Shalata Aya T, Shehata Mohamed, Van Bogaert Eric, Ali Khadiga M, Alksas Ahmed, Mahmoud Ali, El-Gendy Eman M, Mohamed Mohamed A, Giridharan Guruprasad A, Contractor Sohail, El-Baz Ayman
Biomedical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt.
Bioengineering Department, University of Louisville, Louisville, KY 40292, USA.
Cancers (Basel). 2022 Oct 14;14(20):5019. doi: 10.3390/cancers14205019.
Bladder cancer (BC) is the 10th most common cancer globally and has a high mortality rate if not detected early and treated promptly. Non-muscle-invasive BC (NMIBC) is a subclassification of BC associated with high rates of recurrence and progression. Current tools for predicting recurrence and progression on NMIBC use scoring systems based on clinical and histopathological markers. These exclude other potentially useful biomarkers which could provide a more accurate personalized risk assessment. Future trends are likely to use artificial intelligence (AI) to enhance the prediction of recurrence in patients with NMIBC and decrease the use of standard clinical protocols such as cystoscopy and cytology. Here, we provide a comprehensive survey of the most recent studies from the last decade (N = 70 studies), focused on the prediction of patient outcomes in NMIBC, particularly recurrence, using biomarkers such as radiomics, histopathology, clinical, and genomics. The value of individual and combined biomarkers is discussed in detail with the goal of identifying future trends that will lead to the personalized management of NMIBC.
膀胱癌(BC)是全球第十大常见癌症,如果不及早发现并及时治疗,死亡率很高。非肌层浸润性膀胱癌(NMIBC)是膀胱癌的一个亚分类,与高复发率和进展率相关。目前用于预测NMIBC复发和进展的工具使用基于临床和组织病理学标志物的评分系统。这些系统排除了其他可能有用的生物标志物,而这些生物标志物可以提供更准确的个性化风险评估。未来的趋势可能是利用人工智能(AI)来加强对NMIBC患者复发的预测,并减少膀胱镜检查和细胞学等标准临床方案的使用。在此,我们对过去十年的最新研究(N = 70项研究)进行了全面综述,重点是利用影像组学、组织病理学、临床和基因组学等生物标志物预测NMIBC患者的预后,特别是复发情况。我们详细讨论了单个和组合生物标志物的价值,目的是确定将导致NMIBC个性化管理的未来趋势。