New Statistical Technique for Analyzing MIC-Based Susceptibility Data

ABSTRACT Seventeen laboratories participated in a cooperative study to validate the regional susceptibility testing of Neisseria gonorrhoeae in The Netherlands. International reference strains were distributed. Each laboratory determined the MICs of ciprofloxacin, penicillin, and tetracycline, for each strain by Etest. To explore a more transparent assessment of quality and comparability, a statistical regression model was fitted to the data that accounted for the censoring of the MICs. The mean MICs found by all of the laboratories except three were closer than one 2-fold dilution step to the overall mean, and the mean MICs of each antimicrobial agent were close to the MICs for the international reference strains. This approach provided an efficient tool to analyze the performance of the Dutch decentralized gonococcal resistance monitoring system and confirmed good and comparable standards.

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