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Updated: Apr 3, 2026

Author Spotlight: Advancing Pathogen Detection and Disease Assessment in Real-Time Using M-ROSE
Published on: March 1, 2024
Rapid Molecular Diagnostics, Antibiotic Treatment Decisions, and Developing Approaches to Inform Empiric Therapy:
Scott R Evans1, Andrea M Hujer2, Hongyu Jiang1
1Center for Biostatistics in AIDS Research and the Department of Biostatistics, Harvard University, Boston, Massachusetts.
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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