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| 037 | _ | _ | |a DKFZ-2024-01897 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Ostau, Nicola Edith von |b 0 |
| 245 | _ | _ | |a Bicenter validation of a risk model for the preoperative prediction of extraprostatic extension of localized prostate cancer combining clinical and multiparametric MRI parameters. |
| 260 | _ | _ | |a Heidelberg |c 2024 |b Springer |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a This study aimed to validate a previously published risk model (RM) which combines clinical and multiparametric MRI (mpMRI) parameters to predict extraprostatic extension (EPE) of prostate cancer (PC) prior to radical prostatectomy (RP).A previously published RM combining clinical with mpMRI parameters including European Society of Urogenital Radiology (ESUR) classification for EPE was retrospectively evaluated in a cohort of two urological university hospitals in Germany. Consecutive patients (n = 205, January 2015 -June 2021) with available preoperative MRI images, clinical information including PSA, prostate volume, ESUR classification for EPE, histopathological results of MRI-fusion biopsy and RP specimen were included. Validation was performed by receiver operating characteristic analysis and calibration plots. The RM's performance was compared to ESUR criteria.Histopathological T3 stage was detected in 43% of the patients (n = 89); 45% at Essen and 42% at Düsseldorf. Discrimination performance between pT2 and pT3 of the RM in the entire cohort was AUC = 0.86 (AUC = 0.88 at site 1 and AUC = 0.85 at site 2). Calibration was good over the entire probability range. The discrimination performance of ESUR classification alone was comparable (AUC = 0.87).The RM showed good discriminative performance to predict EPE for decision-making for RP as a patient-tailored risk stratification. However, when experienced MRI reading is available, standardized MRI reading with ESUR scoring is comparable regarding information outcome. A main limitation is the potentially limited transferability to other populations because of the high prevalence of EPE in our subgroups. |
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| 650 | _ | 7 | |a Extraprostatic extension |2 Other |
| 650 | _ | 7 | |a Multiparametric MRI |2 Other |
| 650 | _ | 7 | |a Positive surgical margins |2 Other |
| 650 | _ | 7 | |a Prostate cancer |2 Other |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Male |2 MeSH |
| 650 | _ | 2 | |a Prostatic Neoplasms: pathology |2 MeSH |
| 650 | _ | 2 | |a Prostatic Neoplasms: surgery |2 MeSH |
| 650 | _ | 2 | |a Prostatic Neoplasms: diagnostic imaging |2 MeSH |
| 650 | _ | 2 | |a Multiparametric Magnetic Resonance Imaging |2 MeSH |
| 650 | _ | 2 | |a Retrospective Studies |2 MeSH |
| 650 | _ | 2 | |a Risk Assessment |2 MeSH |
| 650 | _ | 2 | |a Middle Aged |2 MeSH |
| 650 | _ | 2 | |a Aged |2 MeSH |
| 650 | _ | 2 | |a Neoplasm Invasiveness |2 MeSH |
| 650 | _ | 2 | |a Prostatectomy: methods |2 MeSH |
| 650 | _ | 2 | |a Predictive Value of Tests |2 MeSH |
| 650 | _ | 2 | |a Preoperative Care: methods |2 MeSH |
| 700 | 1 | _ | |a Handke, Analena Elisa |0 0009-0000-9472-8956 |b 1 |
| 700 | 1 | _ | |a Wiesenfarth, Manuel |0 P:(DE-He78)1042737c83ba70ec508bdd99f0096864 |b 2 |u dkfz |
| 700 | 1 | _ | |a Albers, Peter |b 3 |
| 700 | 1 | _ | |a Antoch, Gerald |b 4 |
| 700 | 1 | _ | |a Noldus, Joachim |b 5 |
| 700 | 1 | _ | |a Reis, Henning |b 6 |
| 700 | 1 | _ | |a Cotarelo, Cristina |b 7 |
| 700 | 1 | _ | |a Preetz, Julia |b 8 |
| 700 | 1 | _ | |a Umutlu, Lale |b 9 |
| 700 | 1 | _ | |a Ingenwerth, Marc |b 10 |
| 700 | 1 | _ | |a Radtke, Jan Philipp |0 P:(DE-He78)79897f8897ff77676549d9895258a0f2 |b 11 |u dkfz |
| 700 | 1 | _ | |a Hadaschik, Boris |b 12 |
| 700 | 1 | _ | |a Schimmöller, Lars |b 13 |
| 700 | 1 | _ | |a Kesch, Claudia |b 14 |
| 773 | _ | _ | |a 10.1007/s00345-024-05232-6 |g Vol. 42, no. 1, p. 530 |0 PERI:(DE-600)1463303-6 |n 1 |p 530 |t World journal of urology |v 42 |y 2024 |x 0724-4983 |
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