Table 6.

Table presenting data for metabolites biomarkers.

Biomarker	Purpose	Number of Patients	Method	Diagnostic Value	Prognostic Value	Predictive Capacity	Type of Study	Reference
Putative markers	diagnostic	n = 124 (BCa = 63, control group = 61)	Urine samples were collected from 124 patients and then derivatizated. GC-MS analysis was performed with Pegasus® 4D GC × GC-TOFMS (LECO, St. Joseph, MI, USA). Data analysis performed with ChromaTOFF® Software (LECO, St. Joseph, MI, USA).	BCa vs. hernia differentiation		AUC = 0.976	retrospective	[52]
Urinary metabolomics	diagnostic	n = 44 (BCa = 29, LG = 10, HG = 19; control group = 15)	Metabolomics analysis on urine samples of 44 paitents was conducted with the Q300 Metabolite Assay Kit (Human Metabolomics Institute, Inc., Shenzen, Guangdong, China). Ultra-performance liquid chromatography coupled to tandem mass spectrometry (ACQUITY UPLC-Xevo TQ-S, Waters Corp., Milford, MA, USA) with an electrospray ionization (ESI) source was operated under positive and negative ion modes for the quantitation of metabolites. Data analysis performed with Targeted Metabolome Batch Quantification software (v1.0, Human Metabolomics Institute, Shenzen, Guangdong, China).	BCa detection		AUC = 0.983, Se. = 95.3%, Sp. = 100%	retrospective	[53]

Abbreviations: AUC—Area under the ROC Curve, n—number of patients participating in study, HG—high grade, LG—low grade, BCa—bladder cancer, PPV—positive predictive value, NPV—negative predictive value, Se.—sensitivity, Sp.—specificity, GC-MS—gas chromatography-mass spectrometry.