Evidence map›Paper›PMID 36936188›Full record

ArticleNew genetics and society2022

"It's personalized, but it's still bucket based": The promise of personalized medicine vs. the reality of genomic risk stratification in a breast cancer screening trial.

Jennifer Elyse James, Galen Joseph

Open access · goldAbstract read
In one paragraph

Article in New genetics and society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Jennifer Elyse JamesInstitute for Health and Aging, University of California, San Francisco.
Galen JosephDepartment of Humanities and Social Sciences, University of California, San Francisco.
University of California, San Francisco · US

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
Precision Genomics in the WISDOM Pragmatic Clinical Trial: An "Embedded" ELSI Study of Risk-based Breast Cancer ScreeningR01CA211999 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOSEPH, GALEN · 2017 to 2021
$3.5M
NCI NIH HHS P30 CA016086NCI NIH HHS R01 CA211999
6 · The paper itself

Abstract

Adaptive pragmatic clinical trials offer an innovative approach that integrates clinical care and research. Yet, blurring the boundaries between research and clinical care raises questions about how clinicians and investigators balance their caregiving and research roles and what types of knowledge and risk assessment are most valued. This paper presents findings from an ethnographic ELSI (Ethical, Legal, Social Implications) study of an innovative clinical trial of risk-based breast cancer screening that utilizes genomics to stratify risk and recommend a breast cancer screening commensurate with the assessed risk. We argue that the trial demonstrates a fundamental tension between the promissory ideals of personalized medicine, and the reality of implementing risk stratified care on a population scale. We examine the development of a Screening Assignment Review Board in response to this tension which allows clinician-investigators to negotiate, but never fully resolve, the inherent contradiction of 'precision population screening'.

Indexed as

breast cancer screeningembedded ELSIethnographygenomicspersonalized medicinepragmatic adaptive trial designrisk-based screeningrisk-stratification

Identifiers

PMID36936188
PMCPMC10021681
OpenAlexW4294311582

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.