Evidence map›Paper›PMID 41212260›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Dual-tracer PET/CT identifies an aggressive PSMA-negative/FDG-positive phenotype predicting early failure of radical prostatectomy in treatment-naive prostate cancer.

Ruohua Chen, Yining Wang, Qiaochu Chen, Liang Dong, Gang Huang, Jianjun Liu

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Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

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4 · The record

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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

6 authors.

Ruohua Chen *Department of Nuclear Medicine, Jiading District Central Hospital Affiliated Shanghai University of Medicine &Health Sciences, Shanghai, 201800, China.
Yining Wang *Department of Nuclear Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Qiaochu ChenDepartment of Nuclear Medicine, Jiading District Central Hospital Affiliated Shanghai University of Medicine &Health Sciences, Shanghai, 201800, China.
Liang DongDepartment of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Gang HuangDepartment of Nuclear Medicine, Jiading District Central Hospital Affiliated Shanghai University of Medicine &Health Sciences, Shanghai, 201800, China. huang2802@163.com.ORCID 0000-0003-1939-3978
Jianjun LiuDepartment of Nuclear Medicine, Jiading District Central Hospital Affiliated Shanghai University of Medicine &Health Sciences, Shanghai, 201800, China. nuclearj@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeThe metabolic phenotype of negative prostate-specific membrane antigen (PSMA) and positive [

methodsThis retrospective cohort study included 104 treatment-naive prostate cancer patients who underwent both [

resultsOf the 104 patients, 65 had positive uptake for both [

conclusionsThe preoperative PSMA-negative/FDG-positive phenotype is a significant and independent predictor of early biochemical recurrence following radical prostatectomy in treatment-naive prostate cancer. These findings suggest that dual-tracer PET/CT may serve as a valuable preoperative risk stratification tool to identify patients with aggressive disease who might be suitable for neoadjuvant or intensified adjuvant therapeutic strategies.

Indexed as

Antigens, SurfaceFluorodeoxyglucose F18Glutamate Carboxypeptidase IIPositron Emission Tomography Computed TomographyProstatectomyProstatic NeoplasmsAgedGallium IsotopesGallium RadioisotopesHumansMaleMiddle AgedPhenotypeRetrospective StudiesTreatment FailureAntigens, SurfaceFluorodeoxyglucose F18FOLH1 protein, humangallium 68 PSMA-11Gallium IsotopesGallium RadioisotopesGlutamate Carboxypeptidase II11 PET/CT; [18F]F[68 Ga]GaFDG PET/CT; treatmentNaive prostate cancer; biochemical recurrencePSMA

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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.