46 research outputs found
Meta-Analysis and Cost Comparison of Empirical versus Pre-Emptive Antifungal Strategies in Hematologic Malignancy Patients with High-Risk Febrile Neutropenia
Background: Invasive fungal disease (IFD) causes significant morbidity and mortality in hematologic malignancy patients with high-risk febrile neutropenia (FN). These patients therefore often receive empirical antifungal therapy. Diagnostic test-guided pre-emptive antifungal therapy has been evaluated as an alternative treatment strategy in these patients. Methods: We conducted an electronic search for literature comparing empirical versus pre-emptive antifungal strategies in FN among adult hematologic malignancy patients. We systematically reviewed 9 studies, including randomized-controlled trials, cohort studies, and feasibility studies. Random and fixed-effect models were used to generate pooled relative risk estimates of IFD detection, IFD-related mortality, overall mortality, and rates and duration of antifungal therapy. Heterogeneity was measured via Cochran’s Q test, I2 statistic, and between study τ2. Incorporating these parameters and direct costs of drugs and diagnostic testing, we constructed a comparative costing model for the two strategies. We conducted probabilistic sensitivity analysis on pooled estimates and one-way sensitivity analyses on other key parameters with uncertain estimates. Results: Nine published studies met inclusion criteria. Compared to empirical antifungal therapy, pre-emptive strategies were associated with significantly lower antifungal exposure (RR 0.48, 95% CI 0.27–0.85) and duration without an increase in IFD-related mortality (RR 0.82, 95% CI 0.36–1.87) or overall mortality (RR 0.95, 95% CI 0.46–1.99). The pre-emptive strategy cost 291.88 to $418.65 pre-emptive compared to empirical) than the empirical approach per FN episode. However, the cost difference was influenced by relatively small changes in costs of antifungal therapy and diagnostic testing. Conclusions: Compared to empirical antifungal therapy, pre-emptive antifungal therapy in patients with high-risk FN may decrease antifungal use without increasing mortality. We demonstrate a state of economic equipoise between empirical and diagnostic-directed pre-emptive antifungal treatment strategies, influenced by small changes in cost of antifungal therapy and diagnostic testing, in the current literature. This work emphasizes the need for optimization of existing fungal diagnostic strategies, development of more efficient diagnostic strategies, and less toxic and more cost-effective antifungals
Neuroimaging markers for studying Gulf-War illness: single-subject level analytical method based on machine learning
Gulf War illness (GWI) refers to the multitude of chronic health symptoms, spanning from fatigue, musculoskeletal pain, and neurological complaints to respiratory, gastrointestinal, and dermatologic symptoms experienced by about 250,000 GW veterans who served in the 1991 Gulf War (GW). Longitudinal studies showed that the severity of these symptoms often remain unchanged even years after the GW, and these veterans with GWI continue to have poorer general health and increased chronic medical conditions than their non-deployed counterparts. For better management and treatment of this condition, there is an urgent need for developing objective biomarkers that can help with simple and accurate diagnosis of GWI. In this study, we applied multiple neuroimaging techniques, including T1-weighted magnetic resonance imaging (T1W-MRI), diffusion tensor imaging (DTI), and novel neurite density imaging (NDI) to perform both a group-level statistical comparison and a single-subject level machine learning (ML) analysis to identify diagnostic imaging features of GWI. Our results supported NDI as the most sensitive in defining GWI characteristics. In particular, our classifier trained with white matter NDI features achieved an accuracy of 90% and F-score of 0.941 for classifying GWI cases from controls after the cross-validation. These results are consistent with our previous study which suggests that NDI measures are sensitive to the microstructural and macrostructural changes in the brain of veterans with GWI, which can be valuable for designing better diagnosis method and treatment efficacy studies.W81XWH-17-1-0440 - a department of Defense CDMRP new investigator awardPublished versio
The Evolving Landscape of Fungal Diagnostics, Current and Emerging Microbiological Approaches
Invasive fungal infections are increasingly recognized in immunocompromised hosts. Current diagnostic techniques are limited by low sensitivity and prolonged turnaround times. We review emerging diagnostic technologies and platforms for diagnosing the clinically invasive disease caused by Candida, Aspergillus, and Mucorales
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Frequent False-positive Bronchoalveolar Lavage Galactomannan Values in a Real-world Setting
Abstract Background: Invasive aspergillosis (IA) is the most common invasive mold infection (IMI) and early diagnosis is critical to improving clinical outcomes. Galactomannan (GM) is a major component of the Aspergillus cell wall. BAL GM is one of the mycologic criteria for diagnosis of probable IA, but it is frequently positive in patients with Aspergillus airway colonization, and its specificity has not been well-studied. Our goal was to estimate the specificity of a positive BAL galactomannan value in a contemporary cohort of consecutive patients with BAL GM checked as part of their workup for potential IA. Methods: We reviewed clinical and microbiologic data of patients who had at least one positive BAL GM (≥0.5), at Brigham and Women’s Hospital from November 2009 to March 2016. We applied EORTC/MSG IMI definitions to classify patients as having possible, probable or proven IMI, excluding BAL GM result as mycologic criterion. Results: We studied 134 patients. Median age was 58; 49% were women. 54% had hematologic malignancy (HM), 10% were solid organ (SOT) and 34% hematopoetic stem-cell transplant (HSCT) recipients. 60% received mold-active antifungal treatment. 4 patients (3%) had proven, 60 (45%) probable, 15 (11%) possible, and 55 (41%) no IMI. One had proven mucormycosis, making at least 42% of positive BAL GM results falsely positive (specificity 58%, 95% confidence interval 47–69%). 6-week mortality was 35% overall: 75% for proven, 47% probable, 33% possible, and 20% for no IMI (χ2 for trend P = 0.008). In patients with no IMI, 6-week mortality was comparable in those who did not receive mold-active treatment (13%, 5/38) and those who did (38%, 6/16, Fischer’s P = 0.07). Conclusion: In this study, at least 42% of positive BAL GM values were falsely positive, potentially exposing these patients to unnecessary antifungals. The number of ‘probable’ IMI cases (which, along with proven IMI are typically included in clinical trials of new antifungals) would be falsely increased by 25%, using a positive BAL GM alone to adjudicate IMI status. Accurate noninvasive tests for diagnosis of IMI are urgently needed. Table: % +BAL GM values in patients with no IMI at various cutoff values. BAL GM ≥ 0.5 BAL GM ≥ 0.8 BAL GM ≥ 1.0 Overall 42 22 17 HM 28 14 7 SOT 100 50 50 HSCT 30 11 7 Disclosures All authors: No reported disclosures
Comparison of IFD-related outcomes in empiric versus pre-emptive antifungal therapy in high-risk neutropenic patients.
<p>RR: relative risk, CI: confidence interval, IFD: invasive fungal disease, RR: relative risk, CI: confidence interval, M-H: Mantel-Haenszel fixed effects model, D-L: Dersimonian-Laird random effects models,—data unavailable and cannot be derived from this study</p><p>Comparison of IFD-related outcomes in empiric versus pre-emptive antifungal therapy in high-risk neutropenic patients.</p
Risk of bias in randomized studies as assessed by the Cochrane Collaboration’s “Risk of Bias” tool.
<p>Risk of bias in randomized studies as assessed by the Cochrane Collaboration’s “Risk of Bias” tool.</p
Forest plot of pooled relative risk of antifungal drug use comparing pre-emptive to empirical strategies.
<p>Forest plot of pooled relative risk of antifungal drug use comparing pre-emptive to empirical strategies.</p
Forest plot of pooled relative risk of IFD detection comparing pre-emptive to empirical strategies.
<p>Forest plot of pooled relative risk of IFD detection comparing pre-emptive to empirical strategies.</p