Linear Regression Equations To Predict β-Lactam, Macrolide, Lincosamide, and Fluoroquinolone MICs from Molecular Antimicrobial Resistance Determinants in Streptococcus pneumoniae

= 747) isolates. The MICs for β-lactam antimicrobials were fully explained by amino acid substitutions in motif regions of the penicillin binding proteins PBP1a, PPB2b, and PBP2x. Accuracies of predicted MICs within 1 doubling dilution to phenotypically determined MICs were 97.4% for penicillin, 98.2% for ceftriaxone, 94.8% for erythromycin, 96.6% for clarithromycin, 98.2% for clindamycin, 100% for levofloxacin, and 98.8% for trimethoprim-sulfamethoxazole, with an overall sensitivity of 95.8% and specificity of 98.0%. Accuracies of predicted MICs to the phenotypically determined MICs were similar to those of phenotype-only MIC comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular determinants will facilitate the transition from routine phenotypic testing to whole-genome sequencing analysis and can fill the surveillance gap in an era of increased reliance on nucleic acid assay diagnostics to better monitor the dynamics of S. pneumoniae.