Co-Use of Drugs and Herbal Remedies in General Practice and In Vitro Inhibition of CYP3A4, CYP2D6 and P-Glycoprotein by the Common Herb Aloe Vera.
Notice bibliographique
Résumé
There is a widespread use of complementary and alternative medicine (CAM) and herbal remedies in particular in different patients groups, but very few are published about co-use among patients in general practice (GP) and herb-drug combinations at risk. Co-use of herbal remedies and drugs can result in none or server adverse effects. Of this reason, knowledge about the GP patients co-use and research on mechanisms of such interactions is needed.\n\nThe aims of this thesis were divided; 1) To register the co-use of drugs and herbs among GP patients in Norway and the patients communication of such use with health care professionals; 2) To evaluate the interaction potential of one of the commonly used herbs in GPs office, Aloe vera (Aloe barbadensis), on the P-glycoprotein (P-gp) and the cytochrome P-450 (CYP) enzymes, CYP3A4 and CYP2D6.\n\nAmong the 381 patients answering the questionnaire in the GP office, 44% used herbs. The most common herbs were bilberry (41%), green tea (31%), garlic (27%), Aloe vera (26%) and purple coneflower (18%). Almost every third (29%) patient co-used drugs and herbs. They combined 255 different drug-groups and herbs whereas 18 of these were considered to have a clinically relevant interaction potential. Close to 40% of patients on anticoagulants co-used herbs, reporting garlic and bilberry most frequently. Co-users had significantly (p<0.05) increased odds to be female, elderly, use herbs to treat an illness, use two or more herbs and experienced adverse effects of herbal use compared to other GP patients. Co-use was also associated with use of analgesics or dermatological drugs. Only 23% of the GP patients discussed their herb use with a health care professional.\n\nEven though Aloe vera is a well-known, old medicine plant used both in cosmetics and as therapeutics, few or no earlier systematic research on its interaction potential has been investigated when co-used with drugs in vitro. Overall three enzymes accounts for the majority of the pharmacokinetics on the drugs in the market: the efflux-protein P-gp transporting the medicinal drug out of the cell and CYP3A4 and CYP2D6, metabolizing the medicinal drugs to less active components. These enzymes can be influenced by other substances (inhibited or induced) and is therefore important regarding herb-drug interactions.\n\nAloe vera juice (AVJ) did not inhibit P-gp mediated digoxin efflux for the investigated AVJ concentrations in vitro. However, it was shown that both AVJ (10.0 mg/ml) and digoxin (≥3µM) was cytotoxic in large concentrations. Two different AVJs were used in the CYP3A4 and CYP2D6 assays. Both juices inhibited CYP3A4 and CYP2D6 irreversible in vitro, having significant different IC50 values. This can come from different concentrations of active components in the juices. Both IC50 values seems, however, to be too high to be clinical relevant alone. Precautions should although, be made with excessive consumption of AVJ, with poor CYP2D6 activity ("poor metabolisers") or with use of drugs having a narrow therapeutic window.\n\nIt can be concluded that GP patients co-using drugs and herbs and that this use can give clinical relevant interactions (e.g. excessive haemorrhage when co-using garlic and warfarin). Elderly patients are most vulnerable for co-use. One of the common used herbs among GP patients, Aloe vera, was investigated for in vitro pharmacokinetic interactions on the enzymes P-gp, CYP3A4, CYP2D6. Although it was concluded with low possibility of clinical relevant pharmacokinetic interactions co-using Aloe vera and drugs, patients with poor CYP2D6 activity might risk interactions when co-using large quantities of Aloe vera with conventional drugs which is metabolized of CYP2D6 (e.g. codeine). Clinical in vivo studies are needed to reveal any interactions in humans for Aloe vera and other herbs at risk of herb-drug interactions. Until then, the GPs and other health care professionals are advised to ask all patients about herbal use.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».