Consider If You Will: Proton Pump Inhibitors in Children, Infections, and Precision Medicine
Notice bibliographique
Résumé
The discovery in 1975 that timoprazole was highly effective in reducing gastric acid secretion followed by the creation of a derivative, omeprazole, in 1979 marked the introduction of a new class of drugs: the proton pump inhibitors (PPIs). Since the entry of omeprazole onto the market in 1988, PPIs have become among the most widely prescribed drugs in the world. This is not unique to adults; over the past decade, there has been a significant increase in the rate of use of PPIs in children.1As PPIs have been increasingly used, concerns have surfaced as to their safety and efficacy.2 In this issue of Pediatrics, Bernal et al3 explore an important 1 of these concerns: infection rate. Their study, “CYP2C19 Phenotype and Proton Pump Inhibitor–Associated Infections,” revealed that among a group of 670 children treated with a PPI, the risk for infection was correlated with a normal or wild type metabolizer phenotype, whereas those children with more rapid metabolism had a lower risk of infection.These are highly relevant findings for a number of reasons. First, although the authors acknowledge their limitations, it is a large and well conducted study with compelling conclusions. There have been a number of studies suggesting an association between PPI use and infection, adding to the hypothesis that low gastric pH is protective against infection. The authors of this study avoid many of the confounding issues in previous work by looking within a group of children treated with PPIs to determine if there may be subpopulations at a higher infection risk.Second, their study highlights the relevance of drug metabolism. In the case of the PPIs, the primary route of metabolism is via the polymorphic phase I enzyme CYP2C19. It has been known for some time that CYP2C19 is expressed in a number of distinct phenotypes ranging from poor to normal to ultrarapid metabolizers related to genetically controlled variations in enzyme expression.4,5 Thus, rapid and ultrarapid metabolizers (the group that would clear the drug most effectively and would presumably have the least efficacy in terms of suppression of acid production) were also the groups that had the lowest rate of infections. Of note, these are not insignificant groups because they in fact accounted for one-third of the patients, whereas the normal metabolizers (who had a higher infection rate) made up 40% of the patients.This in turn raises 2 important considerations. The first relates to drug use. As noted previously, PPIs are among the most widely used drugs in the world. When weighing the therapeutic value of a PPI against its risks, one must consider the fact of an increase in infection among children who metabolize the drug via the normal metabolizer phenotype. This becomes especially relevant for patients who are more medically fragile and comorbid, such as those with immunodeficiency or chronic disease for whom an increased risk of infection may be highly consequential, changing the risk/benefit assessment when deciding to use, or not to use, a PPI.The second is the potential for risk prediction and dose adjustment based on genotyping, the application of precision medicine to the therapy of gastrointestinal disease in children. It has been suggested that genotyping may be useful when planning PPI therapy, especially on a chronic basis. This study provides evidence that can be used to develop clinical guidelines as to when and in which patients genotyping should be conducted. In addition, it provides guidance to clinicians on how to adjust therapy on the basis of specific genotyping.A final implication of these findings is the power of linking large administrative databases to clinical outcomes and biological variables such as genotype. This study was possible because of a thoughtful linkage developed between the Vanderbilt University Medical Center’s electronic medical record and DNA biorepository. As therapy for children becomes increasingly complex (with the revolution in biological, cell, and factor therapy already well underway), these approaches will be increasingly important for early detection of signals to identify specific groups of patients for whom therapy may be especially beneficial or especially harmful.Overall, Bernal et al3 provide important evidence to a new paradigm in which genotyping can enhance clinical decision-making. Their study not only empowers us to improve our prescribing practices but also informs future researchers exploring this paradigm shift in other clinical contexts.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,004 | 0,006 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,008 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».