Objectives: To evaluate the density percentage of biopsy-positive cores (BPCs) relative to prostate volume, defined as Id-BPC, compared with BPCs as a predictor of pelvic lymph node invasion (PLNI) in EAU high-risk prostate cancer (PCa) treated and staged with robot-assisted radical prostatectomy (RARP). Methods: Overall, 254 EAU high-risk patients were treated with RARP between January 2013 and December 2021. Results: Overall, PLNI was detected in 23.2% of patients who were more likely to present with standard adverse clinical features; likewise, on multivariate models, PLNI was independently predicted by both BPC and Id-BPC with the latter showing a stronger association (OR = 1.926; 95% CI: 1.246–2.977; p = 0.003) than the former (OR = 1.028; 95% CI: 1.014–1.042; p < 0.0001); moreover, when cancer density was categorized at Id-BPC ≥ 1.0 versus < 1.0, the prediction was even stronger (OR = 3.535; 95% CI: 1.551–8.054; p = 0.003). Conclusions: In the investigated population, Id-BPC was a stronger predictor of PLNI than BPC; accordingly, as Id-BPC increased, patients were more likely to have PLNI; equivalently, subjects presenting with Id-BPC less than one were 3.5 times less likely to have PLNI. This information has implications for clinical practice as well as for computing nomograms or patterns of artificial intelligence networks.

Index Cancer Density Is a Stronger Predictor of Pelvic Lymph Node Invasion than Percentage of Biopsy-Positive Cores in EAU High-Risk Prostate Cancer: Clinical Impact in 254 Patients Treated and Staged with Robot-Assisted Radical Prostatectomy

Montanaro, Francesca;Siracusano, Salvatore;
2025-01-01

Abstract

Objectives: To evaluate the density percentage of biopsy-positive cores (BPCs) relative to prostate volume, defined as Id-BPC, compared with BPCs as a predictor of pelvic lymph node invasion (PLNI) in EAU high-risk prostate cancer (PCa) treated and staged with robot-assisted radical prostatectomy (RARP). Methods: Overall, 254 EAU high-risk patients were treated with RARP between January 2013 and December 2021. Results: Overall, PLNI was detected in 23.2% of patients who were more likely to present with standard adverse clinical features; likewise, on multivariate models, PLNI was independently predicted by both BPC and Id-BPC with the latter showing a stronger association (OR = 1.926; 95% CI: 1.246–2.977; p = 0.003) than the former (OR = 1.028; 95% CI: 1.014–1.042; p < 0.0001); moreover, when cancer density was categorized at Id-BPC ≥ 1.0 versus < 1.0, the prediction was even stronger (OR = 3.535; 95% CI: 1.551–8.054; p = 0.003). Conclusions: In the investigated population, Id-BPC was a stronger predictor of PLNI than BPC; accordingly, as Id-BPC increased, patients were more likely to have PLNI; equivalently, subjects presenting with Id-BPC less than one were 3.5 times less likely to have PLNI. This information has implications for clinical practice as well as for computing nomograms or patterns of artificial intelligence networks.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/275967
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