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Validation of a Host Response Assay, SeptiCyte LAB, for Discriminating Sepsis from Systemic Inflammatory Response Syndrome in the ICU.

ABSTRACT: RATIONALE:A molecular test to distinguish between sepsis and systemic inflammation of noninfectious etiology could potentially have clinical utility. OBJECTIVES:This study evaluated the diagnostic performance of a molecular host response assay (SeptiCyte LAB) designed to distinguish between sepsis and noninfectious systemic inflammation in critically ill adults. METHODS:The study employed a prospective, observational, noninterventional design and recruited a heterogeneous cohort of adult critical care patients from seven sites in the United States (n = 249). An additional group of 198 patients, recruited in the large MARS (Molecular Diagnosis and Risk Stratification of Sepsis) consortium trial in the Netherlands ( www.clinicaltrials.gov identifier NCT01905033), was also tested and analyzed, making a grand total of 447 patients in our study. The performance of SeptiCyte LAB was compared with retrospective physician diagnosis by a panel of three experts. MEASUREMENTS AND MAIN RESULTS:In receiver operating characteristic curve analysis, SeptiCyte LAB had an estimated area under the curve of 0.82-0.89 for discriminating sepsis from noninfectious systemic inflammation. The relative likelihood of sepsis versus noninfectious systemic inflammation was found to increase with increasing test score (range, 0-10). In a forward logistic regression analysis, the diagnostic performance of the assay was improved only marginally when used in combination with other clinical and laboratory variables, including procalcitonin. The performance of the assay was not significantly affected by demographic variables, including age, sex, or race/ethnicity. CONCLUSIONS:SeptiCyte LAB appears to be a promising diagnostic tool to complement physician assessment of infection likelihood in critically ill adult patients with systemic inflammation. Clinical trial registered with www.clinicaltrials.gov (NCT01905033 and NCT02127502).

SUBMITTER: Miller RR

PROVIDER: S-EPMC6835074 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSystemic inflammation is a whole body reaction having an infection-positive (i.e., sepsis) or infection-negative origin. It is important to distinguish between these two etiologies early and accurately because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on peripheral blood RNAs could be discovered that would (1) determine which patients with systemic inflammation had sepsis, (2) be robust across independent patient cohorts, (3) be insensitive to disease severity, and (4) provide diagnostic utility. The goal of this study was to identify and validate such a molecular classifier.Methods and findingsWe conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICUs). Biomarker discovery utilized an Australian cohort (n = 105) consisting of 74 cases (sepsis patients) and 31 controls (post-surgical patients with infection-negative systemic inflammation) recruited at five tertiary care settings in Brisbane, Australia, from June 3, 2008, to December 22, 2011. A four-gene classifier combining CEACAM4, LAMP1, PLA2G7, and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte Lab, was validated using reverse transcription quantitative PCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Patients for validation were selected from the Molecular Diagnosis and Risk Stratification of Sepsis study (ClinicalTrials.gov, NCT01905033), which recruited ICU patients from the Academic Medical Center in Amsterdam and the University Medical Center Utrecht. Patients recruited from November 30, 2012, to August 5, 2013, were eligible for inclusion in the present study. Validation cohort 1 (n = 59) consisted entirely of unambiguous cases and controls; SeptiCyte Lab gave an area under curve (AUC) of 0.95 (95% CI 0.91-1.00) in this cohort. ROC curve analysis of an independent, more heterogeneous group of patients (validation cohorts 2-5; 249 patients after excluding 37 patients with an infection likelihood of "possible") gave an AUC of 0.89 (95% CI 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility of SeptiCyte Lab was evaluated by comparison to various clinical and laboratory parameters available to a clinician within 24 h of ICU admission. SeptiCyte Lab was significantly better at differentiating cases from controls than all tested parameters, both singly and in various logistic combinations, and more than halved the diagnostic error rate compared to procalcitonin in all tested cohorts and cohort combinations. Limitations of this study relate to (1) cohort compositions that do not perfectly reflect the composition of the intended use population, (2) potential biases that could be introduced as a result of the current lack of a gold standard for diagnosing sepsis, and (3) lack of a complete, unbiased comparison to C-reactive protein.ConclusionsSeptiCyte Lab is a rapid molecular assay that may be clinically useful in managing ICU patients with systemic inflammation. Further study in population-based cohorts is needed to validate this assay for clinical use.

Project description:Due to the low specificity and sensitivity of biomarkers in sepsis diagnostics, the prognosis of sepsis patient outcomes still relies on the assessment of clinical symptoms. Inflammatory response is crucial to sepsis onset and progression; however, the significance of inflammatory response-related genes (IRRGs) in sepsis prognosis is uncertain. This study developed an IRRG-based signature for sepsis prognosis and immunological function. The Gene Expression Omnibus (GEO) database was retrieved for two sepsis microarray datasets, GSE64457 and GSE69528, followed by gene set enrichment analysis (GSEA) comparing sepsis and healthy samples. A predictive signature for IRRGs was created using least absolute shrinkage and selection operator (LASSO). To confirm the efficacy and reliability of the new prognostic signature, Cox regression, Kaplan-Meier (K-M) survival, and receiver operating characteristic (ROC) curve analyses were performed. Subsequently, we employed the GSE95233 dataset to independently validate the prognostic signature. A single-sample GSEA (ssGSEA) was conducted to quantify the immune cell enrichment score and immune-related pathway activity. We found that more gene sets were enriched in the inflammatory response in sepsis patient samples than in healthy patient samples, as determined by GSEA. The signature of nine IRRGs permitted the patients to be classified into two risk categories. Patients in the low-risk group showed significantly better 28-d survival than those in the high-risk group. ROC curve analysis corroborated the predictive capacity of the signature, with the area under the curve (AUC) for 28-d survival reaching 0.866. Meanwhile, the ssGSEA showed that the two risk groups had different immune states. The validation set and external dataset showed that the signature was clinically predictive. In conclusion, a signature consisting of nine IRRGs can be utilized to predict prognosis and influence the immunological status of sepsis patients. Thus, intervention based on these IRRGs may become a therapeutic option in the future.

Project description:ObjectivesTo advance our biological understanding of pediatric septic shock, we measured the genome-level expression profiles of critically ill children representing the systemic inflammatory response syndrome (SIRS), sepsis, and septic shock spectrum.DesignProspective observational study involving microarray-based bioinformatics.SettingMultiple pediatric intensive care units in the United States.PatientsChildren <or=10 years of age: 18 normal controls, 22 meeting criteria for SIRS, 32 meeting criteria for sepsis, and 67 meeting criteria for septic shock on day 1. The available day 3 samples included 20 patients still meeting sepsis criteria, 39 patients still meeting septic shock criteria, and 24 patients meeting the exclusive day 3 category, SIRS resolved.InterventionsNone other than standard care.Measurements and main resultsLongitudinal analyses were focused on gene expression relative to control samples and patients having paired day 1 and day 3 samples. The longitudinal analysis focused on up-regulated genes revealed common patterns of up-regulated gene expression, primarily corresponding to inflammation and innate immunity, across all patient groups on day 1. These patterns of up-regulated gene expression persisted on day 3 in patients with septic shock, but not to the same degree in the other patient classes. The longitudinal analysis focused on down-regulated genes demonstrated gene repression corresponding to adaptive immunity-specific signaling pathways and was most prominent in patients with septic shock on days 1 and 3. Gene network analyses based on direct comparisons across the SIRS, sepsis, and septic shock spectrum, and all available patients in the database, demonstrated unique repression of gene networks in patients with septic shock corresponding to major histocompatibility complex antigen presentation. Finally, analyses focused on repression of genes corresponding to zinc-related biology demonstrated that this pattern of gene repression is unique to patients with septic shock.ConclusionsAlthough some common patterns of gene expression exist across the pediatric SIRS, sepsis, and septic shock spectrum, septic shock is particularly characterized by repression of genes corresponding to adaptive immunity and zinc-related biology.

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Validation of a Host Response Assay, SeptiCyte LAB, for Discriminating Sepsis from Systemic Inflammatory Response Syndrome in the ICU.

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