Evidence map›Paper›PMID 41815510›Full record

ArticleJU open plus2024

Flourine-18 Prostate-Specific Membrane Antigen-1007 Positron Emission Tomography Imaging in Staging of Primary and Secondary Prostate Cancer-A Retrospective Observational Cohort Study.

Matthew H V Byrne, Nithesh Ranasinha, Abhishek Sharma, Claudia Mercader, Mutie Raslan, Ganesh Sathanapally, Francesca Lewis, Stefanos Gorgoraptis, Ana Catarina Lopes Vieira, Jedrzej Golebka and 15 more

Abstract read
In one paragraph

Article in JU open plus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

25 authors.

Matthew H V ByrneOxford University Hospitals NHS Foundation Trust, United Kingdom.ORCID https://orcid.org/0000-0002-2414-352X
Nithesh RanasinhaOxford University Hospitals NHS Foundation Trust, United Kingdom.
Abhishek SharmaOxford University Hospitals NHS Foundation Trust, United Kingdom.
Claudia MercaderOxford University Hospitals NHS Foundation Trust, United Kingdom.
Mutie RaslanOxford University Hospitals NHS Foundation Trust, United Kingdom.
Ganesh SathanapallyOxford University Hospitals NHS Foundation Trust, United Kingdom.
Francesca LewisOxford University Hospitals NHS Foundation Trust, United Kingdom.
Stefanos GorgoraptisOxford University Hospitals NHS Foundation Trust, United Kingdom.
Ana Catarina Lopes VieiraOxford University Hospitals NHS Foundation Trust, United Kingdom.
Jedrzej GolebkaOxford University Hospitals NHS Foundation Trust, United Kingdom.
Bryony PeirisOxford University Hospitals NHS Foundation Trust, United Kingdom.
J Francisco LopezOxford University Hospitals NHS Foundation Trust, United Kingdom.
Tom LeslieOxford University Hospitals NHS Foundation Trust, United Kingdom.ORCID https://orcid.org/0000-0002-4155-1840
Richard C BellOxford University Hospitals NHS Foundation Trust, United Kingdom.
Saiful MiahOxford University Hospitals NHS Foundation Trust, United Kingdom.
Mark TuthillOxford University Hospitals NHS Foundation Trust, United Kingdom.
Andrew ProtheroeOxford University Hospitals NHS Foundation Trust, United Kingdom.ORCID https://orcid.org/0000-0001-9413-0575
Philip CamilleriOxford University Hospitals NHS Foundation Trust, United Kingdom.ORCID https://orcid.org/0000-0002-2677-5627
Ami SabharwalOxford University Hospitals NHS Foundation Trust, United Kingdom.ORCID https://orcid.org/0009-0009-7485-4694
Gerard AndradeOxford University Hospitals NHS Foundation Trust, United Kingdom.
Freddie C HamdyOxford University Hospitals NHS Foundation Trust, United Kingdom.
Ruth MacphersonOxford University Hospitals NHS Foundation Trust, United Kingdom.
Fergus GleesonOxford University Hospitals NHS Foundation Trust, United Kingdom.
Richard J BryantOxford University Hospitals NHS Foundation Trust, United Kingdom.
Alastair D LambOxford University Hospitals NHS Foundation Trust, United Kingdom.ORCID https://orcid.org/0000-0002-2968-7155

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Detection of metastatic disease is important to inform prostate cancer management. Objectives: Evaluate local and distant staging by initial Design Setting and Participants: We retrospectively identified a consecutive series of Results: We identified 1335 PSMA-PET scans, from 1220 men. Across 623 initial scans for primary staging, we observed PSMA-PET avidity in 97.6% cases positive for local disease, 29.5% for nodal disease, and 26.5% for metastatic disease. PSMA-PET identified a 13.2% absolute increase in nodal lesions compared with MRI and a 24.0% absolute increase in metastatic lesions compared with MRI marrow. The sensitivity for detection of local disease among 79 patients who had radical prostatectomy was 96.2% for PSMA-PET vs 89.4% for multiparametric MRI. Across 612 scans for secondary staging, we observed PSMA-PET positive avidity in 51.2% of cases for local recurrence, 46.6% for nodal disease, and 43.0% for metastatic disease. When evaluated by the PSA range for patients receiving secondary staging, using the PSA values of 0.2 to 0.49, 0.5 to 0.99, 1 to 1.99, and ≥ 2 ng/mL, PSMA-PET scans were positive in 57.8%, 75.0%, 83.8%, and 95.5% of cases, respectively. PSMA-PET identified a 26.2% absolute increase in metastatic lesions compared with MRI marrow or other skeletal MRI (n = 61) and a 14.7% absolute increase in metastatic lesions compared with the bone scan (n = 42). Conclusion:

Indexed as

fluorine-18prostate cancerPSMA-PETstaging

Identifiers

PMID41815510
PMCPMC7618851

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.