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Submission Status
Submitted
Abstract
Abstract Title
Prediction Nomograms of Prognosis in Bladder Urothelial Carcinoma Patients Receiving Radical Cystectomy-A Two-center Retrospective Research
Presentation Type
Podium Abstract
Manuscript Type
Clinical Research
Abstract Category *
Oncology: Bladder and UTUC
Author's Information
Number of Authors (including submitting/presenting author) *
6
No more than 10 authors can be listed (as per the Good Publication Practice (GPP) Guidelines).
Please ensure the authors are listed in the right order.
Country
China
Co-author 1
Junjie Ji shengshiyanjjj1314@163.com The Affiliated Hospital of Qingdao University Urology Qingdao China
Co-author 2
Zengjin Wen wenzengjing2001@163.com Peking University Cancer Hospital & Institute Thoracic Surgery II Beijing China
Co-author 3
Yu Yao 962811311@qq.com The Affiliated Hospital of Qingdao University Urology Qingdao China
Co-author 4
Lei Jiang doctorjl97@126.com The Affiliated Hospital of Qingdao University Urology Qingdao China
Co-author 5
Qingya Yang yangqingya2012@163.com Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University Urology Qingdao China
Co-author 6
Guiming Zhang zhangguiming9@126.com The Affiliated Hospital of Qingdao University Urology Qingdao China *
Co-author 7
Co-author 8
Co-author 9
Co-author 10
Co-author 11
Co-author 12
Co-author 13
Co-author 14
Co-author 15
Co-author 16
Co-author 17
Co-author 18
Co-author 19
Co-author 20
Abstract Content
Introduction
This study aims to develop and validate nomograms for predicting overall survival (OS), cancer-specific survival (CSS), and disease-free survival (DFS) in patients with resectable bladder urothelial carcinoma (BUC) after radical cystectomy (RC).
Materials and Methods
Patients with BUC who received RC from the Affiliated Hospital of Qingdao University between January 2018 to December 2021 were assigned to the training cohort, while those from the Affiliated Hospital of Qingdao University between January 2016 to December 2017 and those from Qilu Hospital of Shandong University were assigned to the testing cohort. Demographic, pathological, imaging, and laboratory information were retrospectively collected. Univariate and multivariate COX regression analyses were employed to identify independent predictors for OS, CSS, and DFS in training cohort. The concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), corrected AUC after 1000-Bootstrap resampling with calibration curve, and DCA curve were used to assess the performance of nomograms in training cohort and testing cohort.
Results
393 and 156 patients were enrolled in training cohort and testing cohort, respectively. Multivariate analyses identified age, tumor size, lymph node metastasis (LNM), lymphovascular invasion (LVI), urea nitrogen, creatinine, and albumin/fibrinogen ratio (AFR) as independent predictors for OS; tumor size, LNM, LVI, urea nitrogen, and AFR as independent predictors for CSS; and LNM with LVI as independent predictors for DFS. The OS and CSS nomograms showed high prediction accuracy in C-indexes and ROC curves, reliability in calibration curves with corrected AUCs, and clinical application value in both cohorts. The DFS nomogram showed high accuracy with little changed corrected AUCs but limited stability in calibration curves in both cohorts.
Conclusions
The OS, CSS, and DFS nomograms were developed to predict prognosis in BUC patients treated with RC. These nomograms performed high accuracy, reliability, and clinical benefits in prediction in both cohorts.
Keywords
Bladder cancer; Bladder urothelial carcinoma; Radical cystectomy; Prognosis; Nomogram
Figure 1
https://storage.unitedwebnetwork.com/files/1237/62e7af69b4c00dcf3569939b56967b42.jpg
Figure 1 Caption
The nomograms for predicting OS (a), CSS (b), and DFS (c) in patients with resectable BUC receiving RC. OS, overall survival; CSS, cancer-specific survival; DFS, disease-free survival. BUC, bladder urothelial carcinoma; RC, radical cystectomy.
Figure 2
https://storage.unitedwebnetwork.com/files/1237/4fb2dc08d2a65e224d3f69d42ad3bdbc.jpg
Figure 2 Caption
The ROC curves for predicting 2-year OS rate (a), 3-year OS rate (b), and 5-year OS rate (c) in training cohort. The calibration curves of 2-year OS rate (d), 3-year OS rate (e), and 5-year OS rate (f) after 1000 bootstrap resampling in training coho
Figure 3
https://storage.unitedwebnetwork.com/files/1237/f3c3af97001b6ffd25aec842e1103f8c.jpg
Figure 3 Caption
The ROC curves for predicting 2-year OS rate (a), 3-year OS rate (b), and 5-year OS rate (c) in testing cohort. The calibration curves of 2-year OS rate (d), 3-year OS rate (e), and 5-year OS rate (f) after 1000 bootstrap resampling in testing cohort
Figure 4
https://storage.unitedwebnetwork.com/files/1237/65cc4f5b02fe92af0f4e450f98648f70.jpg
Figure 4 Caption
The ROC curves for predicting 2-year CSS rate (a), 3-year CSS rate (b), and 5-year CSS rate (c) in training cohort. The calibration curves of 2-year CSS rate (d), 3-year CSS rate (e), and 5-year CSS rate (f) after 1000 bootstrap resampling in trainin
Figure 5
https://storage.unitedwebnetwork.com/files/1237/1ea598d7f0008bda72636edc80ecaf54.jpg
Figure 5 Caption
The ROC curves for predicting 2-year CSS rate (a), 3-year CSS rate (b), and 5-year CSS rate (c) in testing cohort. The calibration curves of 2-year CSS rate (d), 3-year CSS rate (e), and 5-year CSS rate (f) after 1000 bootstrap resampling in testing
Character Count
2059
Vimeo Link
Presentation Details
Session
Free Paper Podium(03): Oncology Bladder UTUC (A)
Date
Aug. 14 (Thu.)
Time
16:48 - 16:54
Presentation Order
14