Evidence map›Paper›PMID 38539457›Full record

ReviewCancers2024

The Role of PSMA PET Imaging in the Classification of the Risk of Prostate Cancer Patients: A Systematic Review on the Insights to Guide an Active Surveillance Approach.

Francesco Dondi, Alessandro Antonelli, Nazareno Suardi, Giorgio Treglia, Francesco Bertagna

Abstract readReview
In one paragraph

Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
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  5. Review
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.

Francesco DondiNuclear Medicine, ASST Spedali Civili di Brescia and Università degli Studi di Brescia, 25123 Brescia, Italy.ORCID 0000-0003-4839-9033
Alessandro AntonelliDepartment of Urology, Azienda Ospedaliera Universitaria Integrata Verona, University of Verona, 37134 Verona, Italy.
Nazareno SuardiDepartment of Urology, Spedali Civili di Brescia, 25123 Brescia, Italy.
Giorgio TregliaNuclear Medicine, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland.ORCID 0000-0001-9808-780X
Francesco BertagnaNuclear Medicine, ASST Spedali Civili di Brescia and Università degli Studi di Brescia, 25123 Brescia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundactive surveillance (AS) is a suitable strategy for patients with prostate cancer (PCa). Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) imaging is an established tool used to assess PCa. The aim of this review was to evaluate the role of PSMA imaging to guide correct risk-based classification and the AS approach in PCa patients.

methodsThe Scopus, Embase, Web of Science, Cochrane Library, and PubMed/MEDLINE databases were screened to find relevant published articles.

results1774 articles were revealed with the literature search. A total of 1764 articles were excluded after applying exclusion criteria (data not within the field of interest, preclinical papers, conference proceedings, reviews, or editorials). Ten studies were finally included in the review, revealing that PSMA PET could have the ability to guide risk-based classification of PCa and the choice of AS, and to guide the execution of biopsies for the research of high-grade PCa, therefore precluding AS.

conclusionthis systematic review underlined a possible role of PSMA PET imaging in patients with PCa by correctly re-classifying them on the basis of their risk and guiding AS.

Indexed as

active surveillancenuclear medicinePETpositron emission tomographyprostate cancerprostate-specific membrane antigenPSMA

Identifiers

PMID38539457
PMCPMC10969558

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.