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Predicting Invasive Aspergillosis in Hematology Patients by Combining Clinical and Genetic Risk Factors with Early Diagnostic Biomarkers.

ABSTRACT: Personalized medicine provides a strategic approach to the management of IA. The incidence of IA in high-risk hematology populations is relatively low (<10%), despite unavoidable Aspergillus exposure in patients with a potentially similar clinical risk. Nonclinical variables, including genetic mutations that increase susceptibility to IA, could explain why only certain patients develop the disease. This study screened for mutations in 322 hematology patients classified according to IA status and developed a predictive model based on genetic risk, established clinical risk factors, and diagnostic biomarkers. Genetic markers were determined by real-time PCR and, with clinical risk factors and Aspergillus PCR results, subjected to multilogistic regression analysis to identify a best-fit model for predicting IA. The probability of IA was calculated, and an optimal threshold was determined. Mutations in dectin-1 (rs7309123) and DC-SIGN (rs11465384 and rs7248637), allogeneic stem cell transplantation, respiratory virus infection, and Aspergillus PCR positivity were all significant risk factors for developing IA and were combined in a predictive model. An optimal threshold requiring three positive factors generated a mean sensitivity/specificity of 70.4%/89.2% and a probability of developing IA of 56.7%. In patients with no risk factors, the probability of developing IA was 2.4%, compared to >79.1% in patients with four or more factors. Using a risk threshold of 50%, preemptive therapy would have been prescribed for 8.4% of the population. This pilot study shows that patients can be stratified according to risk of IA, providing personalized medicine based on strategic evidence for the management of IA. Further studies are required to confirm this approach.

SUBMITTER: White PL

PROVIDER: S-EPMC5744209 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Predicting Invasive Aspergillosis in Hematology Patients by Combining Clinical and Genetic Risk Factors with Early Diagnostic Biomarkers.

White P Lewis PL Parr Christian C Barnes Rosemary A RA

Journal of clinical microbiology 20171226 1

Personalized medicine provides a strategic approach to the management of IA. The incidence of IA in high-risk hematology populations is relatively low (<10%), despite unavoidable <i>Aspergillus</i> exposure in patients with a potentially similar clinical risk. Nonclinical variables, including genetic mutations that increase susceptibility to IA, could explain why only certain patients develop the disease. This study screened for mutations in 322 hematology patients classified according to IA sta ...[more]

PMID: 29118175

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Project description:BackgroundThe pathogenesis of invasive aspergillosis (IA) is still unknown, but its progression is rapid and mortality rate remains high. Bronchoalveolar lavage fluid (BALF) galactomannan (GM) analysis has been used to diagnose IA. This study is aimed at making an accurate estimate of the whole accuracy of BALF-GM in diagnosing IA.MethodsAfter a systematic review of the study, a bivariate meta-analysis was used to summarize the specificity (SPE), the sensitivity (SEN), the positive likelihood ratios (PLR), and the negative likelihood ratios (NLR) of BALF-GM in diagnosing IA. The overall test performance was summarized using a layered summary receiver operating characteristic (SROC) curve. Subgroup analysis was performed to explore the heterogeneity between studies.ResultsA total of 65 studies that are in line with the inclusion criteria were included. The summary estimates of BALF-GM analysis are divided into four categories. The first is the proven+probable vs. possible+no IA, with an SPE, 0.87 (95% CI, 0.85-0.98); SEN, 0.81 (95% CI, 0.76-0.84); PLR, 9.78 (5.78-16.56); and NLR, 0.20 (0.14-0.29). The AUC was 0.94. The BALF-GM test for proven+probable vs. no IA showed SPE, 0.88 (95% CI, 0.87-0.90); SEN, 0.82 (95% CI, 0.78-0.85); PLR, 6.56 (4.93-8.75); and NLR, 0.24 (0.17-0.33). The AUC was 0.93. The BALF-GM test for proven+probable+possible vs. no IA showed SPE, 0.82 (95% CI, 0.79-0.95); SEN, 0.59 (95% CI, 0.55-0.63); PLR, 3.60 (2.07-6.25); and NLR, 0.31 (0.15-0.61). The AUC was 0.86. The analyses for others showed SPE, 0.85 (95% CI, 0.83-0.87); SEN, 0.89 (95% CI, 0.86-0.91); PLR, 6.91 (4.67-10.22); and NLR, 0.18 (0.13-0.26). The AUC was 0.94.ConclusionsThe findings of this BALF-GM test resulted in some impact on the diagnosis of IA. The BALF-GM assay is considered a method for diagnosing IA with high SEN and SPE. However, the patients' underlying diseases may affect the accuracy of diagnosis. When the cutoff is greater than 1, the sensitivity will be higher.

Project description:BackgroundPulmonary computed tomography (CT) scans are commonly used as part of the clinical criteria in diagnostic workup of invasive fungal diseases like invasive aspergillosis, and may identify radiographic abnormalities, such as halo signs or air-crescent signs. We assessed the diagnostic utility of CT assessment in patients with hematologic malignancies or those who had undergone allogeneic hematopoietic stem cell transplantation in whom invasive aspergillosis was suspected.MethodsThis post-hoc analysis assessed data from a prospective, multicenter, international trial of voriconazole (with and without anidulafungin) in patients with suspected invasive aspergillosis (IA; proven, probable, or possible, using 2008 European Organisation for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group criteria) [NCT00531479]. Eligible patients received at least one baseline lung CT scan.ResultsOf 395 patients included in this post-hoc analysis, 240 patients (60.8%) had 'confirmed' proven (9/240, 3.8%) or probable (231/240, 96.3%) invasive aspergillosis (cIA) and 155 patients (39.2%) had 'non-confirmed' invasive aspergillosis (all nIA; all possible IA (de Pauw et al., Clin Infect Dis 46:1813-21, 2008)). Mean age was 52.3 and 50.5 years, 56.3 and 60.0% of patients were male, and most patients were white (71.7 and 71.0%) in the cIA and nIA populations, respectively. Median baseline galactomannan was 1.4 (cIA) and 0.2 (nIA), mean Karnofsky score was 65.3 (cIA) and 66.8 (nIA), and mean baseline platelet count was 48.0 (cIA) and 314.1 (nIA). Pulmonary nodules (46.8% of all patients), bilateral lung lesions (37.5%), unilateral lung lesions (28.4%), and consolidation (24.8%) were the most common radiographic abnormalities. Ground-glass attenuation (cIA: 24.2%; nIA: 11.6%; P < 0.01) and pulmonary nodules (cIA: 52.5%; nIA: 38.1%; P < 0.01) were associated with cIA. Other chest CT scan abnormalities (including halo signs and air-crescent signs) at baseline in patients with hematologic malignancy or hematopoietic stem cell transplantation, and suspected IA, were not associated with cIA.ConclusionsThese findings highlight the limitations in the sensitivity of chest CT scans for the diagnosis of IA, and reinforce the importance of incorporating other available clinical data to guide management decisions on individual patients, including whether empirical treatment is reasonable, pending full evaluation.Trial registrationNCT00531479 (First posted on ClinicalTrials.gov on September 18, 2007).

Dataset Information

Predicting Invasive Aspergillosis in Hematology Patients by Combining Clinical and Genetic Risk Factors with Early Diagnostic Biomarkers.

Publications

Predicting Invasive Aspergillosis in Hematology Patients by Combining Clinical and Genetic Risk Factors with Early Diagnostic Biomarkers.

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