Evidence map›Paper›PMID 36831466›Full record

ReviewCancers2023

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review.

Louiza S Velentzis, Victoria Freeman, Denise Campbell, Suzanne Hughes, Qingwei Luo, Julia Steinberg, Sam Egger, G Bruce Mann, Carolyn Nickson

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Louiza S VelentzisThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.
Victoria FreemanThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.ORCID 0000-0001-8033-6740
Denise CampbellThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.ORCID 0000-0002-3183-0790
Suzanne HughesThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.
Qingwei LuoThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.
Julia SteinbergThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.
Sam EggerThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.
G Bruce MannBreast Service, The Royal Women's and Royal Melbourne Hospital, Parkville, VIC 3010, Australia.
Carolyn NicksonThe Daffodil Centre, The University of Sydney, A Joint Venture with Cancer Council NSW, Sydney, NSW 2011, Australia.

Funding

Australian Government contract reference 2000004049
6 · The paper itself

Abstract

backgroundThe benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose.

methodsPopulation: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST.

resultsOf 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (

conclusionSome risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.

Indexed as

breast cancer screeningrisk assessmentrisk-based screeningrisk prediction models

Identifiers

PMID36831466
PMCPMC9953796

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.