Evidence map›Paper›PMID 21597921›Full record

ArticleBreast cancer research and treatment2011

Biologic markers determine both the risk and the timing of recurrence in breast cancer.

Laura J Esserman, Dan H Moore, Pamela J Tsing, Philip W Chu, Christina Yau, Elissa Ozanne, Robert E Chung, Vickram J Tandon, John W Park, Frederick L Baehner and 4 more

Abstract read
In one paragraph

Article in Breast cancer research and treatment, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

  1. A combination of hydroxytyrosol, omega-3 fatty acids and curcumin improves pain and inflammation among early stage breast cancer patients receiving adjuvant hormonal therapy: results of a pilot study.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2019
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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

14 authors.

Laura J EssermanDepartment of Surgery and Radiology, University of California, San Francisco, CA 94115, USA. laura.esserman@ucsfmedctr.org
Dan H Moore
Pamela J Tsing
Philip W Chu
Christina Yau
Elissa Ozanne
Robert E Chung
Vickram J Tandon
John W Park
Frederick L Baehner
Stig Kreps
Andrew N J Tutt
Cheryl E Gillett
Christopher C Benz

Funding

Integrated Biomarkers to Characterize Breast Cancer RiskU01CA111234 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ESSERMAN, LAURA J · 2004 to 2009
$4.4M
NCI NIH HHS 5 UO1 CA111234NCI NIH HHS U01 CA111234
6 · The paper itself

Abstract

Breast cancer has a long natural history. Established and emerging biologic markers address overall risk but not necessarily timing of recurrence. 346 adjuvant naïve breast cancer cases from Guy's Hospital with 23 years minimum follow-up and archival blocks were recut and reassessed for hormone-receptors (HR), HER2-receptor and grade. Disease-specific survival (DSS) was analyzed by recursive partitioning. To validate insights from this analysis, gene-signatures (proliferative and HR-negative) were evaluated for their ability to predict early versus late metastatic risk in 683 node-negative, adjuvant naïve breast cancers annotated with expression microarray data. Risk partitioning showed that adjuvant naïve node-negative outcome risk was primarily partitioned by tumor receptor status and grade but not tumor size. HR-positive and HER2-negative (HRpos) risk was partitioned by tumor grade; low grade cases have very low early risk but a 20% fall-off in DSS 10 or more years after diagnosis. Higher grade HRpos cases have risk over >20 years. Triple-negative (Tneg) and HER2-positive (HER2pos) cases DSS events occurred primarily within the first 5 years. Among node-positive cases, only low grade conferred late risk, suggesting that proliferative gene signatures that identify proliferation would be important for predicting early but not late recurrence. Using pooled data from four publicly available data sets for node-negative tumors annotated with gene expression and outcome data, we evaluated four prognostic gene signatures: two proliferation-based and two immune function-based. Tumor proliferative capacity predicted early but not late metastatic risk for HRpos cases. The immune function or HRneg specific signatures predicted only early metastatic risk in Tneg and HER2pos cases. Breast cancer prognostic signatures need to inform both risk and timing of metastatic events and may best be applied within subsets. Current signatures predict for outcome risk within 5 years of diagnosis. Predictors of late risk for HR positive disease are needed.

Indexed as

Neoplasm Recurrence, LocalAdultAgedBiomarkers, TumorBreast NeoplasmsCell ProliferationDisease-Free SurvivalErb-b2 Receptor Tyrosine KinasesFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunohistochemistryKaplan-Meier EstimateLondonMiddle AgedBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, Progesterone

Identifiers

PMID21597921
PMCPMC4324750

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Registered trials

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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.