Paramananthan Mariappan1, Victoria Lavin2, Chu Qin Phua2, Shahid Aziz Anwar Khan2, Roland Donat2, Gordon Smith2. 1. Edinburgh Urological Cancer Group, Department of Urology, Western General Hospital, Edinburgh, United Kingdom. Electronic address: param.mariappan@nhs.net. 2. Edinburgh Urological Cancer Group, Department of Urology, Western General Hospital, Edinburgh, United Kingdom.
Abstract
OBJECTIVE: To assess urologists' ability to predict the grade and stage of new bladder cancers from the cystoscopic features alone. PATIENTS AND METHODS: We conducted a prospective clinical study on consecutive patients who underwent transurethral resection of bladder tumor (TURBT) for new bladder cancers. Using only cystoscopic tumor morphology at the time of initial TURBT, 3 urology consultants predicted the grade and stage, recording these on a proforma along with tumor features. Predictions were compared with assessments by uropathologists, blinded to the clinical prediction. We analyzed the accuracy in (1) predicting the exact grade and stage of the cancer; (2) differentiating between low- and high-grade cancers; and (3) discerning between Ta, T1, and T2 cancers. RESULTS: Of 248 patients, 224 were suitable for analysis. The positive predictive values for low- and high-grade cancers were 85.8% and 71.3%, respectively. The overall likelihood of a consultant predicting high-grade cancers as being low grade was 16/83 (19.3%). When tumors were large (>30 mm), this likelihood dropped significantly to 7.3% (4/55) (odds ratio = 3.1, 95% confidence interval = 1.0-9.7, P = .04). Non-muscle-invasive and muscle-invasive cancers were predicted accurately in 93.4% and 85.2% patients, respectively. Six of 161 (3.7%) tumors predicted to be non-muscle-invasive bladder cancer were actually muscle invasive on histology. CONCLUSION: For clinical purposes, in newly presenting patients with bladder cancer, urologists appear to reliably predict lower grade and muscle-invasive disease, confirming widely held belief. This allows for appropriate and efficient use of surgical expertise, available technology, and selection of participants for clinical trials on the basis of prehistology risk categories.
OBJECTIVE: To assess urologists' ability to predict the grade and stage of new bladder cancers from the cystoscopic features alone. PATIENTS AND METHODS: We conducted a prospective clinical study on consecutive patients who underwent transurethral resection of bladder tumor (TURBT) for new bladder cancers. Using only cystoscopic tumor morphology at the time of initial TURBT, 3 urology consultants predicted the grade and stage, recording these on a proforma along with tumor features. Predictions were compared with assessments by uropathologists, blinded to the clinical prediction. We analyzed the accuracy in (1) predicting the exact grade and stage of the cancer; (2) differentiating between low- and high-grade cancers; and (3) discerning between Ta, T1, and T2 cancers. RESULTS: Of 248 patients, 224 were suitable for analysis. The positive predictive values for low- and high-grade cancers were 85.8% and 71.3%, respectively. The overall likelihood of a consultant predicting high-grade cancers as being low grade was 16/83 (19.3%). When tumors were large (>30 mm), this likelihood dropped significantly to 7.3% (4/55) (odds ratio = 3.1, 95% confidence interval = 1.0-9.7, P = .04). Non-muscle-invasive and muscle-invasive cancers were predicted accurately in 93.4% and 85.2% patients, respectively. Six of 161 (3.7%) tumors predicted to be non-muscle-invasive bladder cancer were actually muscle invasive on histology. CONCLUSION: For clinical purposes, in newly presenting patients with bladder cancer, urologists appear to reliably predict lower grade and muscle-invasive disease, confirming widely held belief. This allows for appropriate and efficient use of surgical expertise, available technology, and selection of participants for clinical trials on the basis of prehistology risk categories.
Authors: Luís Vale; José Sousa; Pedro Abreu-Mendes; Pedro Vale; Nuno Dias; Paulo Dinis; Tiago Antunes-Lopes; João Silva Journal: Porto Biomed J Date: 2022-09-09