Do We Still Need Randomized Controlled Trials to Support Use of New Methods of Breast Cancer Screening?

Randomized controlled trials (RCTs) have confirmed the mortality benefits of screening mammography and are the gold standard for evaluating new diagnostic tests and medical interventions. Reliable and rigorous execution of RCTs can be complex and require high levels of funding and prolonged time from technology implementation to trial completion. Breast radiology and artificial intelligence technologies are being developed and are receiving regulatory approval faster than RCTs may be effectively conducted. Regulatory approval can lead to societal recommendations, legislation, clinical availability, purchasing, and patient care, even in the absence of reliable evidence indicating increased efficacy. Marketing and patient demand and physician perceptions influence technology use. There is a wide chasm between using data provided by RCTs and site-specific care decisions. Can we find a middle ground? What types of data can influence guidelines in the absence of rigorous clinical trials? This article explores the benefits and drawbacks of RCTs and describes professional initiatives, such as widespread use of method of detection, that could allow the breast imaging community to more quickly evaluate and integrate new technologies in a reasoned and evidence-based fashion.

Authors

Institutions

Publication Details

Journal
Journal of Breast Imaging
Published
2025-11-01
DOI
https://doi.org/10.1093/jbi/wbaf058
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Do We Still Need Randomized Controlled Trials to Support Use of New Methods of Breast Cancer Screening?

Peter R. Eby, Elizabeth S. McDonald, Jon A. Steingrimsson, Etta D. Pisano
Journal of Breast Imaging
Global Cancer Incidence and Screening
article

Do We Still Need Randomized Controlled Trials to Support Use of New Methods of Breast Cancer Screening?

Peter R. Eby, Elizabeth S. McDonald, Jon A. Steingrimsson, Etta D. Pisano
article en

Abstract

Randomized controlled trials (RCTs) have confirmed the mortality benefits of screening mammography and are the gold standard for evaluating new diagnostic tests and medical interventions. Reliable and rigorous execution of RCTs can be complex and require high levels of funding and prolonged time from technology implementation to trial completion. Breast radiology and artificial intelligence technologies are being developed and are receiving regulatory approval faster than RCTs may be effectively conducted. Regulatory approval can lead to societal recommendations, legislation, clinical availability, purchasing, and patient care, even in the absence of reliable evidence indicating increased efficacy. Marketing and patient demand and physician perceptions influence technology use. There is a wide chasm between using data provided by RCTs and site-specific care decisions. Can we find a middle ground? What types of data can influence guidelines in the absence of rigorous clinical trials? This article explores the benefits and drawbacks of RCTs and describes professional initiatives, such as widespread use of method of detection, that could allow the breast imaging community to more quickly evaluate and integrate new technologies in a reasoned and evidence-based fashion.

Journal of Breast ImagingVol. 7(6)
American College of Radiology (US), Biostatistical Consulting (United States) (US), University of Pennsylvania (US)
Openalex Percentile: Top 53%
Global Cancer Incidence and Screening
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.