Evidence map›Paper›PMID 34708579›Full record

ArticleCancer medicine2021

Breast cancer risk stratification for mammographic screening: A nation-wide screening cohort of 24,431 women in Singapore.

Peh Joo Ho, Fuh Yong Wong, Wen Yee Chay, Elaine Hsuen Lim, Zi Lin Lim, Kee Seng Chia, Mikael Hartman, Jingmei Li

Abstract read
In one paragraph

Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

8 authors.

Peh Joo HoGenome Institute of Singapore, Singapore, Singapore.ORCID 0000-0002-3017-4023
Fuh Yong WongDivision of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore.
Wen Yee ChayDivision of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore.
Elaine Hsuen LimDivision of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore.
Zi Lin LimGenome Institute of Singapore, Singapore, Singapore.
Kee Seng ChiaSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Mikael HartmanSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Jingmei LiGenome Institute of Singapore, Singapore, Singapore.ORCID 0000-0001-8587-7511

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer incidence is increasing in Asia. However, few women in Singapore attend routine mammography screening. We aim to identify women at high risk of breast cancer who will benefit most from regular screening using the Gail model and information from their first screen (recall status and mammographic density).

methodsIn 24,431 Asian women (50-69 years) who attended screening between 1994 and 1997, 117 developed breast cancer within 5 years of screening. Cox proportional hazard models were used to study the associations between risk classifiers (Gail model 5-year absolute risk, recall status, mammographic density), and breast cancer occurrence. The efficacy of risk stratification was evaluated by considering sensitivity, specificity, and the proportion of cancers identified.

resultsAdjusting for information from first screen attenuated the hazard ratios (HR) associated with 5-year absolute risk (continuous, unadjusted HR [95% confidence interval]: 2.3 [1.8-3.1], adjusted HR: 1.9 [1.4-2.6]), but improved the discriminatory ability of the model (unadjusted AUC: 0.615 [0.559-0.670], adjusted AUC: 0.703 [0.653-0.753]). The sensitivity and specificity of the adjusted model were 0.709 and 0.622, respectively. Thirty-eight percent of all breast cancers were detected in 12% of the study population considered high risk (top five percentile of the Gail model 5-year absolute risk [absolute risk ≥1.43%], were recalled, and/or mammographic density ≥50%).

conclusionThe Gail model is able to stratify women based on their individual breast cancer risk in this population. Including information from the first screen can improve prediction in the 5 years after screening. Risk stratification has the potential to pick up more cancers.

Indexed as

AgedBreast NeoplasmsCohort StudiesEarly Detection of CancerFemaleHumansMammographyMiddle AgedRisk AssessmentSingaporebreast cancerGail modelmammogram recall statusmammographic densitymammography screening

Identifiers

PMID34708579
PMCPMC8607242

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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.