# Predicting Histopathological Outcomes from Cystoscopic Findings in Newly Diagnosed Bladder Cancer: A Prospective Observational Study

## TL;DR

This study shows that cystoscopic observations during TURBT can predict bladder cancer outcomes with high accuracy, especially for low-grade tumors.

## Contribution

The study introduces a predictive model using cystoscopic features to improve bladder cancer staging and treatment decisions.

## Key findings

- Cystoscopic findings predicted histopathological outcomes with 81.05% accuracy.
- Larger (>3 cm) and sessile tumors were strong indicators of muscle-invasive bladder cancer.
- High NPV supports reliable exclusion of incorrect diagnoses, especially in resource-limited settings.

## Abstract

Background: Bladder cancer represents a major worldwide health challenge, with over 614,000 new diagnoses and approximately 220,000 fatalities reported globally in recent estimates, highlighting the urgent need for accurate early detection and staging to guide effective therapeutic interventions.

Objective: To assess the predictive accuracy of cystoscopic findings during initial transurethral resection of bladder tumor (TURBT) with histopathological outcomes in newly diagnosed bladder cancer, with the aim of enhancing diagnostic precision and guiding clinical management.

Methods: This prospective study enrolled 153 patients with newly diagnosed bladder tumors at a tertiary care center (January 2023-April 2025). Cystoscopic features (tumor size, number, location, morphology) were recorded using white light cystoscopy (WLC) at the time of TURBT, performed by two experienced urologic surgeons. These features were correlated with histopathological outcomes (grade, stage, subtype). Diagnostic accuracy was assessed via sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Logistic regression identified predictors of histopathological outcomes, and TURBT quality was evaluated by detrusor muscle presence.

Results: Of 153 patients (male-to-female ratio: 4.88:1; mean age: 56.97 ± 15.73 years), 71.24% had non-muscle-invasive bladder cancer (NMIBC), and 28.76% had muscle-invasive bladder cancer (MIBC). Tumors sized 1-3 cm were predominant (50.33%). The prediction model achieved 81.05% accuracy, with sensitivities of 81.65% for NMIBC and 79.55% for MIBC. Low-grade Ta (LGTa) tumors had the highest prediction accuracy (83.33%). Tumor size >3 cm and sessile morphology were significant predictors of MIBC (p<0.05).

Conclusion: Initial TURBT cystoscopic findings accurately predict histopathological outcomes in newly diagnosed bladder cancer, achieving an 81.05% diagnostic accuracy. Larger (>3 cm) and sessile tumors strongly indicate MIBC, while solitary, pedunculated tumors are associated with NMIBC. The high NPV (63.64%-99.17%) supports reliable exclusion of incorrect diagnoses, particularly in resource-limited settings. High-quality TURBT, with detrusor muscle sampled in 89.4% of cases, reduces understaging and guides treatment decisions. However, lower sensitivity for high-grade NMIBC suggests that repeat TURBT could enhance staging accuracy. Future multicenter studies incorporating repeat TURBT (re-TURBT) and advanced cystoscopic technologies are needed to improve predictions and personalize treatment.

Cystoscopic findings during TURBT reliably predict histopathological outcomes, particularly for LGTa tumors, with high NPV across stages.