Prediction of histological stage based on cystoscopic appearances of newly diagnosed bladder tumours

Vinnie During, Graham Sole, Anil Jha, Jane Anderson, Richard Bryan

Research output: Contribution to journalArticlepeer-review


In the 75–80% of urothelial bladder cancers (UBC) presenting as non-muscle invasive bladder cancer (NMIBC), transurethral resection of bladder tumour (TURBT) is the key treatment and staging procedure. In the 20–25% of patients with muscle invasive bladder cancer (MIBC), further cross-sectional imaging is required to complete the staging process before considering radical treatment. Given the adverse effects of ionising radiation, clinicians identify patients believed to have MIBC, and so requiring further imaging pre-TURBT, at the tumour histology/stage based on the tumour’s visual characteristics. There is minimal evidence describing the accuracy of such predictions in newly-diagnosed patients.

Over a 6-year period, a database of patients undergoing resection of newly-diagnosed bladder lesions in a single UK centre was prospectively established. Predictions based on histology were simultaneously recorded, and the accuracy of these predictions of histology/stage subsequently assessed.

One hundred and twenty two (73.1%) patients with histologically confirmed NMIBC had predictions recorded versus 45 (26.9%) patients with MIBC. Visual assessment predictions of MIBC had a sensitivity of 88.9% (95% confidence interval [CI] 76.5%–95.2%) and a specificity of 91.0% (95% CI 84.6%–94.9%), giving a positive predictive value of 78.4% (95% CI 65.4%–87.5%) and a negative predictive value of 95.7% (95% CI 90.3%–98.1%).

We find that visual assessment is accurate in predicting the presence of MIBC. This supports the practice of stratifying patients at the time of initial cystoscopy for those requiring further radiological staging pre-TURBT.
Original languageEnglish
Pages (from-to)547-551
Number of pages5
JournalAnnals of the Royal College of Surgeons of England
Issue number8
Early online date9 Aug 2016
Publication statusPublished - Nov 2016


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