Sample size was determined on the basis of a predicted OR of 3, with a desired power of 80% and a of 0.05. It was estimated that 100 controls and 50 cases (2:1 ratio) would be required. However, because of difficulty in locating an adequate number of controls, the ratio of cases to controls was changed to 1:1, which resulted in a new estimated sample size of 64 patients per group.

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A retrospective unmatched case—control study was conducted to examine vancomycin dosing frequency as a function of age. The study was conducted at St Paul’s Hospital, a 520-bed acute care teaching hospital located in downtown Vancouver. The pharmacy’s computer system was used to identify patients admitted to the hospital between October 2002 and August 2006 for whom vancomycin was prescribed. Candidate charts were then screened for inclusion and exclusion criteria. For patients with multiple eligible admissions, only the most recent admission was included in the study.

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INTRODUCTION

Vancomycin is the drug of choice for hospital inpatients with severe methicillin-resistant Staphylococcus aureus (MRSA) infections. Although vancomycin is an effective bactericidal agent, literature reports of antibiotic failure with this drug are relatively common. Efforts to minimize the risk of antibiotic failure have led to a focus on how best to opti­mize vancomycin pharmacokinetics.
The predose level of vancomycin in the serum is believed to be the most relevant clinically measurable pharmacokinetic parameter because the killing of susceptible organisms by this drug is time-dependent. As such, the bactericidal effect is related to the time above the minimum inhibitory concentra­tion (MIC). Although target predose serum levels have tradi­tionally been 5—15 mg/L, there has been a trend among clini­cians and in guidelines to target higher predose levels. For example, higher levels (15—20 mg/L) and more frequent dosing for patients with normal renal function were endorsed by the recent guidelines of the Infectious Diseases Society of America.

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Clinical Implications

It is difficult to draw conclusions from the limited- sampling strategies that have been described in the literature to date, given their methodologic flaws and limitations. As well, discrepancies in results between studies may be attributable to the differences between the patient subpopulations being studied. For example, in addition to pathophysiologic parameters (e.g., age, sex, disease states), results for limited- sampling strategies may vary according to dosing schedules, drug bioavailability, and other pharmacokinetic parameters such as elimination half-life. More importantly, there is a lack of evidence supporting the need for therapeutic drug monitoring for the majority of anti-infectives for which limited-sampling strategies have been developed. In other words, even if clinical efficacy and AUC are related, a limited-sampling strategy may be of limited clinical utility. For example, concentrations of the non-nucleoside reverse transcriptase inhibitors (NNRTIs) nevirapine and efavirenz are not routinely monitored in practice, because clinicians are able to monitor efficacy and toxicity clinically and the evidence related to therapeutic drug monitoring for these agents is conflicting. Therapeutic drug monitoring of the nucleoside reverse transcriptase inhibitors, such as didanosine, stavudine, zidovudine, and lamivudine, is also not routine practice. These agents require intracellular activation, and the intracellular concentration of active drug does not correlate well with the plasma concentration of the parent compound.
Although correlation between pharmacokinetic— pharmacodynamic data and microbiological cure has been demonstrated in vitro and in animal models, there are limited prospective human data correlating pharmacokinetic-pharmaco- dynamic parameters with clinical outcomes. For the fi-lactam anti-infectives, such as ceftazidime and meropenem, which were included in this review, it appears that time above MIC (t > MIC) is actually the pharmacokinetic-pharmacodynamic parameter that correlates best with microbiological and clinical efficacy. The t > MIC parameter represents the time that the antibiotic concentration remains above a certain threshold concentration, usually a concentration 4 to 5 times greater than the MIC. These data are again based largely on animal and in vitro data. However,, if t > MIC is the parameter that correlates best with efficacy, as has been traditionally thought for the time- dependent fi-lactams, determining the AUC would not be required. Therefore, limited-sampling strategies for the fi-lactam anti-infectives would not be necessary.

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Study Strengths and Limitations

Six studies of limited-sampling strategies were considered to present evidence of the highest quality (level I), describing strategies for didanosine, zidovudine, nevirapine, ciprofloxacin, efavirenz, and nelfinavir). Each study used prospectively collected data and proper validation procedures. All 6 studies randomized pharmacokinetic data into index and validation groups, and 5 of the studies clearly randomized the pharmacokinetic data into independent data sets. Each study illustrated the potential utility of limited- sampling strategies by requiring only 1 or 2 blood samples to predict AUC, with minimal bias and relatively good precision. The level I studies of didanosine and zidovudine also provided 1-sample limited-sampling strategies to predict a second pharmacokinetic parameter, maximum drug concentration.

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Thirty-four studies met the initial inclusion criteria. Fourteen of these studies were excluded: 4 were conducted in healthy volunteers, 1 involved volunteers with cystic fibrosis who did not have an active infection, 8 did not suggest sampling times, and 2 studied previously validated limited-sampling strategies in new populations. Summarizes the characteristics of the included studies according to their levels of evidence. The following information was extracted from each study: level of evidence, the anti- infective agent, the population for derivation of the limited- sampling strategy, the sampling times investigated, the suggested timed samples, the equation(s) for the limited-sampling strategy, r (the correlation coefficient) or r2, the percent bias for the validation group, the percent precision, and additional comments.

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The PubMed (January 1966 to December 2008) and EMBASE (January 1980 to December 2008) databases were searched to identify potential studies for review. The following search terms were used: “anti-infective agents”, “limited sampling”, “optimal sampling”, “sparse sampling”, “AUC monitoring”, “abbreviated AUC”, “abbreviated sampling”, and “Bayesian”. The reference lists of retrieved articles were also searched manually.

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