ArticleProstate cancer and prostatic diseases2023
Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only.
Article in Prostate cancer and prostatic diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Lymphocele After Radical Prostatectomy: A Systematic Review of Risk Factors and Quantitative Synthesis Preventive Strategies.World journal of urology · 2026Pooled it
- Impact of peritoneal reconfiguration on lymphocele formation after robot-assisted radical prostatectomy with pelvic lymph node dissection: a systematic review and meta-analysis of randomized controlled trials.Prostate cancer and prostatic diseases · 2024Pooled it
- The predictive value of machine learning and nomograms for lymph node metastasis of prostate cancer: a systematic review and meta-analysis.Prostate cancer and prostatic diseases · 2023Pooled it
- Article
- Relative impact of lymph-node metastasis and seminal vesical invasion on oncologic outcomes following radical prostatectomy.Prostate cancer and prostatic diseases · 2024Article
- Briganti's 2012 nomogram is an independent predictor of prostate cancer progression in EAU intermediate-risk class: results from 527 patients treated with robotic surgery.Asian journal of andrology · 2024Article
- Analysis of biopsy pathology and risk factors of lymph node metastasis in prostate cancer.International urology and nephrology · 2024Article
- Robot-Assisted Radical Prostatectomy in Renal Transplant Recipients: A Systematic Review.Journal of clinical medicine · 2023Review
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16 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundNowadays a tool able to predict the risk of lymph-node invasion (LNI) in patients underwent target biopsy (TB) only before radical prostatectomy (RP) is still lacking. Our aim is to develop a model based on mp-MRI and target biopsy (TB) alone able to predict the risk of LNI.
methodsWe retrospectively extracted data of patients with preoperative positive mp-MRI and TB only who underwent RARP with ePLND from April 2014 to March 2020. A logistic regression model was performed to evaluate the impact of pre- and intra-operative factors on the risk of LNI. Model discrimination was assessed using an area under (AUC) the ROC curve. A nomogram, and its calibration plot, to predict the risk of LNI were generated based on the logistic model. A validation of the model was done using a similar cohort.
results461 patients were included, of which 52 (11.27) had LNI. After logistic regression analysis and multivariable model DRE, PI-RADS, seminal vesicle invasion, PSA and worst GS at I and II target lesions were significant predictors of LNI. The AUC was 0.74 [0.67-0.81] 95% CI. The calibration plot shows that our model is very close to the ideal one which is in the 95% CI. After the creation of a visual nomogram, the cut-off to discriminate between the risk or not of LNI was set with Youden index at 60 points that correspond to a risk of LNI of 7%. The model applied on a similar cohort shown a LH+ of 2.58 [2.17-2.98] 95% CI.
conclusionsOur nomogram for patients undergoing MRI-TB only takes into account clinical stage, SVI at MRI, biopsy Gleason pattern and PSA and it is able to identify patients with risk of LNI when a score higher than 7% is achieved.
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