NMIBC Risk Calculators

A new risk stratification model for intravesical recurrence, disease progression, and cancer-specific death in patients with non-muscle invasive bladder cancer: the J-NICE risk tables

BACKGROUND

The aim of this study is to establish new risk tables for the current clinical setting, enabling short- and long-term risk stratification for recurrence, progression, and cancer-specific death after transurethral resection in non-muscle invasive bladder cancer (NMIBC). Currently available risk tables lack input from the 2004 World Health Organization grading system and risk prediction for cancer-specific death.

METHODS

This was a multi-institutional database study of 1490 patients diagnosed with NMIBC (the development cohort). A multivariate Fine and Gray subdistribution hazard model was used to assess the prognostic impact of various factors. Patients were classified into low-, intermediate-, and high-risk groups according to a sum of the weight of selected factors, and predicted cumulative rates were calculated. Internal validation was conducted using 200 bootstrap resamples to assess the optimism for the c-index and estimate a bias-corrected c-index. External validation of the developed risk table was performed on an independent dataset of 91 patients.

RESULTS

The Japanese NIshinihon uro-onCology Extensive collaboration group (J-NICE) risk stratification table was derived from six, five, and two factors for recurrence, progression, and cancer-specific death, respectively. The internal validation bias-corrected c-index values were 0.619, 0.621, and 0.705, respectively. The application of the J-NICE table to an external dataset resulted in c-indices for recurrence, progression, and cancer-specific death of 0.527, 0.691, and 0.603, respectively.

CONCLUSIONS

We propose a novel risk stratification model that predicts outcomes of treated NMIBC and may overcome the shortcomings of existing risk models. Further external validation is required to strengthen its clinical impact.

Prediction models for progression of non-muscle-invasive bladder cancer: A review

An accurate prediction of progression is critically important in the management of non-muscle-invasive bladder cancer. At present, three risk models are widely known for prediction of the risk of tumor recurrence and progression of non-muscle-invasive bladder cancer: the European Organization for Research and Treatment of Cancer, Club Urológico Español de Tratamiento Oncológico, and new European Organization for Research and Treatment of Cancer models. Bladder neck involvement has been shown to be one of the significant predictors for progression in non-muscle-invasive bladder cancer, and a new scoring model (Tokyo Medical and Dental University model) consisting of bladder neck involvement, tumor grade, and stage has been developed and externally validated. However, the predictive abilities of these models are still unsatisfactory, and more precise models are necessary for accurate individual prediction of prognosis. Until now, time-fixed analysis has been used for most studies predicting the prognosis and outcome of non-muscle-invasive bladder cancer patients. In order to predict progression more precisely, time-dependent models should be developed using multiple-event analytical techniques, as non-muscle-invasive bladder cancer often progresses to muscle-invasive bladder cancer after multiple recurrences and changes in tumor characteristics over a long natural history. Integration of molecular markers is also a promising approach. A validated model that accurately predicts the risk of progression would help urologists and patients decide whether and when to choose radical cystectomy on an individual basis.

Prognostic and Prediction Tools in Bladder Cancer: A Comprehensive Review of the Literature

CONTEXT

This review focuses on risk assessment and prediction tools for bladder cancer (BCa).

OBJECTIVE

To review the current knowledge on risk assessment and prediction tools to enhance clinical decision making and counseling of patients with BCa.

EVIDENCE ACQUISITION

A literature search in English was performed using PubMed in July 2013. Relevant risk assessment and prediction tools for BCa were selected. More than 1600 publications were retrieved. Special attention was given to studies that investigated the clinical benefit of a prediction tool.

EVIDENCE SYNTHESIS

Most prediction tools for BCa focus on the prediction of disease recurrence and progression in non-muscle-invasive bladder cancer or disease recurrence and survival after radical cystectomy. Although these tools are helpful, recent prediction tools aim to address a specific clinical problem, such as the prediction of organ-confined disease and lymph node metastasis to help identify patients who might benefit from neoadjuvant chemotherapy. Although a large number of prediction tools have been reported in recent years, many of them lack external validation. Few studies have investigated the clinical utility of any given model as measured by its ability to improve clinical decision making. There is a need for novel biomarkers to improve the accuracy and utility of prediction tools for BCa.

CONCLUSIONS

Decision tools hold the promise of facilitating the shared decision process, potentially improving clinical outcomes for BCa patients. Prediction models need external validation and assessment of clinical utility before they can be incorporated into routine clinical care.

PATIENT SUMMARY

We looked at models that aim to predict outcomes for patients with bladder cancer (BCa). We found a large number of prediction models that hold the promise of facilitating treatment decisions for patients with BCa. However, many models are missing confirmation in a different patient cohort, and only a few studies have tested the clinical utility of any given model as measured by its ability to improve clinical decision making.

Expression profile of epithelial-mesenchymal transition markers in non-muscle-invasive urothelial carcinoma of the bladder: correlation with intravesical recurrence following transurethral resection

OBJECTIVES

To evaluate the expression of molecular markers involved in epithelial-mesenchymal transition (EMT), a key process mediating the progression of malignant tumors, in non-muscle-invasive urothelial carcinoma of the bladder (NMIUCB) to clarify the significance of these markers as predictors of intravesical recurrence in patients treated with transurethral resection (TUR).

MATERIALS AND METHODS

Expression levels of 13 EMT markers, including E-cadherin, N-cadherin, β-catenin, γ-catenin, fibronectin, matrix metalloproteinase (MMP)-2, MMP-9, Slug, Snail, TWIST, vimentin, ZEB1, and ZEB2, in TUR specimens obtained from 161 consecutive patients with NMIUCB were measured by immunohistochemical staining.

RESULTS

Of these 13 markers, significant differences in the incidence of intravesical recurrence were noted according to expression levels of E-cadherin, N-cadherin, MMP-2, MMP-9, and TWIST. Univariate analysis also identified expression levels of E-cadherin, N-cadherin, MMP-2, MMP-9 and TWIST, in addition to the tumor size, pathological T category, and concomitant carcinoma in situ, as significant predictors of intravesical recurrence-free survival. Of these significant factors, expression levels of E-cadherin, MMP-9, and TWIST; tumor size; and concomitant carcinoma in situ appeared to be independently associated with intravesical recurrence-free survival on multivariate analysis. Furthermore, there were significant differences in recurrence-free survival according to positive numbers of these 5 independent risk factors (i.e., positive for 0 or 1 factor vs. positive for 2 factors vs. positive for 3 or more factors).

CONCLUSIONS

Consideration of expression levels of EMT-associated markers in TUR specimens, in addition to conventional prognostic parameters, would contribute to the accurate prediction of intravesical recurrence following TUR for NMIUCB.