Evidence map›Paper›PMID 38473301›Full record

ReviewCancers2024

The Current Landscape of Prostate-Specific Membrane Antigen (PSMA) Imaging Biomarkers for Aggressive Prostate Cancer.

Haidar Al Saffar, David C Chen, Carlos Delgado, Jacob Ingvar, Michael S Hofman, Nathan Lawrentschuk, Marlon Perera, Declan G Murphy, Renu Eapen

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Size and SUVThe Prostate · 2025
    Article
  8. Review
  9. Review
  10. Article
  11. 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

9 authors.

Haidar Al SaffarDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.
David C ChenDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.ORCID 0000-0002-7675-7208
Carlos DelgadoSchool of Medicine and Health Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico.ORCID 0000-0003-0400-2647
Jacob IngvarDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.
Michael S HofmanProstate Cancer Theranostics and Imaging Centre of Excellence, Molecular Imaging and Therapeutic Nuclear Medicine, Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.
Nathan LawrentschukDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.ORCID 0000-0001-8553-5618
Marlon PereraDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.
Declan G MurphyDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.
Renu EapenDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC 3052, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The review examines the vital role of prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) in the diagnosis, staging, and treatment of prostate cancer (PCa). It focuses on the superior diagnostic abilities of PSMA PET/CT for identifying both nodal and distant PCa, and its potential as a prognostic indicator for biochemical recurrence and overall survival. Additionally, we focused on the variability of PSMA's expression and its impact on personalised treatment, particularly the use of [

Indexed as

aggressive prostate cancerbiochemical recurrenceprostate-specific membrane antigenPSMA PET/CTuro-oncology

Identifiers

PMID38473301
PMCPMC10931387

What OpenQuestion holds

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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.