How to measure the impacts of antibiotic resistance and antibiotic development on empiric therapy: new composite indices

Postdoctoral project. Centre for Disease Modelling at York University.
Collaborators: Amy Hurford (Memorial U), Rita Finley (PHAC), David Patrick (UBC/BCCDC), Jianhong Wu (York U) and Andrew Morris (Sinai Health System/U of Toronto).
2016. BMJ Open. 6:e012040. http://bmjopen.bmj.com/content/6/12/e012040.abstract

ABSTRACT
Objectives
We aimed to construct widely useable summary measures of the net impact of antibiotic resistance on empiric therapy. Summary measures are needed to communicate the importance of resistance, plan and evaluate interventions, and direct policy and investment.
Design, setting and participants As an example, we retrospectively summarised the 2011 cumulative antibiogram from a Toronto academic intensive care unit.
Outcome measures We developed two complementary indices to summarise the clinical impact of antibiotic resistance and drug availability on empiric therapy. The Empiric Coverage Index (ECI) measures susceptibility of common bacterial infections to available empiric antibiotics as a percentage. The Empiric Options Index (EOI) varies from 0 to ‘the number of treatment options available’, and measures the empiric value of the current stock of antibiotics as a depletable resource. The indices account for drug availability and the relative clinical importance of pathogens. We demonstrate meaning and use by examining the potential impact of new drugs and threatening bacterial strains.
Conclusions In our intensive care unit coverage of device-associated infections measured by the ECI remains high (98%), but 37–44% of treatment potential measured by the EOI has been lost. Without reserved drugs, the ECI is 86–88%. New cephalosporin/β-lactamase inhibitor combinations could increase the EOI, but no single drug can compensate for losses. Increasing methicillin-resistant Staphylococcus aureus (MRSA) prevalence would have little overall impact (ECI=98%, EOI=4.8–5.2) because many Gram-positives are already resistant to β-lactams. Aminoglycoside resistance, however, could have substantial clinical impact because they are among the few drugs that provide coverage of Gram-negative infections (ECI=97%, EOI=3.8–4.5). Our proposed indices summarise the local impact of antibiotic resistance on empiric coverage (ECI) and available empiric treatment options (EOI) using readily available data. Policymakers and drug developers can use the indices to help evaluate and prioritise initiatives in the effort against antimicrobial resistance.

A poster describing our initial work on indices for device-associated infections in intensive care units was presented on at IDWeek (Oct 2015, San Diego, California).  We presented our analysis of the impact of changing resistance since 2000 on empiric therapy of severe device-associated infections in three Toronto academic intensive care units in an incubator poster at AMMI Canada (Apr 2016,  Vancouver, BC).

This work is part of a larger interdisciplinary project jointly funded by CIHR and NSERC.

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