Evidence map›Paper›PMID 31703396›Full record

ArticleMetabolites2019

Untargeted Urinary

Catarina L Silva, Ana Olival, Rosa Perestrelo, Pedro Silva, Helena Tomás, José S Câmara

Abstract read
In one paragraph

Article in Metabolites, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
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  17. Article
  18. Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer.International journal of molecular sciences · 2021
    Review
  19. Article
  20. 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

6 authors.

Catarina L SilvaCQM-Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105 Funchal, Portugal.ORCID 0000-0002-3018-3165
Ana OlivalCQM-Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105 Funchal, Portugal.
Rosa PerestreloCQM-Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105 Funchal, Portugal.
Pedro SilvaCQM-Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105 Funchal, Portugal.ORCID 0000-0003-1487-9346
Helena TomásCQM-Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105 Funchal, Portugal.
José S CâmaraCQM-Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105 Funchal, Portugal.ORCID 0000-0003-1965-3151

Funding

ARDITI-Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação 09-5369-FSE-000001ARDITI-Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação M1420-01-0145-FEDER-000005Fundação para a Ciência e a Tecnologia PEstOE/QUI/UI0674/2019Fundação para a Ciência e a Tecnologia SFRH/BD/97039/2013Fundação para a Ciência e a Tecnologia SFRH/BPD/97387/2013Indigo Program (Era-Net) INNOINDIGO/0001/2015Madeira 14-20 M1420-01-0145-FEDER-000008
6 · The paper itself

Abstract

Breast cancer (BC) remains the second leading cause of death among women worldwide. An emerging approach based on the identification of endogenous metabolites (EMs) and the establishment of the metabolomic fingerprint of biological fluids constitutes a new frontier in medical diagnostics and a promising strategy to differentiate cancer patients from healthy individuals. In this work we aimed to establish the urinary metabolomic patterns from 40 BC patients and 38 healthy controls (CTL) using proton nuclear magnetic resonance spectroscopy (1H-NMR) as a powerful approach to identify a set of BC-specific metabolites which might be employed in the diagnosis of BC. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to a 1H-NMR processed data matrix. Metabolomic patterns distinguished BC from CTL urine samples, suggesting a unique metabolite profile for each investigated group. A total of 10 metabolites exhibited the highest contribution towards discriminating BC patients from healthy controls (variable importance in projection (VIP) >1,

Indexed as

1H NMRbreast cancerchemometric toolsmetabolomicsurine

Identifiers

PMID31703396
PMCPMC6918409

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.