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Choosing Optimal Antifungal Agents To Prevent Fungal Infections in Nonneutropenic Critically Ill Patients: Trial Sequential Analysis, Network Meta-analysis, and Pharmacoeconomic Analysis.

ABSTRACT: The use of antifungal interventions in critically ill patients prior to invasive fungal infection (IFI) being microbiologically confirmed and the preferred drug are still controversial. A systematic literature search was performed to identify randomized controlled trials (RCTs) that compared untargeted antifungal treatments applied to nonneutropenic critically ill patients. The primary outcomes were all-cause mortality and proven IFI rates. A random-effects model was used with trial sequential analyses (TSA), a network meta-analysis (NMA) was conducted to obtain indirect evidence, and a cost-effectiveness analysis using a decision-analytic model was completed from the patient perspective over a lifetime horizon. In total, 19 RCTs involving 2,556 patients (7 interventions) were included. Untargeted antifungal treatment did not significantly decrease the incidence of all-cause mortality (odds ratio [OR] = 0.89, 95% confidence interval [95%CI] = 0.70 to 1.14), but it did reduce the incidence of proven IFI (OR = 0.45, 95%CI = 0.29 to 0.71) relative to placebo/no intervention. The TSA showed that there was sufficient evidence supporting these findings. In the NMA, the only significant difference found for both primary outcomes was between fluconazole and placebo/no intervention in preventing proven IFI (OR = 0.35, 95%CI = 0.19 to 0.65). Based on drug and hospital costs in China, the incremental cost-effectiveness ratios per life-year saved for fluconazole, caspofungin, and micafungin relative to placebo/no intervention corresponded to US$889, US$9,994, and US$10,351, respectively. Untargeted antifungal treatment significantly reduced proven IFI rates in nonneutropenic critically ill patients but with no mortality benefits relative to placebo/no intervention. Among the well-tolerated antifungals, fluconazole remains the only one that is effective for IFI prevention and significantly cheaper than echinocandins.

SUBMITTER: Wang Y

PROVIDER: S-EPMC5700297 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Choosing Optimal Antifungal Agents To Prevent Fungal Infections in Nonneutropenic Critically Ill Patients: Trial Sequential Analysis, Network Meta-analysis, and Pharmacoeconomic Analysis.

Wang Yan Y Xie Jiao J Xing Yuanming Y Chen Lu L Li Ying Y Meng Ti T Dong Weihua W Wang Xue X Dong Yalin Y

Antimicrobial agents and chemotherapy 20171122 12

The use of antifungal interventions in critically ill patients prior to invasive fungal infection (IFI) being microbiologically confirmed and the preferred drug are still controversial. A systematic literature search was performed to identify randomized controlled trials (RCTs) that compared untargeted antifungal treatments applied to nonneutropenic critically ill patients. The primary outcomes were all-cause mortality and proven IFI rates. A random-effects model was used with trial sequential a ...[more]

PMID: 28993334

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Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood 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 overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyteÂ® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyteÂ® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood 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 the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyteÂ® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyteÂ® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyteÂ® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyteÂ® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator

Dataset Information

Choosing Optimal Antifungal Agents To Prevent Fungal Infections in Nonneutropenic Critically Ill Patients: Trial Sequential Analysis, Network Meta-analysis, and Pharmacoeconomic Analysis.

Publications

Choosing Optimal Antifungal Agents To Prevent Fungal Infections in Nonneutropenic Critically Ill Patients: Trial Sequential Analysis, Network Meta-analysis, and Pharmacoeconomic Analysis.

Similar Datasets

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