Evidence map›Paper›PMID 42078406›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Comparative fine-mapping of breast cancer susceptibility loci using summary statistics methods and multinomial regression.

Denise G O'Mahony, Jonathan Beesley, Maria Zanti, Joe Dennis, Diptavo Dutta, Peter Kraft, Vessela Kristensen, Georgia Chenevix-Trench, Douglas F Easton, Kyriaki Michailidou

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Denise G O'MahonyDepartment of Biostatistics, the Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.ORCID 0000-0002-7212-0920
Jonathan BeesleyCancer Research Program, QIMR Berghofer, Brisbane, QLD, Australia.
Maria ZantiDepartment of Biostatistics, the Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.ORCID 0000-0002-0136-9921
Joe DennisCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK.ORCID 0000-0003-4591-1214
Diptavo DuttaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, USA.ORCID 0000-0002-6634-9040
Peter KraftDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Maryland, USA.
Vessela KristensenDepartment of Medical Genetics, Oslo University Hospital, Oslo, Norway.
Georgia Chenevix-TrenchCancer Research Program, QIMR Berghofer, Brisbane, QLD, Australia.ORCID 0000-0002-1878-2587
Douglas F EastonCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK.
Kyriaki MichailidouDepartment of Biostatistics, the Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.ORCID 0000-0001-7065-1237

Funding

Epidemiologic StudiesU19CA148065 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI AHSAN, HABIBUL, BRUGGE, JOAN SIEFERT · 2010 to 2014
$10.6M
NCI NIH HHS U19 CA148065
6 · The paper itself

Abstract

statistics fine-mapping methods offer advantages over classical methods, including avoiding data-sharing constraints and improved modelling of correlated variables and sparse effects. However, its performance has not been comprehensively evaluated in breast cancer using real-world data. Previous multinomial stepwise regression (MNR) fine-mapping analyses for breast cancer identified 196 credible sets. Here, we apply summary statistics fine-mapping, compare methods, and assess parameters influencing performance. Using summary statistics from the Breast Cancer Association Consortium, we compared

Identifiers

PMID42078406
PMCPMC13131697

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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.