Whether Immunostimulants Are Effective in Susceptible Children Suffering From Recurrent Respiratory Tract Infections: A Modeling Analysis Based on Literature Aggregate Data

This tutorial describes the development of a population pharmacokinetic (Pop PK) analysis guidance within Pfizer, which strives for improved consistency and efficiency, and a more systematic approach to model building. General recommendations from the Pfizer internal guidance and a suggested workflow for Pop PK model building are discussed. A description is also provided for mechanisms by which conflicting opinions were captured and resolved across the organization to arrive at the final guidance. CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e51; doi:10.1038/psp.2013.26; advance online publication 3 July 2013

The Visual Predictive Check (VPC) is a valuable and supportive instrument for evaluating model performance. However in its most commonly applied form, the method largely depends on a subjective comparison of the distribution of the simulated data with the observed data, without explicitly quantifying and relating the information in both. In recent adaptations to the VPC this drawback is taken into consideration by presenting the observed and predicted data as percentiles. In addition, in some of these adaptations the uncertainty in the predictions is represented visually. However, it is not assessed whether the expected random distribution of the observations around the predicted median trend is realised in relation to the number of observations. Moreover the influence of and the information residing in missing data at each time point is not taken into consideration. Therefore, in this investigation the VPC is extended with two methods to support a less subjective and thereby more adequate evaluation of model performance: (i) the Quantified Visual Predictive Check (QVPC) and (ii) the Bootstrap Visual Predictive Check (BVPC). The QVPC presents the distribution of the observations as a percentage, thus regardless the density of the data, above and below the predicted median at each time point, while also visualising the percentage of unavailable data. The BVPC weighs the predicted median against the 5th, 50th and 95th percentiles resulting from a bootstrap of the observed data median at each time point, while accounting for the number and the theoretical position of unavailable data. The proposed extensions to the VPC are illustrated by a pharmacokinetic simulation example and applied to a pharmacodynamic disease progression example.

Drug-related adverse events are an under-appreciated consequence of antibiotic use, and the national magnitude and scope of these events have not been studied. Our objective was to estimate and compare the numbers and rates of emergency department (ED) visits for drug-related adverse events associated with systemic antibiotics in the United States by drug class, individual drug, and event type. We analyzed drug-related adverse events from the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance project (2004-2006) and outpatient prescriptions from national sample surveys of ambulatory care practices, the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey (2004-2005). On the basis of 6614 cases, an estimated 142,505 visits (95% confidence interval [CI], 116,506-168,504 visits) annually were made to US EDs for drug-related adverse events attributable to systemic antibiotics. Antibiotics were implicated in 19.3% of all ED visits for drug-related adverse events. Most ED visits for antibiotic-associated adverse events were for allergic reactions (78.7% of visits; 95% CI, 75.3%-82.1% of visits). One-half of the estimated ED visits were attributable to penicillins (36.9% of visits; 95% CI, 34.7%-39.2% of visits) and cephalosporins (12.2%; 95% CI, 10.9%-13.5%). Among commonly prescribed antibiotics, sulfonamides and clindamycin were associated with the highest rate of ED visits (18.9 ED visits per 10,000 outpatient prescription visits [95% CI, 13.1-24.7 ED visits per 10,000 outpatient prescription visits] and 18.5 ED visits per 10,000 outpatient prescription visits [95% CI, 12.1-25.0 ED visits per 10,000 outpatient prescription visits], respectively). Compared with all other antibiotic classes, sulfonamides were associated with a significantly higher rate of moderate-to-severe allergic reactions (4.3% [95% CI, 2.9%-5.8%] vs. 1.9 % [95% CI, 1.5%-2.3%]), and sulfonamides and fluoroquinolones were associated with a significantly higher rate of neurologic or psychiatric disturbances (1.4% [95% CI, 1.0%-1.7%] vs. 0.5% [95% CI, 0.4%-0.6%]). Antibiotic-associated adverse events lead to many ED visits, and allergic reactions are the most common events. Minimizing unnecessary antibiotic use by even a small percentage could significantly reduce the immediate and direct risks of drug-related adverse events in individual patients.