Literature DB >> 23445082

Construction of predictive models for recurrence and progression in >1000 patients with non-muscle-invasive bladder cancer (NMIBC) from a single centre.

Bedeir Ali-El-Dein1, Prasanna Sooriakumaran, Quoc-Dien Trinh, Tamer S Barakat, Adel Nabeeh, El-Housseiny I Ibrahiem.   

Abstract

OBJECTIVE: To construct predictive models based on the objectively calculated risks of progression and recurrence of non-muscle-invasive bladder cancer (NMIBC) in a large cohort of patients from a single centre. PATIENTS AND METHODS: Between October 1984 and March 2009 a cohort of 1019 patients (877 males; 142 females; median age 44 years) with histologically confirmed NMIBC was included in this study. Among these patients, 74% received bacillus Calmette-Guérin (BCG)-based therapy. Complete transurethral resection of bladder tumour of all visible tumours was carried out in all patients, and the stage and grade were determined. Univariate analysis and multivariate Cox regression were used to identify predictors of recurrence and progression. The studied predictors included age, sex, stage, grade, associated carcinoma in situ, tumour size, multiplicity, macroscopic appearance of the tumour, history of recurrence and type of adjuvant intravesical therapy. Multivariate logistic regression models were used to develop the 12- and 60-month recurrence and progression predictive models. The predictive accuracy of the models was assessed for discrimination as well as calibration.
RESULTS: The median (range) follow-up was 44 (6-254) months. On multivariate analysis, stage, multiplicity, history of recurrence and adjuvant intravesical therapy were significantly associated with recurrence, whereas for progression only tumour grade and size were significant independent predictors. The constructed nomograms had a 64.9% and 69.4% chance of correctly distinguishing between two patients, one destined to have a recurrence and one not at 12 and 60 months, respectively. The constructed nomograms had a 70.2% and 73.5% chance of correctly distinguishing between two patients, one destined to progress and one not at 12 and 60 months, respectively. All predictive models were well calibrated.
CONCLUSIONS: Based on multivariate analysis of the studied prognostic factors nomograms for predicting recurrence and progression in NMIBC were constructed. Most of the studied patients had received BCG-based therapy, making these models more closely applicable to contemporary practice than others. These predictive models have reasonable discriminative ability and are well calibrated, but require external validation before they can be applied to other populations.
© 2013 BJU International.

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Year:  2013        PMID: 23445082     DOI: 10.1111/bju.12026

Source DB:  PubMed          Journal:  BJU Int        ISSN: 1464-4096            Impact factor:   5.588


  5 in total

1.  Development of a New Recurrence-Free Survival Prediction Nomogram for Patients with Primary Non-Muscle-Invasive Bladder Cancer Based on Preoperative Controlling Nutritional Status Score.

Authors:  Liwei Zhao; Ji Sun; Kai Wang; Shengcheng Tai; Runmiao Hua; Yufu Yu; Yi Fan; Jiaguo Huang
Journal:  Cancer Manag Res       Date:  2021-08-16       Impact factor: 3.989

2.  Tumor size and T stage correlate independently with recurrence and progression in high-risk non-muscle-invasive bladder cancer patients treated with adjuvant BCG.

Authors:  Ioannis Zachos; Vasileios Tzortzis; Lampros Mitrakas; Michael Samarinas; Anastasios Karatzas; Stavros Gravas; Gerasimos P Vandoros; Michael D Melekos; Athanasios G Papavassiliou
Journal:  Tumour Biol       Date:  2013-12-28

3.  OUTCOMES OF INTRAVESICAL BACILLUS CALMETTE-GUERIN IN A MULTIRACIAL COHORT WITH NON-MUSCLE-INVASIVE BLADDER CANCER.

Authors:  Emily Barry; Ilir Agalliu; Richard Maiman; Evan Shreck; Evan Kovac; Ahmed Aboumohamed; Alexander Sankin
Journal:  Urol Pract       Date:  2021-01-01

4.  A novel pathway to detect muscle-invasive bladder cancer based on integrated clinical features and VI-RADS score on MRI: results of a prospective multicenter study.

Authors:  Marco Bicchetti; Giuseppe Simone; Gianluca Giannarini; Rossano Girometti; Alberto Briganti; Eugenio Brunocilla; Gianpiero Cardone; Francesco De Cobelli; Caterina Gaudiano; Francesco Del Giudice; Simone Flammia; Costantino Leonardo; Martina Pecoraro; Riccardo Schiavina; Carlo Catalano; Valeria Panebianco
Journal:  Radiol Med       Date:  2022-06-28       Impact factor: 6.313

Review 5.  Non-muscle invasive bladder cancer risk stratification.

Authors:  Sumit Isharwal; Badrinath Konety
Journal:  Indian J Urol       Date:  2015 Oct-Dec
  5 in total

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