Voriconazole is approved for treating invasive fungal infections. We examined voriconazole exposureresponse relationships for patients from nine published clinical trials. The relationship between the mean voriconazole plasma concentration (C avg ) and clinical response and between the free C avg /MIC ratio versus the clinical response were explored using logistic regression. The impact of covariates on response was also assessed. Monte Carlo simulation was used to estimate the relationship between the trough concentration/MIC ratio and the probability of response. The covariates individually related to response were as follows: study (P < 0.001), therapy (primary/salvage, P < 0.001), primary diagnosis (P < 0.001), race (P ‫؍‬ 0.004), baseline bilirubin (P < 0.001), baseline alkaline phosphatase (P ‫؍‬ 0.014), and pathogen (yeast/mold, P < 0.001). The C avg for 72% of the patients was 0.5 to 5.0 g/ml, with the maximum response rate (74%) at 3.0 to 4.0 g/ml. The C avg showed a nonlinear relationship to response (P < 0.003), with a lower probability at the extremes. For patients with C avg < 0.5 g/ml, the response rate was 57%. The lowest response rate (56%) was seen with a C avg > 5.0 g/ml (18% of patients) and was associated with significantly lower mold infection responses compared to yeasts (P < 0.001) but not with voriconazole toxicity. Higher free C avg /MIC ratios were associated with a progressively higher probability of response. Monte Carlo simulation suggested that a trough/MIC ratio of 2 to 5 is associated with a near-maximal probability of response. The probability of response is lower at the extremes of C avg . Patients with higher free C avg /MIC ratios have a higher probability of clinical response. A trough/MIC ratio of 2 to 5 can be used as a target for therapeutic drug monitoring.

Volume 55, no. 10, p. 4782-4788, 2011. Page 4786: The x axis values for Fig. 2 were incorrect; the figure should appear as shown below. FIG. 2. Binomial data and linear logistic fit for investigator outcome versus the mean voriconazole free drug/MIC ratio for 404 patients. E, Data points separated as clinical success or clinical failure. Curves: ---, spline; --, line of predicted fit; ---, upper and lower 95% confidence intervals. The slope was significant at P ϭ 0.005. Note that the free ratio is 0.4 ϫ the ratio. Calculation: logit (P) ϭ (0.766 ϩ 0.139) ϫ log e free ratio, where P is the probability of response. 5415on May 9, 2018 by guest http://aac.asm.org/ Downloaded from

Voriconazole shows activity, in vitro, similar to that of itraconazole against a wide range of moulds. It is also active against some isolates not susceptible to itraconazole or amphotericin B, but not the Zygomycetes. The relationship between voriconazole MIC and clinical outcome requires further study.

A common but not necessarily logical requirement in drug development is that a 'limit of quantitation' be set for chemical assays and that observations that fall below the limit should not be treated as real data but should be labelled as below the limit and set aside for special treatment. We examine five of seven approaches to analysing such data considered by Beal in 2001, concentrating in particular on two: one that treats the data as a truncated sample and another that treats them as a censored sample. In fact, using a pattern-mixture framework, one can show that the former consists of using the conditional distribution of the 'acceptable values' and the latter adds the information from the marginal mixing distribution. We illustrate these approaches with a real example, concentrating in particular on the two likelihood-based methods, provide various formulae that may be used to compare these and other approaches, check these formulae using simulations and make some recommendations as to which approach one should use.

No abstract