External validation of nomograms including PSMA PET information for the prediction of lymph node involvement of prostate cancer
Rattachement africain : nl, us, de, hk, it, at, pl, gb. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
BACKGROUND: Novel nomograms predicting lymph node involvement (LNI) of prostate cancer (PCa) including PSMA PET information have been developed. However, their predictive accuracy in external populations is still unclear. PURPOSE: To externally validate four LNI nomograms including PSMA PET parameters (three Muehlematter models and the Amsterdam-Brisbane-Sydney model) as well as the Briganti 2012 and MSKCC nomograms. METHODS: Patients with histologically confirmed PCa undergoing preoperative MRI and PSMA PET/CT before radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND) were included. Model discrimination (AUC), calibration and net benefit using decision curve analysis were determined for each nomogram. RESULTS: A total of 437 patients were included, comprising 0.7% with low-risk disease, 39.8% with intermediate-risk disease, and 59.5% with high-risk disease. Among them, 86 out of 437 (19.7%) had pN1 disease. The sensitivity and specificity of PSMA PET/CT for the detection of LNI were 47.7% (95% CI: 36.8-58.7) and 95.4% (95% CI: 92.7-97.4), respectively. Among predictive models, the Amsterdam-Brisbane-Sydney model achieved the highest discrimination (AUC: 0.81, 95% CI: 0.76-0.86), followed by Muehlematter Model 1 (AUC: 0.79, 95% CI: 0.74-0.85), both with good calibration but slight systematic overestimation of risks across all thresholds. The MSKCC and Briganti 2012 models had AUCs of 0.68 (95% CI: 0.61-0.74) and 0.67 (95% CI: 0.61-0.73), respectively, and both had moderate calibration. Decision curve analysis indicated that the Amsterdam-Brisbane-Sydney model provided superior net benefit across thresholds of 5-20%, followed by the Muehlematter Model 1 nomogram showing benefit in the 14-20% range. Using thresholds of 8% for the Amsterdam-Brisbane-Sydney nomogram and 15% for Muehlematter Model 1, ePLND could be spared in 15% and 16% of patients, respectively, without missing any LNI cases. CONCLUSION: External validation of the Muehlematter Model 1 and Amsterdam-Brisbane-Sydney nomograms for predicting LNI confirmed their strong model discrimination, moderate calibration, and good clinical utility, supporting their reliability as tools to guide clinical decision-making.
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
- External validation of nomograms including PSMA PET information for the prediction of lymph node involvement of prostate cancer
- Date Crossref
- 02/04/2025
- 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.
Où se fait cette recherche
-
University Medical Center Utrecht Center for Image Sciences pays non établi dans la noticeÉtablissement de santé
-
Utrecht University pays non établi dans la noticeUniversité ou école supérieure
-
Canisius-Wilhelmina Ziekenhuis pays non établi dans la noticeÉtablissement de santé
-
St. Antonius Ziekenhuis pays non établi dans la noticeOrganisme public
-
University Medical Center Department of Urology pays non établi dans la noticeÉtablissement de santé
-
University Hospital and Clinics pays non établi dans la noticeÉtablissement de santé
-
Indiana University – Purdue University Indianapolis pays non établi dans la noticeUniversité ou école supérieure
-
Essen University Hospital pays non établi dans la noticeOrganisme public
-
Deutsches Konsortium für Translationale Krebsforschung pays non établi dans la noticeStructure de recherche
-
Chinese University of Hong Kong Department of Surgery pays non établi dans la noticeUniversité ou école supérieure
-
Hong Kong Sanatorium and Hospital Department of Nuclear Medicine and PET pays non établi dans la noticeOrganisme public
-
University of Padua pays non établi dans la noticeUniversité ou école supérieure
Center for Image Sciences — University Medical Center Utrecht, Utrecht University et Canisius-Wilhelmina Ziekenhuis, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.