Scott R Evans1, Andrea M Hujer2, Hongyu Jiang1, Kristine M Hujer2, Thomas Hall3, Christine Marzan3, Michael R Jacobs4, Rangarajan Sampath3, David J Ecker3, Claudia Manca5, Kalyan Chavda5, Pan Zhang6, Helen Fernandez6, Liang Chen5, Jose R Mediavilla5, Carol B Hill7, Federico Perez2, Angela M Caliendo8, Vance G Fowler9, Henry F Chambers10, Barry N Kreiswirth5, Robert A Bonomo11. 1. Center for Biostatistics in AIDS Research and the Department of Biostatistics, Harvard University, Boston, Massachusetts. 2. Department of Medicine, Case Western Reserve University School of Medicine Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio. 3. Ibis Biosciences, an Abbott Company, Carlsbad, California. 4. Department of Pathology, Case Western Reserve University School of Medicine, Cleveland, Ohio. 5. Public Health Research Institute Center, New Jersey Medical School-Rutgers University, Newark. 6. Weill Cornell Medical College, New York, New York. 7. Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina. 8. Department of Medicine, Alpert Medical School of Brown University, Providence, Rhode Island. 9. Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, North Carolina. 10. University of California, San Francisco General Hospital. 11. Department of Medicine, Case Western Reserve University School of Medicine Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, Ohio Departments of Pharmacology, Molecular Biology and Microbiology, Biochemistry, and Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, Ohio.
Abstract
BACKGROUND: Rapid molecular diagnostic (RMD) platforms may lead to better antibiotic use. Our objective was to develop analytical strategies to enhance the interpretation of RMDs for clinicians. METHODS: We compared the performance characteristics of 4 RMD platforms for detecting resistance against β-lactams in 72 highly resistant isolates of Escherichia coli and Klebsiella pneumoniae (PRIMERS I). Subsequently, 2 platforms were used in a blinded study in which a heterogeneous collection of 196 isolates of E. coli and K. pneumoniae (PRIMERS II) were examined. We evaluated the genotypic results as predictors of resistance or susceptibility against β-lactam antibiotics. We designed analytical strategies and graphical representations of platform performance, including discrimination summary plots and susceptibility and resistance predictive values, that are readily interpretable by practitioners to inform decision-making. RESULTS: In PRIMERS I, the 4 RMD platforms detected β-lactamase (bla) genes and identified susceptibility or resistance in >95% of cases. In PRIMERS II, the 2 platforms identified susceptibility against extended-spectrum cephalosporins and carbapenems in >90% of cases; however, against piperacillin/tazobactam, susceptibility was identified in <80% of cases. Applying the analytical strategies to a population with 15% prevalence of ceftazidime-resistance and 5% imipenem-resistance, RMD platforms predicted susceptibility in >95% of cases, while prediction of resistance was 69%-73% for ceftazidime and 41%-50% for imipenem. CONCLUSIONS: RMD platforms can help inform empiric β-lactam therapy in cases where bla genes are not detected and the prevalence of resistance is known. Our analysis is a first step in bridging the gap between RMDs and empiric treatment decisions.
BACKGROUND: Rapid molecular diagnostic (RMD) platforms may lead to better antibiotic use. Our objective was to develop analytical strategies to enhance the interpretation of RMDs for clinicians. METHODS: We compared the performance characteristics of 4 RMD platforms for detecting resistance against β-lactams in 72 highly resistant isolates of Escherichia coli and Klebsiella pneumoniae (PRIMERS I). Subsequently, 2 platforms were used in a blinded study in which a heterogeneous collection of 196 isolates of E. coli and K. pneumoniae (PRIMERS II) were examined. We evaluated the genotypic results as predictors of resistance or susceptibility against β-lactam antibiotics. We designed analytical strategies and graphical representations of platform performance, including discrimination summary plots and susceptibility and resistance predictive values, that are readily interpretable by practitioners to inform decision-making. RESULTS: In PRIMERS I, the 4 RMD platforms detected β-lactamase (bla) genes and identified susceptibility or resistance in >95% of cases. In PRIMERS II, the 2 platforms identified susceptibility against extended-spectrum cephalosporins and carbapenems in >90% of cases; however, against piperacillin/tazobactam, susceptibility was identified in <80% of cases. Applying the analytical strategies to a population with 15% prevalence of ceftazidime-resistance and 5% imipenem-resistance, RMD platforms predicted susceptibility in >95% of cases, while prediction of resistance was 69%-73% for ceftazidime and 41%-50% for imipenem. CONCLUSIONS:RMD platforms can help inform empiric β-lactam therapy in cases where bla genes are not detected and the prevalence of resistance is known. Our analysis is a first step in bridging the gap between RMDs and empiric treatment decisions.
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Authors: Henry F Chip Chambers; Heather R Cross; Scott R Evans; Barry N Kreiswirth; Vance G Fowler Journal: Clin Infect Dis Date: 2017-03-15 Impact factor: 9.079
Authors: Claudia Manca; Carol Hill; Andrea M Hujer; Robin Patel; Scott R Evans; Robert A Bonomo; Barry N Kreiswirth Journal: Clin Infect Dis Date: 2017-03-15 Impact factor: 9.079
Authors: Scott R Evans; Thuy Tien T Tran; Andrea M Hujer; Carol B Hill; Kristine M Hujer; Jose R Mediavilla; Claudia Manca; T Nicholas Domitrovic; Federico Perez; Michael Farmer; Kelsey M Pitzer; Brigid M Wilson; Barry N Kreiswirth; Robin Patel; Michael R Jacobs; Liang Chen; Vance G Fowler; Henry F Chambers; Robert A Bonomo Journal: Clin Infect Dis Date: 2019-05-17 Impact factor: 9.079
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