Cover Image

Radiomics for the prediction of overall survival in patients with bladder cancer prior to radical cystectomy

(1) Background: To evaluate radiomics features as well as a combined model with clinical parameters for predicting overall survival in patients with bladder cancer (BCa). (2) Methods: This retrospective study included 301 BCa patients who received radical cystectomy (RC) and pelvic lymphadenectomy....

Full description

Saved in:
Bibliographic Details
Main Authors: Woźnicki, Piotr (Author) , Laqua, Fabian Christopher (Author) , Messmer, Katharina (Author) , Kunz, Wolfgang Gerhard (Author) , Stief, Christian (Author) , Nörenberg, Dominik (Author) , Schreier, Andrea (Author) , Wójcik, Jan (Author) , Ruebenthaler, Johannes (Author) , Ingrisch, Michael (Author) , Ricke, Jens (Author) , Buchner, Alexander (Author) , Schulz, Gerald Bastian (Author) , Gresser, Eva (Author)
Format: Article (Journal)
Language:English
Published: 13 September 2022
In: Cancers
Year: 2022, Volume: 14, Issue: 18, Pages: 1-12
ISSN:2072-6694
DOI:10.3390/cancers14184449
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.3390/cancers14184449
Verlag, kostenfrei, Volltext: https://www.mdpi.com/2072-6694/14/18/4449
Get full text
Author Notes:Piotr Woźnicki, Fabian Christopher Laqua, Katharina Messmer, Wolfgang Gerhard Kunz, Christian Stief, Dominik Nörenberg, Andrea Schreier, Jan Wójcik, Johannes Ruebenthaler, Michael Ingrisch, Jens Ricke, Alexander Buchner, Gerald Bastian Schulz and Eva Gresser
Description
Summary:(1) Background: To evaluate radiomics features as well as a combined model with clinical parameters for predicting overall survival in patients with bladder cancer (BCa). (2) Methods: This retrospective study included 301 BCa patients who received radical cystectomy (RC) and pelvic lymphadenectomy. Radiomics features were extracted from the regions of the primary tumor and pelvic lymph nodes as well as the peritumoral regions in preoperative CT scans. Cross-validation was performed in the training cohort, and a Cox regression model with an elastic net penalty was trained using radiomics features and clinical parameters. The models were evaluated with the time-dependent area under the ROC curve (AUC), Brier score and calibration curves. (3) Results: The median follow-up time was 56 months (95% CI: 48-74 months). In the follow-up period from 1 to 7 years after RC, radiomics models achieved comparable predictive performance to validated clinical parameters with an integrated AUC of 0.771 (95% CI: 0.657-0.869) compared to an integrated AUC of 0.761 (95% CI: 0.617-0.874) for the prediction of overall survival (p = 0.98). A combined clinical and radiomics model stratified patients into high-risk and low-risk groups with significantly different overall survival (p < 0.001). (4) Conclusions: Radiomics features based on preoperative CT scans have prognostic value in predicting overall survival before RC. Therefore, radiomics may guide early clinical decision-making.
Item Description:Dieser Artikel gehört zum Special issue: Advance and new insights in bladder cancer
Gesehen am 16.10.2023
Physical Description:Online Resource
ISSN:2072-6694
DOI:10.3390/cancers14184449

Similar Items