The recurrence rate of non-muscle-invasive bladder cancer (NMIBC) is up to 60% within the first year of therapy. Accurate risk stratification is necessary for patient counselling, follow-up scheduling and individualized therapeutic decision making. Current prognostic models rely on clinicopathologic features, but their discrimination remains limited when in external cohorts. Despite intense efforts regarding the value of biomarkers in prognosticating outcomes in NMIBC, clinical utility remains suboptimal. It is clear that a single biomarker is not enough for the prediction of disease recurrence. Therefore, panels of non-redundant biomarkers have been created and integrated in clinical prognostic model further research relying on high throughput technologies is required. Areas covered: We performed a systematic research of the English-language literature on tissue biomarkers for prediction of NMIBC outcomes up to December 2017. Expert commentary: Despite the essential milestones achieved in our knowledge and understanding of the molecular biology underlying NMIBC, no biomarker has been implemented together with clinical feature in clinical practice. Integration of such biomarkers into predictive and prognostic model could, however, improve our accuracy, thereby paving the way for personalized medicine in the management of NMIBC.

Progressive tissue biomarker profiling in non-muscle-invasive bladder cancer / D'Andrea, David; Hassler, Melanie R; Abufaraj, Mohammad; Soria, Francesco; Ertl, Iris E; Ilijazi, Dafina; Mari, Andrea; Foerster, Beat; Egger, Gerda; Shariat, Shahrokh F. - In: EXPERT REVIEW OF ANTICANCER THERAPY. - ISSN 1473-7140. - STAMPA. - 18:(2018), pp. 695-703. [10.1080/14737140.2018.1474104]

Progressive tissue biomarker profiling in non-muscle-invasive bladder cancer

Mari, Andrea;
2018

Abstract

The recurrence rate of non-muscle-invasive bladder cancer (NMIBC) is up to 60% within the first year of therapy. Accurate risk stratification is necessary for patient counselling, follow-up scheduling and individualized therapeutic decision making. Current prognostic models rely on clinicopathologic features, but their discrimination remains limited when in external cohorts. Despite intense efforts regarding the value of biomarkers in prognosticating outcomes in NMIBC, clinical utility remains suboptimal. It is clear that a single biomarker is not enough for the prediction of disease recurrence. Therefore, panels of non-redundant biomarkers have been created and integrated in clinical prognostic model further research relying on high throughput technologies is required. Areas covered: We performed a systematic research of the English-language literature on tissue biomarkers for prediction of NMIBC outcomes up to December 2017. Expert commentary: Despite the essential milestones achieved in our knowledge and understanding of the molecular biology underlying NMIBC, no biomarker has been implemented together with clinical feature in clinical practice. Integration of such biomarkers into predictive and prognostic model could, however, improve our accuracy, thereby paving the way for personalized medicine in the management of NMIBC.
2018
18
695
703
D'Andrea, David; Hassler, Melanie R; Abufaraj, Mohammad; Soria, Francesco; Ertl, Iris E; Ilijazi, Dafina; Mari, Andrea; Foerster, Beat; Egger, Gerda; Shariat, Shahrokh F
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1153257
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