OPTIMIZATION OF FOLLOW-UP OF NON-MUSCLE-INVASIVE BLADDER TUMORS WITH BIOMARKERS

ARCHIVOS ESPANOLES DE UROLOGIA(2022)

引用 0|浏览5
暂无评分
摘要
INTRODUCTION: Bladder cancer is the fifth most common tumor in the world. Moreover, it is one of the most expensive due to its high recurrence rate. Urinary biomarkers for surveillance of non muscle invasive bladder cancer is a promising and growing field due to the invasiveness of the actual methods, based on cystoscopy and cytology. Although current European Guidelines only consider the use of biomarkers in the low risk scenario as an alternative to cystoscopy when the patient declines invasive methods for the follow-up after surgery, there is increasing evidence of their safety in high risk tumors. MATERIAL AND METHODS: We have performed a review of the main urinary biomarkers, including FDA-approved ones, protein-based and genetic biomarkers. We have also described the different options to incorporate the biomarkers in the clinical practice. RESULTS: There are not randomized control trials comparing any biomarker with the gold standard follow-up. Most of the papers published so far are cohort studies, limitating the evidence of the results. Biomarkers can be used as an alternative of cystoscopy, in a non invasive follow-up, or alternating both tests. There are few economical studies comparing both options, but the evidence supports the efficiency of the main biomarkers. CONCLUSIONS: Cystoscopy and cytology are the gold standard for non muscle invasive bladder cancer surveillance. 2021 European Guidelines suggest, for the first time, an alternative use of biomarkers in a concrete low grade scenario to avoid invasive explorations to patients with low risk of progression. Paradoxically, biomarkers (mainly genetic ones) have a very good profile of sensitivity and negative predictive value in the high risk scenario. Although there is increasing evidence to support their implementation, the lack of fase IV trials hinders their daily use.
更多
查看译文
关键词
Bladder cancer, Biomarker, Surveillance
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要