Evidence map›Paper›PMID 30319966›Full record

ReviewFrontiers in oncology2018

Recent Advances in Liquid Biopsy in Patients With Castration Resistant Prostate Cancer.

Vincenzo Di Nunno, Lidia Gatto, Matteo Santoni, Alessia Cimadamore, Antonio Lopez-Beltran, Liang Cheng, Marina Scarpelli, Rodolfo Montironi, Francesco Massari

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

9 authors.

Vincenzo Di NunnoDivision of Oncology, S.Orsola-Malpighi Hospital, Bologna, Italy.
Lidia GattoDivision of Oncology, S.Orsola-Malpighi Hospital, Bologna, Italy.
Matteo SantoniOncology Unit, Macerata Hospital, Macerata, Italy.
Alessia CimadamoreSection of Pathological Anatomy, School of Medicine, United Hospital, Polytechnic University of the Marche Region, Ancona, Italy.
Antonio Lopez-BeltranDepartment of Pathology and Surgery, Faculty of Medicine, Cordoba, Spain.
Liang ChengDepartment of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.
Marina ScarpelliSection of Pathological Anatomy, School of Medicine, United Hospital, Polytechnic University of the Marche Region, Ancona, Italy.
Rodolfo MontironiSection of Pathological Anatomy, School of Medicine, United Hospital, Polytechnic University of the Marche Region, Ancona, Italy.
Francesco MassariDivision of Oncology, S.Orsola-Malpighi Hospital, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Management of localized and advanced prostate cancer benefits from several therapeutic options with a surprising improvement in terms of clinical outcome. The selection of patients more likely to benefit from a specific approach still remains a key issue as well as the early identification of patients with aggressive disease which could benefit from a more aggressive treatment strategy. The lack of reliable bio-marker in castration resistant setting able to monitor response to treatment and early inform about tumor progression is an emerging issue. Accordingly, circulating DNA and circulating tumor cells appears a promising and attractive approach despite to date practical applications of these techniques are few and not validated. The aim of this review of the literature is to explore current knowledge on liquid biopsy in prostate cancer focusing on possible future applications.

Indexed as

circulating DNACTCsliquid biopsymetastatic castration resistant prostate cancerprostate cancer

Identifiers

PMID30319966
PMCPMC6165898

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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.