Off-label use of drugs in the pediatric population: application of the binary logistic regression model
DOI:
https://doi.org/10.5377/ryr.v49i49.8062Keywords:
binary logistic regression; logit model; off-label prescription; medicine; pediatric; El SalvadorAbstract
In the universe of drugs there is the concept of off-label use, or use of drugs outside of the Summary of Product Characteristics (SmPC)/label.
This is the use of drugs under conditions not authorized by the regulatory agency of drugs for commercialization, which is, because these applications have not been subjected to clinical trials of safety and efficacy.
For ethical reasons, among the populations that do not undergo clinical trials, is the pediatric population, therefore, among the most vulnerable when prescribing drugs.
With the application of the binary logistic regression model, we intend to identify those variables that significantly increase the probability of prescribing drugs off-label in this population.
To carry out this study, a survey was passed out to doctors who attend children: pediatricians, family doctors and general practitioners.
As hypothesis, it was stated that most of the weight of the probability of making an off-label use of drugs is due to the lack of knowledge of the drug's Summary of Product Characteristics (SmPC); however, thanks to the application of the binary logistic regression, it has been revealed which are the main predictor variables of the off-label prescription.
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Instituto de Ciencia, Tecnología e Innovación (ICTI)
Reality and Reflection
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