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Diffuse Lung Disease |

Molecular Diagnostics Require a Bayesian Approach

Marya Zilberberg*, MD; A. Shorr, MD
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EviMed Research Group, Goshen, MA


Chest. 2012;142(4_MeetingAbstracts):437A. doi:10.1378/chest.1381422
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Abstract

SESSION TYPE: ILD Posters

PRESENTED ON: Wednesday, October 24, 2012 at 01:30 PM - 02:30 PM

PURPOSE: Traditional microbiology identification takes 48-72 hours to complete. This lag forces clinicians to rely on broad-spectrum empiric coverage. To address this gap, manufacturers are developing rapid molecular diagnostics (RMD). We hypothesized that RMD’s accuracy is more dependent upon population risk of harboring the culprit pathogen than to their sensitivity and specificity.

METHODS: We modeled the impact of changing a test’s characteristics on its positive (PPV) and negative (NPV) predictive values, and hence the risk of over- or under-treatment, within strata of an organism’s population prevalence. We used the range of risks (5%-50%) for methicillin-resistant Staphylococcus aureus (MRSA) among patients hospitalized with complicated skin and skin structure infections, pneumonia, or sepsis. MRSA diagnostics provided assumptions for the test sensitivity and specificity (95%-99%). Scenarios with low sensitivity and specificity (90%), and best- and worst-case scenarios normalized to the annual universe of populations of interest, were examined.

RESULTS: With a low prevalence (5%) and high test specificity, the PPV was 84%. Conversely, with 50% prevalence and 95% test specificity the PPV rose to >95%. Even when the test’s specificity and sensitivity were both 90%, in a high-risk population both PPV and NPV were ~90%. In the worst-case scenario, 150,000 patients with cSSSI, pneumonia and sepsis annually were at risk for inappropriate treatment, 91% of these at risk for over-treatment. In the best-case scenario, 81% of 18,000 patients at risk for inappropriate coverage were subject to over-treatment.

CONCLUSIONS: Although promising for limiting exposure to excessive antimicrobial coverage, RMDs alone will not solve the issue of inappropriate, and particularly over-, treatment. Increasing pre-test probability as a strategy to minimize antibiotic abuse results in more accurate patient classification than does developing a test with near-perfect characteristics. The healthcare community must build robust evidence and information technology infrastructure to guide appropriate use of such testing.

CLINICAL IMPLICATIONS: Clinicians need to use RMDs in a targeted manner in order not to promote the development of further antimicrobial resistance through over-treatment.

DISCLOSURE: The following authors have nothing to disclose: Marya Zilberberg, A. Shorr

No Product/Research Disclosure Information

EviMed Research Group, Goshen, MA

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