Buturović, Ljubomir

Abstract Many patients in the emergency department present with signs and symptoms that arouse concern for sepsis; however, other explanations are also possible. There are currently no rapid tests used in clinical practice that reliably distinguish the presence of a bacterial or viral infection vs. a non-infectious etiology and can predict a patient’s likelihood to decompensate. The diagnostic and prognostic uncertainty in “gray zone” patients complicates the decision to begin therapy as clinicians need to balance the risk of withholding therapy vs. the risk of the therapy itself (e.g., overtreatment with antibiotics and hospitalization, which is costly, potentially harmful, and contributes to antibiotic resistance). The TriVerity™ Test uses isothermal amplification and machine-learning algorithms to quantify and interpret mRNA expression levels to determine both likelihood of bacterial infection, viral infection, or no infection, and whether the patient will likely require one or more critical interventions within 7 days. The three scores each fall into one of five interpretation bands ranging from Very high to Very low. Testing takes approximately 30 minutes using the proprietary Myrna™ Instrument with an operator hands-on-time of under one minute. We enrolled 1,222 patients from 22 emergency departments (ED) to validate the performance of the TriVerity Test. Patients were treated as per local standard of care and were followed for 28 days. Bacterial and viral TriVerity results were validated against clinically adjudicated infection status; the illness severity TriVerity result was validated against the need for at least one critical interventions within 7 days. The bacterial TriVerity result had high AUROC for the diagnosis of bacterial infection (0.83; 80% CI 0.81–0.85) and divided bacterial infection likelihood scores into five interpretation bands with increasing likelihood ratios of infection ranging from Very low (LR- 0.08, 80% CI 0.06–0.11) to Very high (LR + 8.04, 80% CI 5.72–11.78). The AUROC for the bacterial TriVerity result was significantly higher compared to AUROCs for C-reactive protein, procalcitonin or white blood cell count. Similarly, the viral TriVerity score showed high AUROC for the diagnosis of viral infection (0.91; 80% CI 0.90–0.93) and likelihood ratios from Very low (LR- 0.09, 80% CI 0.05–0.14) to Very high (LR + 40.93; 80% CI 29.11–79.23). The TriVerity Illness Severity score showed a high AUROC for the prediction of illness severity (0.77; 80% CI 0.77–0.81) with scores divided into five interpretation bands with increasing likelihood ratios ranging from Very low (LR- 0.22; 80% CI 0.14–0.33) to Very high (LR + 11.33; 80% CI 7.31–17.00). TriVerity illness severity results allowed marked re-classification of the risk for “ICU-level care” as compared to clinical assessment (qSOFA scores) alone. In conclusion, TriVerity provides rapid, highly accurate and actionable results for the diagnosis and prognosis of patients with suspected acute infection and/or sepsis, supporting a major unmet medical need. TriVerity may improve personalized management of patients with suspected acute infections and suspected sepsis for improved overall healthcare outcomes.

Purpose Malignancies found in unexpected locations or with poorly differentiated morphologies can pose a significant challenge for tissue of origin determination. Current histologic and imaging techniques fail to yield definitive identification of the tissue of origin in a significant number of cases. The aim of this study was to validate a predefined 1,550-gene expression profile for this purpose. Methods Four institutions processed 547 frozen specimens representing 15 tissues of origin using oligonucleotide microarrays. Half of the specimens were metastatic tumors, with the remainder being poorly differentiated and undifferentiated primary cancers chosen to resemble those that present as a clinical challenge. Results In this blinded multicenter validation study the 1,550-gene expression profile was highly informative in tissue determination. The study found overall sensitivity (positive percent agreement with reference diagnosis) of 87.8% (95% CI, 84.7% to 90.4%) and overall specificity (negative percent agreement with reference diagnosis) of 99.4% (95% CI, 98.3% to 99.9%). Performance within the subgroup of metastatic tumors (n = 258) was found to be slightly lower than that of the poorly differentiated and undifferentiated primary tumor subgroup, 84.5% and 90.7%, respectively (P = .04). Differences between individual laboratories were not statistically significant. Conclusion This study represents the first adequately sized, multicenter validation of a gene-expression profile for tissue of origin determination restricted to poorly differentiated and undifferentiated primary cancers and metastatic tumors. These results indicate that this profile should be a valuable addition or alternative to currently available diagnostic methods for the evaluation of uncertain primary cancers.