Comparison of Relapse Risk Prediction Models During Active Surveillance in Stage I Seminoma: A Retrospective...

Area of Science:

• Oncology
• Urology
• Clinical Prediction Models

Background:

• Clinical stage I seminoma management often involves active surveillance post-orchidectomy.
• Accurate prediction of relapse is crucial for optimizing treatment strategies.
• Existing models for relapse prediction have limitations.

Purpose of the Study:

• To validate the Boormans model against the conventional classification for predicting relapse in clinical stage I seminoma.
• To assess the performance and clinical utility of the Boormans model.

Main Methods:

• Retrospective analysis of 1025 clinical stage I seminoma patients managed with active surveillance.
• Comparison of the Boormans model (tumor size, rete testis invasion, lymphovascular invasion) with conventional classification (tumor size >4 cm/rete testis invasion).
• Multivariable analysis to identify independent predictors of relapse.

Main Results:

• The Boormans model demonstrated superior discrimination (C-index 0.66 vs. 0.61) compared to the conventional model.
• Tumor size and rete testis invasion were independent predictors of relapse.
• While showing improved accuracy, the clinical utility of the Boormans model was limited in risk-adapted treatment scenarios.

Conclusions:

• The Boormans model offers enhanced predictive accuracy for relapse in clinical stage I seminoma.
• Further integration of novel biomarkers is needed to improve risk-stratification and clinical utility.
• More precise, risk-adapted management strategies are required for seminoma patients.