ArticleCentral European journal of urology2021
External validation of a magnetic resonance imaging-based algorithm for prediction of side-specific extracapsular extension in prostate cancer.
Article in Central European journal of urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review.Abdominal radiology (New York) · 2023Pooled it
- Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis.Insights into imaging · 2023Review
- Radiation after radical prostatectomy in elderly patients - a SEER database-derived competing-risk survival analysis of propensity score-matched age groups.Central European journal of urology · 2023Article
- E-Cadherin, Integrin Alpha2 (Cd49b), and Transferrin Receptor-1 (Tfr1) Are Promising Immunohistochemical Markers of Selected Adverse Pathological Features in Patients Treated with Radical Prostatectomy.Journal of clinical medicine · 2021Article
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6 authors at 3 institutions in 1 country.
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Abstract
introductionRecently developed algorithm for prediction of side-specific extracapsular extension (ECE) of prostate cancer required validation before being recommended to use. The algorithm assumed that ECE on a particular side was not likely with same side maximum tumor diameter (MTD) <15 mm AND cancerous tissue in ipsilateral biopsy <15% AND PSA <20 ng/mL (both sides condition). The aim of the study was to validate this predictive tool in patients from another department. MATERIAL AND
methodsData of 154 consecutive patients (308 prostatic lateral lobes) were used for validation. Predictive factors chosen in the development set of patients were assessed together with other preoperative parameters using logistic regression to check for their significance. Sensitivity, specificity, negative and positive predictive values were calculated for bootstrapped risk-stratified validation dataset.
resultsValidation cohort did not differ significantly from development cohort regarding PSA, PSA density, Gleason score (GS), MTD, age, ECE and seminal vesicle invasion rate. In bootstrapped data set (n = 200 random sampling) algorithm revealed 70.2% sensitivity (95% confidence interval (CI) 58.8-83.0%), 49.9% specificity (95%CI: 42.0-57.7%), 83.9% negative predictive value (NPV; 95%CI: 76.1-91.4%) and 31.1% positive predictive value (PPV; 95%CI: 19.6-39.7%). When limiting analysis to high-risk patients (Gleason score >7) the algorithm improved its performance: sensitivity 91%, specificity 47%, PPV 53%, NPV 89%.
conclusionsAnalyzed algorithm is useful for identifying prostate lobes without ECE and deciding on ipsilateral nerve-sparing technique during radical prostatectomy, especially in patients with GS >7. Due to significant number of false positives in case of: MTD ≥15 mm OR cancer in biopsy ≥15% OR PSA ≥20 ng/mL additional evaluation is necessary to aid decision-making.
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