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ABBREVIATIONS. GP, general practitioner; ATC, Anatomic Therapeutic Chemical; FDA, US Food and Drug Administration. Before a drug is allowed on the market, a favorable balance between beneficial and harmful effects [...], Objective. To establish risk factors of unlicensed and off-label drug use by children outside the hospital. Methods. A cross-sectional study based on 66 222 pharmacy dispensing records for the year 2000 was performed in the northern part of the Netherlands. All prescriptions were divided into the following categories: unlicensed (no product license), off-label (licensed drugs used outside the terms of the product license), and on-label (licensed drugs used according to the product license). For identifying possible problem areas, the proportions of unlicensed and off-label drug use were determined per age group (0-1, 2-5, 6-11, or 12-16 years) and per drug group. For all systemic drugs, a logistic regression was done that models the odds of receiving an unlicensed or off-label prescription as a function of several possible risk factors. Results. Unlicensed drug use in Dutch children is the highest among 0 to 1-year-olds, and off-label drug use is the highest among 12- to 16-year-olds. Drug groups with highest percentages of unlicensed and off-label drug use were ophthalmologicals/otologicals (80.7% of all prescriptions in this group), blood and blood-forming organs (mainly vitamin K for breastfed newborns; 75.7%), cardiovascular drugs (74.7%), and dermatologicals (73.3%). Prescriptions by specialists (outpatient), prescriptions for new drugs, prescriptions for drugs with a low use in the pediatric population, and prescriptions for infants were risk factors for using a systemic drug unlicensed or off-label. Conclusion. Efforts to improve pediatric labeling are important and need full support. The present results can be used to focus these efforts. Pediatrics 2003;111:291-295; children, pediatrics, drug utilization, unlicensed, off-label, pharmacy dispensing data.

Purpose: The interpretation of the available studies on adverse drug reactions (ADRs) in children outside the hospital is hampered because none of these studies used a control group. The aim of this study was to describe ADRs in children outside the hospital, controlled for drug use in the paediatric background population., Methods: Using a case-control design, we compared drugs on which a suspected ADR was reported to the Netherlands Pharmacovigilance Centre LAREB, and drugs used in the general paediatric population from the InterAction pharmacy database, both in the year 2001, for children aged 0-16 years., Results: The main findings are that ADRs were disproportionately more often reported on systemic drugs (OR 3.0; [95%CI: 1.9-4.8]), new drugs (2.4; [1.6-2.7]), anti-infective drugs (1.7; [1.1-2.7]) and nervous system drugs (2.1; [1.3-3.5]), whereas unlicensed drugs (0.1; [0.0-0.4]), frequently used drugs (0.3; [0.2-0.5]) and dermatologicals (0.1; [0.0-0.4]) were less likely to be associated with a reported ADR. Overall, the proportion of off-label prescriptions did not differ between drugs suspected of an ADR and drugs used by children in a general population., Conclusions: The pattern of drugs associated with a reported ADR could not be solely explained on the basis of drug utilisation patterns in the general population.

Purpose: Pharmacy-dispensing data are valuable sources of drug information, but the population that is covered by the pharmacies is often difficult to determine. We evaluated two methods using drug utilisation information to estimate the population size: a drug-use-based extrapolation of a known part of the population and a capture-recapture estimation without any prior knowledge of the population., Methods: Using pharmacy-dispensing data of three towns with known populations in the Netherlands, we estimated age-and-sex specific population sizes by extrapolating the proportion of drug-using inhabitants. In addition, we applied two-source and three-source capture-recapture models with all combinations of the following drug groups as different sources: anti-asthmatics, analgesics, antibiotics and anti-histamines., Results: Drug-use-based extrapolation resulted in the best estimates with the least variability. All capture-recapture models provided underestimations of the true population. Three-source capture-recapture resulted in better average estimates than two-source capture-recapture, but also had more variability., Conclusions: If a part of the population is known, and if there is reason to assume that drug utilisation patterns do not vary within the region, it is best to use drug-use-based extrapolation. In all other situations capture-recapture may be considered, with as main limitation that we found all models to underestimate the population considerably.