The Diagnostic Performance of Cxbladder Resolve, Alone and in Combination with Other Cxbladder Tests, in the Identification and Priority Evaluation of Patients at Risk for Urothelial Carcinoma.

PURPOSE: Cxbladder (Cxb) tests combine genomic biomarkers in urine with phenotypic and clinical data to classify hematuria patients into those at low/high probability of urothelial carcinoma (UC). Cxbladder Resolve (CxbR) is designed for use after Cxb Triage (CxbT) and Detect (CxbD), where CxbT-positive tests reflex to CxbD and CxbD-positive to CxbR to identify patients at high probability of high-impact tumors (HIT; high grade Ta, Tis or T1-T3). This study validated the diagnostic performance of CxbR in identifying HIT, and validated the algorithm of Cxb tests to segregate high-impact from low-impact tumors. MATERIALS AND METHODS: CxbR was developed in 863 hematuria patients in 3 studies in United States, Australia and New Zealand. CxbR, separately and combined with other Cxb tests, was validated in a prospective, observational U.S. study in 548 hematuria patients. All UC diagnoses were confirmed by histopathology. RESULTS: In the development data set, CxbR sensitivity was 92.4% (95% CI 83.3-96.7) and specificity 93.8% (95% CI 86.8-97.2) for identifying HIT within the high priority category. During external validation, sequential Cxb tests correctly ruled out 87.6% of patients from further workup (negative predictive value 99.4%); 100% of HIT were correctly identified (specificity 96.3%), and 3 low-grade tumors were missed. In both studies, all patients with HIT were correctly assigned to prioritized evaluation. CONCLUSIONS: CxbR has high sensitivity and specificity, correctly identifying all HIT. Sequential Cxb tests accurately segregate patients with a low vs high probability of HIT, focusing resources on those patients, with a diagnostic yield 4.8-fold higher than American Urological Association guideline stratification.

Clinical comparison of noninvasive urine tests for ruling out recurrent urothelial carcinoma.

OBJECTIVE: Patients with urothelial carcinoma (UC) undergo rigorous surveillance for recurrence. Noninvasive urine tests are not currently recommended by guideline panels owing to insufficient clinical benefit. The objective of this study was to prospectively compare the performance of the Cxbladder Monitor test to other commonly available urine markers and cytology for surveillance of patients with UC. METHODS AND MATERIALS: A total of 1,036 urine samples were collected from 803 patients undergoing surveillance for UC. Of these, 1,016 samples were directly assessed using cytology, NMP22 Bladderchek and NMP22 enzyme-linked immunosorbent assay (ELISA), and the clinically validated Cxbladder Monitor test. An exploratory analysis was also performed comparing data from 157 samples where UroVysion fluorescence in situ hybridization analysis was performed locally. RESULTS: The sensitivity of Cxbladder Monitor (0.91) significantly outperformed cytology (0.22), NMP22 ELISA (0.26), and NMP22 BladderChek (0.11). The negative predictive value of Cxbladder Monitor was also superior at 0.96 compared with cytology (0.87), NMP22 ELISA (0.87), and NMP22 BladderChek (0.86). All false-negative results (n = 14) observed using Cxbladder Monitor were also negative for cytology, NMP22 ELISA, and NMP22 BladderChek. In the more limited set, UroVysion fluorescence in situ hybridization also had inferior sensitivity (0.33) and negative predictive value (0.92). CONCLUSIONS: The Cxbladder Monitor test significantly outperforms current Food and Drug Administration-approved urine-based monitoring tests, as well as cytology, in a large representative population undergoing surveillance for recurrent UC. This supports using Cxbladder Monitor as a confirmatory negative adjunct to cystoscopy or to justify postponing cystoscopic investigations in patients with a low risk of recurrence.

Performance Characteristics of a Multigene Urine Biomarker Test for Monitoring for Recurrent Urothelial Carcinoma in a Multicenter Study.

PURPOSE: Urothelial carcinoma is associated with a high rate of recurrence. Guidelines recommend rigorous, regular surveillance programs that are invasive and expensive. This study describes a noninvasive urine test with sufficient sensitivity to rule out recurrent urothelial carcinoma, thereby reducing invasive diagnostic evaluations without compromising patient care. METHODS AND MATERIALS: A total of 1,036 urine samples were prospectively collected from 763 patients undergoing routine surveillance for recurrent urothelial carcinoma of the bladder. The purpose was to develop and validate a test with combined high sensitivity and high negative predictive value. Cxbladder Monitor combines gene expression, clinical and patient data, and it is designed to rule out the presence of recurrent urothelial carcinoma. RESULTS: Cxbladder Monitor showed an internally validated sensitivity of 0.93 with a negative predictive value of 0.97 and a test negative rate of 0.34. Sensitivity was 0.95 for recurrent disease with a high risk of progression (all high grade disease and low grade, stage T1 or greater disease) compared with 0.86 for low grade Ta disease. Subgroup analyses indicated that diagnostic performance was not significantly different in different age groups, or by gender or tumor stage. Sensitivity was not affected by adjuvant bacillus Calmette-Guérin treatment within the last 6 months. False-negative findings were reported in fewer than 1.5% of all samples collected. CONCLUSIONS: The Cxbladder Monitor test offers combined high sensitivity and high negative predictive value to rule out urothelial carcinoma. This test has clinical utility as a confirmatory negative adjunct to cystoscopy, potentially justifying the postponement/avoidance of cystoscopic investigations to monitor recurrence in patients.

A holistic comparative analysis of diagnostic tests for urothelial carcinoma: a study of Cxbladder Detect, UroVysion® FISH, NMP22® and cytology based on imputation of multiple datasets.

BACKGROUND: Comparing the relative utility of diagnostic tests is challenging when available datasets are small, partial or incomplete. The analytical leverage associated with a large sample size can be gained by integrating several small datasets to enable effective and accurate across-dataset comparisons. Accordingly, we propose a methodology for a holistic comparative analysis and ranking of cancer diagnostic tests through dataset integration and imputation of missing values, using urothelial carcinoma (UC) as a case study. METHODS: Five datasets comprising samples from 939 subjects, including 89 with UC, where up to four diagnostic tests (cytology, NMP22®, UroVysion® Fluorescence In-Situ Hybridization (FISH) and Cxbladder Detect) were integrated into a single dataset containing all measured records and missing values. The tests were firstly ranked using three criteria: sensitivity, specificity and a standard variable (feature) ranking method popularly known as signal-to-noise ratio (SNR) index derived from the mean values for all subjects clinically known to have UC versus healthy subjects. Secondly, step-wise unsupervised and supervised imputation (the latter accounting for the 'clinical truth' as determined by cystoscopy) was performed using personalized modelling, k-nearest-neighbour methods, multiple logistic regression and multilayer perceptron neural networks. All imputation models were cross-validated by comparing their post-imputation predictive accuracy for UC with their pre-imputation accuracy. Finally, the post-imputation tests were re-ranked using the same three criteria. RESULTS: In both measured and imputed data sets, Cxbladder Detect ranked higher for sensitivity, and urine cytology a higher specificity, when compared with other UC tests. Cxbladder Detect consistently ranked higher than FISH and all other tests when SNR analyses were performed on measured, unsupervised and supervised imputed datasets. Supervised imputation resulted in a smaller cross-validation error. Cxbladder Detect was robust to imputation showing a 2% difference in its predictive versus clinical accuracy, outperforming FISH, NMP22 and cytology. CONCLUSION: All data analysed, pre- and post-imputation showed that Cxbladder Detect had higher SNR and outperformed all other comparator tests, including FISH. The methodology developed and validated for comparative ranking of the diagnostic tests for detecting UC, may be further applied to other cancer diagnostic datasets across population groups and multiple datasets.

A segregation index combining phenotypic (clinical characteristics) and genotypic (gene expression) biomarkers from a urine sample to triage out patients presenting with hematuria who have a low probability of urothelial carcinoma.

BACKGROUND: Hematuria can be symptomatic of urothelial carcinoma (UC) and ruling out patients with benign causes during primary evaluation is challenging. Patients with hematuria undergoing urological work-ups place significant clinical and financial burdens on healthcare systems. Current clinical evaluation involves processes that individually lack the sensitivity for accurate determination of UC. Algorithms and nomograms combining genotypic and phenotypic variables have largely focused on cancer detection and failed to improve performance. This study aimed to develop and validate a model incorporating both genotypic and phenotypic variables with high sensitivity and a high negative predictive value (NPV) combined to triage out patients with hematuria who have a low probability of having UC and may not require urological work-up. METHODS: Expression of IGFBP5, HOXA13, MDK, CDK1 and CXCR2 genes in a voided urine sample (genotypic) and age, gender, frequency of macrohematuria and smoking history (phenotypic) data were collected from 587 patients with macrohematuria. Logistic regression was used to develop predictive models for UC. A combined genotypic-phenotypic model (G + P INDEX) was compared with genotypic (G INDEX) and phenotypic (P INDEX) models. Area under receiver operating characteristic curves (AUC) defined the performance of each INDEX: high sensitivity, NPV >0.97 and a high test-negative rate was considered optimal for triaging out patients. The robustness of the G + P INDEX was tested in 40 microhematuria patients without UC. RESULTS: The G + P INDEX offered a bias-corrected AUC of 0.86 compared with 0.61 and 0.83, for the P and G INDEXs respectively. When the test-negative rate was 0.4, the G + P INDEX (sensitivity = 0.95; NPV = 0.98) offered improved performance compared with the G INDEX (sensitivity = 0.86; NPV = 0.96). 80% of patients with microhematuria who did not have UC were correctly triaged out using the G + P INDEX, therefore not requiring a full urological work-up. CONCLUSION: The adoption of G + P INDEX enables a significant change in clinical utility. G + P INDEX can be used to segregate hematuria patients with a low probability of UC with a high degree of confidence in the primary evaluation. Triaging out low-probability patients early significantly reduces the need for expensive and invasive work-ups, thereby lowering diagnosis-related adverse events and costs.

Electrical capacitance as a rapid and non-invasive indicator of root length.

Measurement of tree root systems by conventional methods is a Herculean task. The electrical capacitance method offers a rapid and non-destructive alternative, but it has largely been restricted to herbaceous species. The Dalton Model has been the main concept for understanding equivalent root circuitry; it proposed that roots were cylindrical capacitors with epidermis and xylem being the external and internal electrodes. Capacitance (C) therefore varied in proportion to root surface area (A), mass (M), length (L) and relative permittivity of the plant tissue ε(r). We used the capacitance method on forest and plantation trees (13 to circa 100 y.o.) in situ to test hypotheses derived from implicit assumptions about tree-root-soil circuitry. We concluded: C was not confounded by intermingled root systems; C was strongly related to diameter at breast height (DBH); C was less strongly related to DBH for multiple species at the same site; and C was a poor indicator of DBH, M and L across species, ages and sites. We proposed that ε(r) was proportional to root tissue density ρ and fitted a model with P < 0.05 and R(2) = 0.70 when the three immature (13 y.o.) trees were excluded. There was no significant difference (P = 0.28) between the parameters of the tree model (excluding the immature trees) and one of the same form fitted to data from bean (Vicia faba L.; R(2) = 0.55). Together, the data sets suggested (R(2) = 0.94; n = 26) that there may exist a general relationship of this form applied over two orders of magnitude of L.