Evidence map›Paper›PMID 37702749›Full record

ReviewUrologie (Heidelberg, Germany)2023

[Opportunities for prostate-specific membrane antigen hybrid imaging in prostate cancer].

Anna-Sophie Strauß, Christian Bolenz, Ambros J Beer, Friedemann Zengerling, Meinrad Beer, Jonathan Miksch

Erratum issuedAbstract readEnglish AbstractReview
PubMed Publisher
In one paragraph

Review in Urologie (Heidelberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

6 authors.

Anna-Sophie StraußKlinik für Urologie und Kinderurologie, Universitätsklinikum Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Deutschland. anna-sophie.strauss@uniklinik-ulm.de.
Christian BolenzKlinik für Urologie und Kinderurologie, Universitätsklinikum Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Deutschland.
Ambros J BeerKlinik für Nuklearmedizin, Universitätsklinikum Ulm, Ulm, Deutschland.
Friedemann ZengerlingKlinik für Urologie und Kinderurologie, Universitätsklinikum Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Deutschland.
Meinrad BeerKlinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Ulm, Ulm, Deutschland.
Jonathan MikschKlinik für Nuklearmedizin, Universitätsklinikum Ulm, Ulm, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate-specific membrane antigen (PSMA) hybrid imaging is a promising new technique gaining importance in the field of prostate cancer (PCa) diagnosis and treatment planning. By combining PSMA radioligands and computed tomography (CT) or magnetic resonance imaging (MRI), PSMA hybrid imaging opens up new diagnostic opportunities. PSMA-PET/CT (PET: positron-emission tomography) is already well established in high-risk PCa for primary staging and tumor localization when biochemical recurrence occurs. Further potential indications for PSMA-PET/CT include tumor detection in the initial work-up before a rebiopsy with improved accuracy, the identification of target structures for precise local treatment in recurrent PCa (salvage radiotherapy or radio-guided surgery) as well as a prediction of response to PSMA radioligand therapy. This narrative review is based on a recent literature search and aims to highlight the opportunities of PSMA imaging in different disease stages of PCa.

Indexed as

ProstateProstatic NeoplasmsHumansMalePositron-Emission TomographyPositron Emission Tomography Computed TomographyProstate-Specific AntigenProstate-Specific AntigenNeoplasm stagingNuclear medicinePET/CTRadioligandsTargeted therapy

Identifiers

What OpenQuestion holds

Textmetadata
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.