Evidence map›Paper›PMID 37101769›Full record

ArticleEuropean urology open science2023

A Systematic Review of the Variability in Performing and Reporting Intraprostatic Prostate-specific Membrane Antigen Positron Emission Tomography in Primary Staging Studies.

Gideon Ptasznik, Daniel Moon, James Buteau, Brian D Kelly, Sean Ong, Declan G Murphy, Mark Page, Nathan Papa

Abstract read
In one paragraph

Article in European urology open science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Automated lesion tracking and treatment response classification on [European journal of nuclear medicine and molecular imaging · 2026
    Article
  2. LLM-powered prostate cancer staging from PSMA-PET/CT reports using PROMISE v2.European journal of nuclear medicine and molecular imaging · 2026
    Article
  3. Article
  4. 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

8 authors.

Gideon PtasznikDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Daniel MoonSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
James ButeauProstate Cancer Theranostics and Imaging Centre of Excellence (ProsTIC) and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Brian D KellyDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Sean OngUniversity of Melbourne, Royal Melbourne Hospital Clinical School, Melbourne, VIC, Australia.
Declan G MurphyDivision of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Mark PageSt Vincent's Hospital, Melbourne, VIC, Australia.
Nathan PapaSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Context: Prostate cancer (PCa) remains one of the leading causes of cancer-related deaths in men worldwide. Men at risk are typically offered multiparametric magnetic resonance imaging and, if suspicious, a targeted biopsy. However, false-negative rates of magnetic resonance imaging are consistently 18%; therefore, there is growing interest in improving the diagnostic performance of imaging through novel technologies. Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) is being utilised for PCa staging and, more recently, for intraprostatic tumour localisation. However, significant variability has been observed in how PSMA PET is performed and reported. Objective: In this review, we aim to evaluate how pervasive this variability is in trials investigating the performance of PSMA PET in primary PCa workup. Evidence acquisition: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, we performed an optimal search in five different databases. After removing duplicates, 65 studies were included in our review. Evidence synthesis: Studies dated back as early as 2016, with numerous different source countries. There was variation in the reference standard for PSMA PET, with some using biopsy specimens or surgical specimens, and in some cases, a combination of the two. Similar inconsistencies were noted when studies selected histological definitions of clinically significant PCa, while some omitted their definition altogether. The most significant variations in performing PSMA PET were the radiotracer type, dose, acquisition time after injection, and the PET camera being utilised. Substantial variation in the reporting of PSMA PET was noted, with no consistency in defining what constitutes a positive intraprostatic lesion. Across 65 studies, four different definitions were used. Conclusions: This systematic review has highlighted considerable variation in obtaining and performing a PSMA PET study in the context of primary PCa diagnosis. Given the discrepancy in how PSMA PET was performed and reported, it questions the homogony of studies from centre to centre. Standardisation of PSMA PET is required for this to become a consistently useful and reproducible modality in the diagnosis of PCa. Patient summary: Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) is being utilised for staging and localisation of prostate cancer (PCa); however, there is significant variability in performing and reporting PSMA PET. Standardisation of PSMA PET is required for results to be consistently useful and reproducible for the diagnosis of PCa.

Indexed as

Novel imagingPrimary localisationPrimary prostate cancerProstate-specific membrane antigen positron emission tomography

Identifiers

PMID37101769
PMCPMC10123424

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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.