Publication: External tertiary-care-hospital validation of the epidemiological SEER-based nomogram predicting downgrading in high-risk prostate cancer patients treated with radical prostatectomy
Program
KU-Authors
KU Authors
Co-Authors
Garcia, Cristina Cano
Wenzel, Mike
Piccinelli, Mattia Luca
Hoeh, Benedikt
Landmann, Lea
Tian, Zhe
Humke, Clara
Incesu, Reha-Baris
Koellermann, Jens
Wild, Peter J.
Advisor
Publication Date
2023
Language
en
Type
Journal article
Journal Title
Journal ISSN
Volume Title
Abstract
We aimed to externally validate the SEER-based nomogram used to predict downgrading in biopsied high-risk prostate cancer patients treated with radical prostatectomy (RP) in a contemporary European tertiary-care-hospital cohort. We relied on an institutional tertiary-care database to identify biopsied high-risk prostate cancer patients in the National Comprehensive Cancer Network (NCCN) who underwent RP between January 2014 and December 2022. The model's downgrading performance was evaluated using accuracy and calibration. The net benefit of the nomogram was tested with decision-curve analyses. Overall, 241 biopsied high-risk prostate cancer patients were identified. In total, 51% were downgraded at RP. Moreover, of the 99 patients with a biopsy Gleason pattern of 5, 43% were significantly downgraded to RP Gleason pattern = 4 + 4. The nomogram predicted the downgrading with 72% accuracy. A high level of agreement between the predicted and observed downgrading rates was observed. In the prediction of significant downgrading from a biopsy Gleason pattern of 5 to a RP Gleason pattern = 4 + 4, the accuracy was 71%. Deviations from the ideal predictions were noted for predicted probabilities between 30% and 50%, where the nomogram overestimated the observed rate of significant downgrading. This external validation of the SEER-based nomogram confirmed its ability to predict the downgrading of biopsy high-risk prostate cancer patients and its accurate use for patient counseling in high-volume RP centers.
Description
Source:
Diagnostics
Publisher:
MDPI
Keywords:
Subject
Medicine, General, Internal