ArticleEuropean journal of nuclear medicine and molecular imaging2025
External validation of nomograms including PSMA PET information for the prediction of lymph node involvement of prostate cancer.
Article in European journal of nuclear medicine and molecular imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Can pelvic lymph node dissection be spared in intermediate-risk prostate cancer patients with negative PSMA PET scan? A systematic review and diagnostic meta-analysis.Prostate cancer and prostatic diseases · 2026Pooled it
- Guideline of guidelines: pelvic lymph node dissection at time of radical prostatectomy.BJU international · 2026Review
- Surgical Management of PSMA PET-Positive Lymph Nodes in Prostate Cancer.Current urology reports · 2026Review
- Article
- Prostate specific membrane antigen (PSMA) as a biomarker in early and localized advanced prostate cancer: a narrative review.The Canadian journal of urology · 2026Review
- Article
- Development and evaluation of a lymph node invasion risk prediction model in intermediate- and high-risk prostate cancer patients.Acta oncologica (Stockholm, Sweden) · 2025Article
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28 authors.
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Abstract
backgroundNovel 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.
methodsPatients 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.
resultsA 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.
conclusionExternal 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.
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