Evidence map›Paper›PMID 32434554›Full record

ArticleBMC research notes2020

Predicting breast cancer metastasis from whole-blood transcriptomic measurements.

Einar Holsbø, Vittorio Perduca, Lars Ailo Bongo, Eiliv Lund, Etienne Birmelé

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC research notes, 2020. 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
–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

2 citing papers in PubMed.

  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

5 authors.

Einar HolsbøDepartment of Computer Science, UiT - The Arctic University of Norway, Tromsø, Norway. einar.j.holsbo@uit.no.ORCID http://orcid.org/0000-0002-9728-2088
Vittorio PerducaLaboratoire MAP5 (UMR CNRS 8145), Université Paris Descartes, Université de Paris, Paris, France.
Lars Ailo BongoDepartment of Computer Science, UiT - The Arctic University of Norway, Tromsø, Norway.
Eiliv LundCancer Registry of Norway, Oslo, Norway.
Etienne BirmeléLaboratoire MAP5 (UMR CNRS 8145), Université Paris Descartes, Université de Paris, Paris, France.

Funding

European Research Council ERC-AdG 232997 TICE
6 · The paper itself

Abstract

objectiveIn this exploratory work we investigate whether blood gene expression measurements predict breast cancer metastasis. Early detection of increased metastatic risk could potentially be life-saving. Our data comes from the Norwegian Women and Cancer epidemiological cohort study. The women who contributed to these data provided a blood sample up to a year before receiving a breast cancer diagnosis. We estimate a penalized maximum likelihood logistic regression. We evaluate this in terms of calibration, concordance probability, and stability, all of which we estimate by the bootstrap.

resultsWe identify a set of 108 candidate predictor genes that exhibit a fold change in average metastasized observation where there is none for the average non-metastasized observation.

Indexed as

Gene Expression ProfilingBreast NeoplasmsCase-Control StudiesFemaleHumansMiddle AgedNeoplasm MetastasisNorwayPrognosisBreast cancerEpidemiologyMetastasisPredictive modelsTranscriptomics

Identifiers

PMID32434554
PMCPMC7238609

What OpenQuestion holds

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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.