ArticleAnnals of nuclear medicine2026
Baseline Ga-68 PSMA PET/CT-derived volumetric parameters as predictors of biochemical recurrence following radical prostatectomy.
Article in Annals of nuclear medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to investigate the prognostic value of volumetric parameters derived from staging Ga-68 PSMA PET/CT imaging in predicting biochemical recurrence (BCR) among prostate cancer patients treated with radical prostatectomy.
methodsThis retrospective study included 217 patients diagnosed with prostate cancer between March 2018 and October 2024 who underwent preoperative Ga-68 PSMA PET/CT, subsequent radical prostatectomy, and had regular follow-up data available. Semiquantitative (SUVmax, SUVmean) and volumetric (PSMA-TV, TL-PSMA, wbPSMA-TV, wbTL-PSMA) parameters for both the primary prostate lesion and the whole body were calculated from the images. The primary endpoint was defined as biochemical progression-free survival (bPFS). ROC curve, Kaplan-Meier, and Cox regression analyses were utilized to evaluate prognostic performance.
resultsGa-68 PSMA PET/CT volumetric parameters, particularly wbPSMA-TV and wbTL-PSMA, were found to be significantly higher in patients who developed BCR. Univariate Cox regression analysis revealed that both volumetric and semiquantitative parameters were significantly associated with biochemical progression. However, in the multivariate analysis, volumetric parameters did not emerge as independent predictors; instead, prostate SUVmean, ISUP grade group, and positive surgical margin status were identified as independent prognostic factors. Addition of prostate SUVmean to a clinical model modestly improved discrimination (C-index: 0.587 vs. 0.608) and significantly improved model fit (p = 0.004). Furthermore, prostate SUVmax and SUVmean values demonstrated significant performance in predicting early biochemical progression occurring within the first year post-surgery.
conclusionsAlthough Ga-68 PSMA PET/CT-derived volumetric parameters were associated with biochemical progression, they were not validated as independent prognostic factors. Conversely, semiquantitative parameters-most notably prostate SUVmean-demonstrated independent prognostic value and may be significant indicators for predicting early biochemical progression. These findings suggest that prostate SUVmean and SUVmax could serve as complementary, preoperatively available indicators of early BCR risk when integrated with established clinicopathological factors, although their modest discriminative performance warrants external validation before clinical application.
Indexed as
Identifiers
42821058What OpenQuestion holds
Registered trials
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.