The application value of multi-parameter cystoscope in improving the accuracy of preoperative bladder cancer grading

To develop and validate a preoperative cystoscopic-based predictive model for predicting postoperative high-grade bladder cancer (BCa), which could be used to guide the surgical selection and postoperative treatment strategies. We retrospectively recruited 366 patients with cystoscopy biopsy for pat...

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Bibliographic Details
Published in:BMC urology 2022-07, Vol.22 (1), p.111-10, Article 111
Main Authors: Wu, Qikai, Cai, Lingkai, Yuan, Baorui, Cao, Qiang, Zhuang, Juntao, Bao, Meiling, Wang, Zhen, Feng, Dexiang, Tao, Jun, Li, Pengchao, Shao, Qiang, Yang, Xiao, Lu, Qiang
Format: Article
Language:English
Subjects:
Algae
Biopsy
Bladder
Bladder cancer
Cancer
Care and treatment
Cystectomy
Cystoscopes
Cystoscopic biopsy
High grade
Humans
Medical research
Medicine, Experimental
Morphology
Pathological grade
Pathology
Patients
Prediction models
Predictive model
Regression analysis
Retrospective Studies
Risk factors
Software
Tumors
Urinary Bladder - surgery
Urinary Bladder Neoplasms - pathology
Urology
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Summary:To develop and validate a preoperative cystoscopic-based predictive model for predicting postoperative high-grade bladder cancer (BCa), which could be used to guide the surgical selection and postoperative treatment strategies. We retrospectively recruited 366 patients with cystoscopy biopsy for pathology and morphology evaluation between October 2010 and January 2021. A binary logistic regression model was used to assess the risk factors for postoperative high-grade BCa. Diagnostic performance was analyzed by plotting receiver operating characteristic curve and calculating area under the curve (AUC), sensitivity, specificity. From January 2021 to July 2021, we collected 105 BCa prospectively to validate the model's accuracy. A total of 366 individuals who underwent transurethral resection of bladder tumor (TURBT) or radical cystectomy following cystoscopy biopsy were included for analysis. 261 (71.3%) had a biopsy pathology grade that was consistent with postoperative pathology grade. We discovered five cystoscopic parameters, including tumor diameter, site, non-pedicled, high-grade biopsy pathology, morphology, were associated with high-grade BCa. The established multi-parameter logistic regression model ("JSPH" model) revealed AUC was 0.917 (P 
ISSN:1471-2490
1471-2490
DOI:10.1186/s12894-022-01054-z