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

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 to

SUBMITTER: Wu Q 

PROVIDER: S-EPMC9295426 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature