Evidence map›Paper›PMID 38676390›Full record

ArticleCancer medicine2024

Ensemble-based classification using microRNA expression identifies a breast cancer patient subgroup with an ultralow long-term risk of metastases.

Ines Block, Mark Burton, Kristina P Sørensen, Martin J Larsen, Thi T N Do, Martin Bak, Søren Cold, Mads Thomassen, Qihua Tan, Torben A Kruse

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 2 institutions in 1 country.

Ines BlockDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.ORCID 0000-0003-1964-6031
Mark BurtonDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.
Kristina P SørensenDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.
Martin J LarsenDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.
Thi T N DoDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.
Martin BakDepartment of Pathology, Odense University Hospital, Odense, Denmark.
Søren ColdDepartment of Oncology, Odense University Hospital, Odense, Denmark.
Mads ThomassenDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.
Qihua TanHuman Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Torben A KruseDepartment of Clinical Genetics, Odense University Hospital, Odense, Denmark.ORCID 0000-0002-2460-6483
University of Southern Denmark · DKOdense University Hospital · DK

Funding

A. J. Andersen & Hustrus FondBreast FriendsDanish Ministry of the InteriorDansk Kræftforsknings FondDirektør Jacob Madsen & Hustru Olga Madsens FondFonden af 1870Fonden til Lægevidenskabens FremmeFree Research Fond of the Odense University HospitalFrimodt-Heineke FondenFru Ingeborg Albinus Larsens MindelegatHarboefondenInge & Jørgen Larsens MindelegatKræftens BekæmpelseLundbeck FoundationMeta & Håkon Baggers FondNatur og Univers, Det Frie Forskningsråd 09-061677/FSSNatur og Univers, Det Frie Forskningsråd 7016-00346B/FSSOverlægerådets LegatudvalgRegionernes Medicin- og behandlingspuljeThe Danish Council for Strategic Research DBCG-TIBCATUniversity of Southern Denmark DAWN2020
6 · The paper itself

Abstract

backgroundCurrent clinical markers overestimate the recurrence risk in many lymph node negative (LNN) breast cancer (BC) patients such that a majority of these low-risk patients unnecessarily receive systemic treatments. We tested if differential microRNA expression in primary tumors allows reliable identification of indolent LNN BC patients to provide an improved classification tool for overtreatment reduction in this patient group.

methodsWe collected freshly frozen primary tumors of 80 LNN BC patients with recurrence and 80 recurrence-free patients (mean follow-up: 20.9 years). The study comprises solely systemically untreated patients to exclude that administered treatments confound the metastasis status. Samples were pairwise matched for clinical-pathological characteristics to minimize dependence of current markers. Patients were classified into risk-subgroups according to the differential microRNA expression of their tumors via classification model building with cross-validation using seven classification methods and a voting scheme. The methodology was validated using available data of two independent cohorts (n = 123, n = 339).

resultsOf the 80 indolent patients (who would all likely receive systemic treatments today) our ultralow-risk classifier correctly identified 37 while keeping a sensitivity of 100% in the recurrence group. Multivariable logistic regression analysis confirmed independence of voting results from current clinical markers. Application of the method in two validation cohorts confirmed successful classification of ultralow-risk BC patients with significantly prolonged recurrence-free survival.

conclusionProfiles of differential microRNAs expression can identify LNN BC patients who could spare systemic treatments demanded by currently applied classifications. However, further validation studies are required for clinical implementation of the applied methodology.

Indexed as

Biomarkers, TumorBreast NeoplasmsMicroRNAsAdultAgedFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedNeoplasm MetastasisNeoplasm Recurrence, LocalPrognosisRisk AssessmentBiomarkers, TumorMicroRNAslow‐risk breast cancerlymph node negativemicroRNA‐based recurrence predictionovertreatment reductionsystematically untreated

Identifiers

PMID38676390
PMCPMC11053369
OpenAlexW4395699572

What Socratic 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 Socratic graph.