Aller au contenu principal
Accès ouvert déclaré 2025 article

Development and validation of a visual nomogram for predicting clinically significant prostate cancer in negative mpMRI using 68Ga-PSMA PET/CT

1Citations signalées, ce qui n’est pas une note de qualité
9Institutions déclarées
1Pays d’affiliation déclarés

Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Multi-parametric magnetic resonance imaging (mpMRI) is a valuable medical technology for detecting clinically significant prostate cancer (csPCa). The diagnostic accuracy of mpMRI for csPCa in negative mpMRI (PI-RADS 1–2) remains suboptimal, underscoring the need for improvements for csPCa. This study aimed to build a visual predictive nomogram for early detection of csPCa in negative mpMRI. We retrospectively reviewed 303 men from our institution who simultaneously underwent 68Ga-PSMA-11 PET/CT and mpMRI before a biopsy between March 2020 and July 2022 and 130 men from the outside institution (Nanjing Drum Tower Hospital) as external validation between September 2021 and June 2022. The enrolled patients in our institution were randomly divided into the training set (n = 212) and the internal validation set (n = 91). Multivariate logistic regression was performed to identify independent predictors and establish a nomogram using SUVmax of 68Ga-PSMA-11 PET/CT and prostatic specific antigen density (PSAD) to predict the occurrence of csPCa in negative mpMRI. Multivariate logistic regression demonstrated that SUVmax (odds ratio [OR] 5.296, 95% confidence interval [CI] 1.691–23.972), and PSAD (OR 4.867, 95%CI 2.389–10.901) were independent predictors for csPCa in negative mpMRI. The area under the curve (AUC) of the nomogram was 0.819 (95%CI 0.729–0.890). Additionally, both the decision curve analysis (DCA) curve and the net reclassification improvement (NRI) showed significant improvements for csPCa in our model. External validation validated the reliability of the prediction nomogram. The visual interactive web risk calculator PI-RADS/SUVmax/PSAD model (PSP Model, www.cspca.online ) based on the nomogram allows us to assess the risk of having csPCa. The nomogram based on preoperative examination was developed to predict csPCa in negative mpMRI and help reduce unnecessary biopsies. The visual PSP Model is an effective and accurate tool for urologists to use in the early prediction and timely management of csPCa.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Development and validation of a visual nomogram for predicting clinically significant prostate cancer in negative mpMRI using 68Ga-PSMA PET/CT
Date Crossref
28/07/2025
Éditeur
Springer Science and Business Media LLC
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Prostate Cancer Treatment and ResearchProstate Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.