The Application Value of Multi-parameter Cystoscope in Improving the Accuracy of Preoperative Bladder Cancer Grading

Overview

Journal BMC Urol

Publisher Biomed Central

Specialty Urology

Date 2022 Jul 19

PMID 35850869

Authors

Qikai Wu

Lingkai Cai

Baorui Yuan

Qiang Cao

Juntao Zhuang

Meiling Bao

Zhen Wang

Dexiang Feng

Jun Tao

Pengchao Li

Qiang Shao

Xiao Yang

Qiang Lu

Affiliations

Soon will be listed here.

Abstract

Purpose: 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.

Materials And Methods: 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.

Results: 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 < 0.001). Sensitivity and specificity were 86.2% and 84.0%, respectively. And the consistency of pre- and post-operative high-grade pathology was improved from biopsy-based 70.5% to JSPH model-based 85.2%. In a 105-patients prospective validation cohort, the consistency of pre- and post-operative high-grade pathology was increased from 63.1 to 84.2% after incorporation into JSPH model for prediction.

Conclusion: The cystoscopic parameters based "JSPH model" is accurate at predicting postoperative pathological high-grade tumors prior to operations.

Citing Articles

The vascular and morphological characteristics of tumors under narrow-band imaging as predictors for the grade and stage of bladder cancer: a prospective and multi-center study.

Liang H, Yang Q, Sun H, Xu Y, Wang J, Huang W Ann Med. 2023; 55(2):2281656.

PMID: 37949085 PMC: 10653648. DOI: 10.1080/07853890.2023.2281656.

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