Evidence map›Paper›PMID 41108673›Full record

ArticleCancer2025

Prostate-specific membrane antigen positron emission tomography/computed tomography imaging as a precision diagnostic at prostate cancer recurrence after radical prostatectomy: Modeling long-term survival.

Kemal Caglar Gogebakan, Zizi Elsisi, Felipe Montano-Campos, Lukas Owens, Yibai Zhao, Roman Gulati, Justin Ferdinandus, Wolfgang P Fendler, Jeremie Calais, Thomas A Hope and 9 more

Abstract read
In one paragraph

Article in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

19 authors.

Kemal Caglar GogebakanPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.ORCID https://orcid.org/0009-0000-8474-4039
Zizi ElsisiThe Comparative Health Outcomes, Policy, and Economics Institute, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0001-6931-4962
Felipe Montano-CamposThe Comparative Health Outcomes, Policy, and Economics Institute, University of Washington, Seattle, Washington, USA.
Lukas OwensPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.ORCID https://orcid.org/0000-0002-5149-5379
Yibai ZhaoPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.
Roman GulatiPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.ORCID https://orcid.org/0000-0002-7592-6567
Justin FerdinandusFaculty of Medicine and University Hospital of Cologne, Department I of Internal Medicine, and Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf, University of Cologne, Cologne, Germany.
Wolfgang P FendlerDepartment of Nuclear Medicine, DKTK and NCT University Hospital Essen, Essen, Germany.
Jeremie CalaisAhmanson Translational Theranostics Division, Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, USA.
Thomas A HopeDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA.
Sigrid CarlssonDepartments of Surgery and Epidemiology and Biostatistics, Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID https://orcid.org/0000-0003-3553-5710
Jonathan FainbergDepartment of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Vincent LaudoneDepartment of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Natalia KunstCentre for Health Economics, University of York, York, UK.
Alejandro BerlinRadiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
Matthew SchipperDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
Andrew BarbourDepartment of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Seattle, Washington, USA.
Amir IravaniDivision of Nuclear Medicine, Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA.
Ruth EtzioniPublic Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
TRANSCRIPTOME AND PROTEOME STRATIFICATION OF PROSTATE ADENOCARCINOMA PHENOTYPESP50CA097186 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PETER S NELSON · 2002 to 2026
$58.1M
Modeling Precision Interventions for Prostate Cancer ControlU01CA253915 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI ETZIONI, RUTH D, TSODIKOV, ALEXANDER · 2020 to 2025
$6.5M
Modeling and analytics for cancer diagnostics: traversing the data-evidence divideR35CA274442 · NCI · FRED HUTCHINSON CANCER CENTER · PI RUTH D ETZIONI · 2022 to 2026
$4.9M
Statistical modeling to support population and translational cancer researchR50CA221836 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Roman Gulati · 2017 to 2026
$2.0M
NCI NIH HHS CA097186NCI NIH HHS CA253915NCI NIH HHS P30 CA008748NCI NIH HHS P50 CA097186NCI NIH HHS R35 CA274442NCI NIH HHS R50 CA221836NCI NIH HHS R50:CA 221836NCI NIH HHS U01 CA253915
6 · The paper itself

Abstract

backgroundProstate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT) is affecting the management of patients with prostate cancer with biochemical recurrence after radical prostatectomy. The long-term outcomes of tailoring salvage treatment on the basis of PSMA-PET/CT status remain to be determined.

methodsA decision-analytic model was developed to project incremental life-years of strategies that allocate treatments at biochemical recurrence after radical prostatectomy on the basis of PSMA-PET/CT status (PSMA-metastatic vs. PSMA-nonmetastatic). Modeled treatments are local/regional (radiation) or systemic (hormone therapy and doublet therapy), administered immediately or delayed. PSMA-metastatic status was assumed to lead to treatment intensification, whereas PSMA-nonmetastatic status would lead to deintensification. To project survival, data on progression to metastasis from a clinical cohort were combined with registry data on postmetastasis survival. Because of the lack of data on long-term treatment benefits by PSMA status, survival was projected by varying the hazard ratio (HR) for disease-specific death among PSMA-metastatic versus PSMA-nonmetastatic patients under delayed or local/regional regimens (HR1) and under immediate systemic regimens (HR2).

resultsMean life-years are projected to be 15.5 under the non-PSMA-tailored strategy, and mean incremental life-years range from 0.38 to 0.81 depending on HR1 and HR2. A greater benefit is projected when PSMA-metastatic status is more adverse under salvage regimens that do not include systemic agents.

conclusionsThis decision-analytic modeling study projects that PSMA-PET/CT-guided management at biochemical recurrence after radical prostatectomy yields a modest survival benefit under the specified model inputs and assumptions regarding treatment distributions. These findings may complement emerging data on the corresponding economic costs and health-related quality of life.

Indexed as

Antigens, SurfaceGlutamate Carboxypeptidase IINeoplasm Recurrence, LocalPositron Emission Tomography Computed TomographyProstatic NeoplasmsAgedHumansMaleMiddle AgedProstatectomySalvage TherapyAntigens, SurfaceFOLH1 protein, humanGlutamate Carboxypeptidase IIbiochemical recurrencedecision‐analytic modelprostate cancerprostate‐specific membrane antigen positron emission tomography/computed tomography (PSMA‐PET/CT)

Identifiers

PMID41108673
PMCPMC12632154

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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.