Predicting the risk of high-grade bladder cancer using noninvasive data

Nandakishore Shapur, Dov Pode, Ran Katz, Amos Shapiro, Vladimir Yutkin, Galina Pizov, Liat Appelbaum, Kevin C. Zorn, Mordechai Duvdevani, Ezekiel H. Landau, Ofer N. Gofrit

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Aim: To examine the hypothesis that the risk of high-grade bladder cancer can be predicted using noninvasively obtained data. Patients and Methods: We retrospectively analyzed the database of 431 patients that had transurethral resection of first-time bladder tumors between June 1998 and December 2009. Pre-operative parameters evaluated were: patients' age; gender; sonographic tumor diameter, number and location of tumor inside the bladder; presence of hydronephrosis, and results of urinary cytology. Parameters that showed significance in multivariate analysis were incorporated into the nomogram. Results: Multivariate analysis of the data showed that patient's age, the presence of hydronephrosis, sonographic tumor diameter (risk of a high-grade tumor: 14, 29, 43.3, 55.7 and 69.4% at diameters: 0.5-1.5, 1.6-2, 2.1-2.5, 2.6-3 and >3 cm, respectively), location of tumor in the bladder (risk of high-grade tumor: 28.8, 47, 67.5 and 90.5% in the lateral walls, posterior/base, anterior and dome, respectively), and urinary cytology were all highly significant and independent predictors of high-grade tumors. A nomogram constructed using these variables scored an area of 0.853 in the ROC curve. Conclusions: The risk of high-grade bladder tumor can be accurately predicted using non-invasively obtained information. This prediction can help to triage patients with newly detected bladder cancer for biopsy.

Original languageEnglish
Pages (from-to)319-324
Number of pages6
JournalUrologia Internationalis
Volume87
Issue number3
DOIs
StatePublished - Oct 2011
Externally publishedYes

Keywords

  • Bladder cancer
  • Nomogram

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