TABLE 3.
Nonsynonymous mutations in pncA and alr improve diagnosis of resistance to pyrazinamide and cycloserine, respectivelya
| Drug | Gene | Mutation | Frequency | PPV | Sensitivity | Specificity |
|---|---|---|---|---|---|---|
| Pyrazinamide | Any | 19 | 1 | 1 | 1 | |
| pncA | LOF | 3 | 1 | 0.16 | 1 | |
| D8N | 1 | 1 | 0.05 | 1 | ||
| Q10R | 1 | 1 | 0.05 | 1 | ||
| D12A | 1 | 1 | 0.05 | 1 | ||
| V21A | 1 | 1 | 0.05 | 1 | ||
| D49G/Y | 5 | 1 | 0.26 | 1 | ||
| H57D | 1 | 1 | 0.05 | 1 | ||
| W68G/R | 5 | 1 | 0.26 | 1 | ||
| L151W | 1 | 1 | 0.05 | 1 | ||
| Cycloserine | 15 | 0.73 | 0.33 | 0.93 | ||
| alr | L89R | 15 | 0.73 | 0.33 | 0.93 |
a
Isolates were included only if they had both phenotypic and genotypic resistance predictions. For each mutation, we show the frequency of the mutation in the data set, positive predictive value (PPV), sensitivity, and specificity for predicting phenotypic resistance. Mutations are either listed as specific changes or as any loss-of-function (LOF) mutation, including nonsense mutations and frameshifts.