Evidence map›Paper›PMID 30787204›Full record

ArticleAging2019

Towards a more precise and individualized assessment of breast cancer risk.

Marie E Wood, Nicholas H Farina, Thomas P Ahern, Melissa E Cuke, Janet L Stein, Gary S Stein, Jane B Lian

Abstract read
In one paragraph

Article in Aging, 2019. 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. Lifestyle, Behavioral, and Dietary Risk Factors in Relation to Mammographic Breast Density in Women at High Risk for Breast Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
    Article
  2. Review
  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

7 authors.

Marie E WoodUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.
Nicholas H FarinaUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.
Thomas P AhernUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.
Melissa E CukeUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.
Janet L SteinUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.
Gary S SteinUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.
Jane B LianUniversity of Vermont Cancer Center, The Robert Larner MD College of Medicine, University of Vermont, Burlington, VT 05405, USA.

Funding

Understanding Factors Influencing COVID-19 Testing and Vaccination in Immigrant Low-income and Homeless Populations and Testing Targeted InterventionsU54GM115516 · NIGMS · MAINEHEALTH · PI Kimberly Luebbers · 2017 to 2026
$51.6M
Vermont Center on Behavior and HealthP20GM103644 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SIGMON, STACEY C · 2013 to 2022
$21.3M
SUBNUCLEAR TARGETING OF TRANSCRIPTION FACTORSP01CA082834 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI STEIN, GARY S. · 2001 to 2015
$18.4M
Vermont Breast Cancer Molecular Characterization LaboratoryU01CA196383 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L, STEIN, JANET L · 2015 to 2020
$5.4M
NCI NIH HHS P01 CA082834NCI NIH HHS U01 CA196383NIGMS NIH HHS P20 GM103644NIGMS NIH HHS U54 GM115516
6 · The paper itself

Abstract

Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Research Perspective, we highlight commonly used clinical risk assessment models and recent scientific advances to individualize risk assessment using precision biomarkers. Genome-wide association studies have identified >100 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, and polygenic risk scores (PRS) have been developed by several groups using this information. The ability of a PRS to improve risk assessment is promising; however, validation in both genetically and ethnically diverse populations is needed. Additionally, novel classes of biomarkers, such as microRNAs, may capture clinically relevant information based on epigenetic regulation of gene expression. Our group has recently identified a circulating-microRNA signature predictive of long-term breast cancer in a prospective cohort of high-risk women. While progress has been made, the importance of accurate risk assessment cannot be understated. Precision risk assessment will identify those women at greatest risk of developing breast cancer, thus avoiding overtreatment of women at average risk and identifying the most appropriate candidates for chemoprevention or surgical prevention.

Indexed as

Genetic Predisposition to DiseaseBiomarkers, TumorBreast NeoplasmsFemaleHumansMicroRNAsPolymorphism, Single NucleotideRisk FactorsBiomarkers, TumorMicroRNAsbiomarkersbreast cancer riskcirculating miRNAprecision risk assessment

Identifiers

PMID30787204
PMCPMC6402518

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.