Evidence map›Paper›PMID 23774836›Full record

ReviewInternational journal of molecular sciences2013

The present and future of prostate cancer urine biomarkers.

Marina Rigau, Mireia Olivan, Marta Garcia, Tamara Sequeiros, Melania Montes, Eva Colás, Marta Llauradó, Jacques Planas, Inés de Torres, Juan Morote and 4 more

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
–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

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
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  3. Article
  4. CAP superfamily proteins in human: a new target for cancer therapy.Medical oncology (Northwood, London, England) · 2024
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  13. Review
  14. Article
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  16. Review
  17. Fibromodulin Gene Variants (Disease markers · 2022
    Article
  18. 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

14 authors.

Marina RigauResearch Unit in Biomedicine and Translational Oncology, Vall d'Hebron Research Institute and Hospital and Autonomous University of Barcelona, 08035 Barcelona, Spain. andreas.doll@vhir.org.
Mireia Olivan
Marta Garcia
Tamara Sequeiros
Melania Montes
Eva Colás
Marta Llauradó
Jacques Planas
Inés de Torres
Juan Morote
Colin Cooper
Jaume Reventós
Jeremy Clark
Andreas Doll

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to successfully cure patients with prostate cancer (PCa), it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput "omic" techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field.

Indexed as

AnimalsBiomarkers, TumorDNA, NeoplasmExosomesHumansMaleMetabolomeMicroRNAsProstatic NeoplasmsBiomarkers, TumorDNA, NeoplasmMicroRNAs

Identifiers

PMID23774836
PMCPMC3709804

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.