Evidence map›Paper›PMID 37493837›Full record

ReviewAbdominal radiology (New York)2023

PSMA PET imaging in the diagnosis and management of prostate cancer.

Sina Houshmand, Courtney Lawhn-Heath, Spencer Behr

Open access · hybridAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
11.9field-weighted citation impact, top 1% of its field
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

40 citing papers in PubMed, 46 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Sina HoushmandDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA. sina.houshmand@ucsf.edu.ORCID 0000-0002-8935-6622
Courtney Lawhn-HeathDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA.
Spencer BehrDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA.
University of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer is the second leading cause of cancer-related deaths in men in the United States. Imaging techniques such as CT, MRI, and bone scans have traditionally been used for diagnosis and staging. Molecular imaging modalities targeting the prostate-specific membrane antigen (PSMA) have recently gained attention due to their high affinity and accuracy. PSMA PET has been combined with other modalities such as multiparametric MRI for better diagnostic and prognostic performance. PSMA imaging has been studied at different clinical settings with a wide range of disease aggressiveness. In this review we will explore the role of PSMA PET in high-risk prostate cancer staging, biochemical recurrence, and castration-resistant prostate cancer. The primary focus of this review article is to examine the latest developments in the use of PSMA imaging and emphasize the clinical situations where its effectiveness has been demonstrated to significantly impact the treatment of prostate cancer. In addition, we will touch upon the potential future advancements of PSMA PET imaging and its evolving significance in the management of prostate cancer.

Indexed as

Prostate-Specific AntigenProstatic NeoplasmsCholineHumansMaleMolecular Targeted TherapyNeoplasm StagingPositron Emission Tomography Computed TomographyRecurrenceCholineProstate-Specific AntigenBiochemical recurrencePETProstate cancerPSMA

Identifiers

PMID37493837
PMCPMC10682054
OpenAlexW4385264329

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.