Urine biomarkers individually and as a consensus model show high sensitivity and specificity for detecting UTIs.

BACKGROUND: Current diagnoses of urinary tract infection (UTI) by standard urine culture (SUC) has significant limitations in sensitivity, especially for fastidious organisms, and the ability to identify organisms in polymicrobial infections. The significant rate of both SUC "negative" or "mixed flora/contamination" results in UTI cases and the high prevalence of asymptomatic bacteriuria indicate the need for an accurate diagnostic test to help identify true UTI cases. This study aimed to determine if infection-associated urinary biomarkers can differentiate definitive UTI cases from non-UTI controls. METHODS: Midstream clean-catch voided urine samples were collected from asymptomatic volunteers and symptomatic subjects ≥ 60 years old diagnosed with a UTI in a urology specialty setting. Microbial identification and density were assessed using a multiplex PCR/pooled antibiotic susceptibility test (M-PCR/P-AST) and SUC. Three biomarkers [neutrophil gelatinase-associated lipocalin (NGAL), and Interleukins 8 and 1ß (IL-8, and IL-1ß)] were also measured via enzyme-linked immunosorbent assay (ELISA). Definitive UTI cases were defined as symptomatic subjects with a UTI diagnosis and positive microorganism detection by SUC and M-PCR, while definitive non-UTI cases were defined as asymptomatic volunteers. RESULTS: We observed a strong positive correlation (R2 > 0.90; p < 0.0001) between microbial density and the biomarkers NGAL, IL-8, and IL-1ß for symptomatic subjects. Biomarker consensus criteria of two or more positive biomarkers had sensitivity 84.0%, specificity 91.2%, positive predictive value 93.7%, negative predictive value 78.8%, accuracy 86.9%, positive likelihood ratio of 9.58, and negative likelihood ratio of 0.17 in differentiating definitive UTI from non-UTI cases, regardless of non-zero microbial density. NGAL, IL-8, and IL-1ß showed a significant elevation in symptomatic cases with positive microbe identification compared to asymptomatic cases with or without microbe identification. Biomarker consensus exhibited high accuracy in distinguishing UTI from non-UTI cases. CONCLUSION: We demonstrated that positive infection-associated urinary biomarkers NGAL, IL-8, and IL-1ß, in symptomatic subjects with positive SUC and/or M-PCR results was associated with definitive UTI cases. A consensus criterion with ≥ 2 of the biomarkers meeting the positivity thresholds showed a good balance of sensitivity (84.0%), specificity (91.2%), and accuracy (86.9%). Therefore, this biomarker consensus is an excellent supportive diagnostic tool for resolving the presence of active UTI, particularly if SUC and M-PCR results disagree.

A Diagnostic Test Combining Molecular Testing with Phenotypic Pooled Antibiotic Susceptibility Improved the Clinical Outcomes of Patients with Non-E. coli or Polymicrobial Complicated Urinary Tract Infections.

Purpose: Complicated UTIs (cUTIs) cause significant morbidity and healthcare resource utilization and cost. Standard urine culture has limitations in detecting polymicrobial and non-E. coli infections, resulting in the under-diagnosis and under-treatment of cUTIs. In this study, patient-reported outcomes were compared between treated and untreated patients when an advanced diagnostic test combining multiplex-polymerase chain reaction (M-PCR) with a pooled antibiotic susceptibility method (P-AST) was incorporated into the patients' clinical management. Methods: Patients who had symptoms typical of cUTI and positive M-PCR/P-AST test results were recruited from urology clinics. Symptom reduction and clinical cure rates were measured from day 0 through day 14 using the American English Acute Cystitis Symptom Score (ACSS) Questionnaire. Clinical cure was defined based on the sum of the scores of four US Food and Drug Administration (FDA) symptoms and the absence of visible blood in the urine. Results: Of 264 patients with suspected cUTI, 146 (55.4%) had exclusively non-E. coli infections (115 treated and 31 untreated) and 190 (72%) had polymicrobial infections (162 treated and 28 untreated). Treated patients exhibited greater symptom reduction compared to untreated ones on day 14 for those with exclusively non-E. coli organisms (3.18 vs 1.64, p = 0.006) and polymicrobial infections (3.52 vs 1.41, p = 0.002), respectively. A higher percentage of treated patients than of untreated patients achieved clinical cure for polymicrobial infections on day 14 (58.7% vs 36.4%, p = 0.049). Conclusion: Patients with cUTIs treated based on the M-PCR/P-AST diagnostic test had significantly improved symptom reduction and clinical cure rates compared to untreated patients among those with non-E. coli or polymicrobial infections.

Molecular classification of human cancers using a 92-gene real-time quantitative polymerase chain reaction assay.

CONTEXT: Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge. OBJECTIVE: Adoption of microarray technologies in the clinic remains limited. We aimed to bridge this technological gap by developing a real-time quantitative polymerase chain reaction (RT-PCR) assay. DESIGN: We constructed a microarray database of 466 frozen and 112 formalin-fixed, paraffin-embedded (FFPE) samples of both primary and metastatic tumors, measuring expression of 22,000 genes. From the microarray database, we used a genetic algorithm to search for gene combinations optimal for multitumor classification. A 92-gene RT-PCR assay was then designed and used to generate a database for 481 frozen and 119 FFPE tumor samples. RESULTS: The microarray-based K-nearest neighbor classifier demonstrated 84% accuracy in classifying 39 tumor types via cross-validation and 82% accuracy in predicting 112 independent FFPE samples. We successfully translated the microarray database to the RT-PCR platform, which allowed an overall success rate of 87% in classifying 32 different tumor classes in the validation set of 119 FFPE tumor samples. CONCLUSIONS: The RT-PCR-based expression assay involving 92 genes represents a powerful tool for accurately and objectively identifying the site of origin for metastatic tumors, especially in the cases of cancer of unknown primary. The assay uses RT-PCR and routine FFPE samples, making it suitable for rapid clinical adoption.