Chen Tina ShihThe University of Texas MD Anderson Cancer Center, Houston, Texas (Y.T.S., W.D., Y.X., Y.S.).
Wenli DongThe University of Texas MD Anderson Cancer Center, Houston, Texas (Y.T.S., W.D., Y.X., Y.S.).
Ying XuThe University of Texas MD Anderson Cancer Center, Houston, Texas (Y.T.S., W.D., Y.X., Y.S.).ORCID 0000-0002-9454-4337
Ruth EtzioniFred Hutchinson Cancer Center, Seattle, Washington (R.E.).
Yu ShenThe University of Texas MD Anderson Cancer Center, Houston, Texas (Y.T.S., W.D., Y.X., Y.S.).ORCID 0000-0002-3899-7868
The University of Texas MD Anderson Cancer Center · USFred Hutch Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Estimating the Cost Trajectories and Projecting the Cost of Cancer Care in the United States: Methodology and ApplicationR01CA225646 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LI, LIANG, SHIH, YA-CHEN TINA · 2018 to 2022
$1.8M
Technology Diffusion in Cancer: Geographic Variations, Facilitators, Outcomes, and CostsR01CA207216 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SHIH, YA-CHEN TINA · 2016 to 2020
$1.6M
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA207216NCI NIH HHS R01 CA225646
6 · The paper itself

Abstract

backgroundBreast density classification is largely determined by mammography, making the timing of the first screening mammogram clinically important.

objectiveTo evaluate the cost-effectiveness of breast cancer screening strategies that are stratified by breast density.

designMicrosimulation model to generate the natural history of breast cancer for women with and those without dense breasts and assessment of the cost-effectiveness of strategies tailored to breast density and nontailored strategies. DATA SOURCES: Model parameters from the literature; statistical modeling; and analysis of Surveillance, Epidemiology, and End Results-Medicare data. TARGET POPULATION: Women aged 40 years or older. TIME HORIZON: Lifetime. PERSPECTIVE: Societal.

interventionNo screening; biennial or triennial mammography from age 50 to 75 years; annual mammography from age 50 to 75 years for women with dense breasts at age 50 years and biennial or triennial mammography from age 50 to 75 years for those without dense breasts at age 50 years; and annual mammography at age 40 to 75 years for women with dense breasts at age 40 years and biennial or triennial mammography at age 50 to 75 years for those without dense breasts at age 40 years. OUTCOME MEASURES: Lifetime costs and quality-adjusted life-years (QALYs), discounted at 3% annually. RESULTS OF BASE-CASE ANALYSIS: Baseline screening at age 40 years followed by annual screening at age 40 to 75 years for women with dense breasts and biennial screening at age 50 to 75 years for women without dense breasts was effective and cost-effective, yielding an incremental cost-effectiveness ratio of $36 200 per QALY versus the biennial strategy at age 50 to 75 years. RESULTS OF SENSITIVITY ANALYSIS: At a societal willingness-to-pay threshold of $100 000 per QALY, the probability that the density-stratified strategy at age 40 years was optimal was 56% compared with 6 other strategies. LIMITATION: Findings may not be generalizable outside the United States.

conclusionThe study findings advocate for breast density-stratified screening with baseline mammography at age 40 years. PRIMARY FUNDING SOURCE: National Cancer Institute.

Indexed as

Breast DensityCost-Benefit AnalysisQuality-Adjusted Life YearsAdultAgedBreast NeoplasmsEarly Detection of CancerFemaleHumansMammographyMass ScreeningMiddle AgedSEER ProgramUnited States

Identifiers

PMID33556275
PMCPMC8171124
OpenAlexW3126194048

What OpenQuestion holds

Textmetadata
LicenceTDM
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.