International multi-site initiative to develop an mri-inclusive nomogram for side-specific prediction of extraprostatic extension of prostate cancer
Research output: Contribution to journal › Journal article › Research › peer-review
Standard
International multi-site initiative to develop an mri-inclusive nomogram for side-specific prediction of extraprostatic extension of prostate cancer. / Wibmer, Andreas G.; Kattan, Michael W.; Alessandrino, Francesco; Baur, Alexander D.J.; Boesen, Lars; Franco, Felipe Boschini; Bonekamp, David; Campa, Riccardo; Cash, Hannes; Catalá, Violeta; Crouzet, Sebastien; Dinnoo, Sounil; Eastham, James; Fennessy, Fiona M.; Ghabili, Kamyar; Hohenfellner, Markus; Levi, Angelique W.; Ji, Xinge; Løgager, Vibeke; Margolis, Daniel J.; Moldovan, Paul C.; Panebianco, Valeria; Penzkofer, Tobias; Puech, Philippe; Radtke, Jan Philipp; Rouvière, Olivier; Schlemmer, Heinz Peter; Sprenkle, Preston C.; Tempany, Clare M.; Vilanova, Joan C.; Weinreb, Jeffrey; Hricak, Hedvig; Shukla-Dave, Amita.
In: Cancers, Vol. 13, No. 11, 2627, 2021.Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - International multi-site initiative to develop an mri-inclusive nomogram for side-specific prediction of extraprostatic extension of prostate cancer
AU - Wibmer, Andreas G.
AU - Kattan, Michael W.
AU - Alessandrino, Francesco
AU - Baur, Alexander D.J.
AU - Boesen, Lars
AU - Franco, Felipe Boschini
AU - Bonekamp, David
AU - Campa, Riccardo
AU - Cash, Hannes
AU - Catalá, Violeta
AU - Crouzet, Sebastien
AU - Dinnoo, Sounil
AU - Eastham, James
AU - Fennessy, Fiona M.
AU - Ghabili, Kamyar
AU - Hohenfellner, Markus
AU - Levi, Angelique W.
AU - Ji, Xinge
AU - Løgager, Vibeke
AU - Margolis, Daniel J.
AU - Moldovan, Paul C.
AU - Panebianco, Valeria
AU - Penzkofer, Tobias
AU - Puech, Philippe
AU - Radtke, Jan Philipp
AU - Rouvière, Olivier
AU - Schlemmer, Heinz Peter
AU - Sprenkle, Preston C.
AU - Tempany, Clare M.
AU - Vilanova, Joan C.
AU - Weinreb, Jeffrey
AU - Hricak, Hedvig
AU - Shukla-Dave, Amita
N1 - Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021
Y1 - 2021
N2 - Background: To develop an international, multi-site nomogram for side-specific prediction of extraprostatic extension (EPE) of prostate cancer based on clinical, biopsy, and magnetic resonance imaging-(MRI) derived data. Methods: Ten institutions from the USA and Europe contributed clinical and side-specific biopsy and MRI variables of consecutive patients who underwent prostatectomy. A logistic regression model was used to develop a nomogram for predicting side-specific EPE on prostatectomy specimens. The performance of the statistical model was evaluated by bootstrap resampling and cross validation and compared with the performance of benchmark models that do not incorporate MRI findings. Results: Data from 840 patients were analyzed; pathologic EPE was found in 320/840 (31.8%). The nomogram model included patient age, prostate-specific antigen density, side-specific biopsy data (i.e., Gleason grade group, percent positive cores, tumor extent), and side-specific MRI features (i.e., presence of a PI-RADSv2 4 or 5 lesion, level of suspicion for EPE, length of capsular contact). The area under the receiver operating characteristic curve of the new, MRI-inclusive model (0.828, 95% confidence limits: 0.805, 0.852) was significantly higher than that of any of the benchmark models (p < 0.001 for all). Conclusions: In an international, multi-site study, we developed an MRI-inclusive nomogram for the side-specific prediction of EPE of prostate cancer that demonstrated significantly greater accuracy than clinical benchmark models.
AB - Background: To develop an international, multi-site nomogram for side-specific prediction of extraprostatic extension (EPE) of prostate cancer based on clinical, biopsy, and magnetic resonance imaging-(MRI) derived data. Methods: Ten institutions from the USA and Europe contributed clinical and side-specific biopsy and MRI variables of consecutive patients who underwent prostatectomy. A logistic regression model was used to develop a nomogram for predicting side-specific EPE on prostatectomy specimens. The performance of the statistical model was evaluated by bootstrap resampling and cross validation and compared with the performance of benchmark models that do not incorporate MRI findings. Results: Data from 840 patients were analyzed; pathologic EPE was found in 320/840 (31.8%). The nomogram model included patient age, prostate-specific antigen density, side-specific biopsy data (i.e., Gleason grade group, percent positive cores, tumor extent), and side-specific MRI features (i.e., presence of a PI-RADSv2 4 or 5 lesion, level of suspicion for EPE, length of capsular contact). The area under the receiver operating characteristic curve of the new, MRI-inclusive model (0.828, 95% confidence limits: 0.805, 0.852) was significantly higher than that of any of the benchmark models (p < 0.001 for all). Conclusions: In an international, multi-site study, we developed an MRI-inclusive nomogram for the side-specific prediction of EPE of prostate cancer that demonstrated significantly greater accuracy than clinical benchmark models.
KW - Clinical staging
KW - Extraprostatic tumor extension
KW - Magnetic resonance imaging
KW - Nomogram
KW - Prostate cancer
U2 - 10.3390/cancers13112627
DO - 10.3390/cancers13112627
M3 - Journal article
C2 - 34071842
AN - SCOPUS:85106580240
VL - 13
JO - Cancers
JF - Cancers
SN - 2072-6694
IS - 11
M1 - 2627
ER -
ID: 302452425