Interacting with drugs used in oncology: an Alberta Cancer Board initiative
Notice bibliographique
Résumé
Objective. The Alberta Cancer Board (ACB) Pharmacy recognized the importance of having a sound knowledge of drug interactions with anti-neoplastic agents. A pharmacy student was given the task of surveying ACB pharmacists for published literature and Internet sources used most often as sources of drug interaction information during medication order review and evaluation of patient profiles. The goal was to extract information from these sources and integrate it into a concise ACB drug interaction database, which lists the actual and potential antineoplastic drug-drug, drug-disease, drug-natural products and drug-food interactions. The antineoplastic agents identified and examined were part of the ACB Out-patient Cancer Drug Benefit Program (OCDBP) (August 2002). Equipped with this information and using their clinical expertise, pharmacists can play an important role in the medical management of patients with cancer. Data sources. The student collected information from literary and remote sources used most often by ACB pharmacists. Study selection. ACB pharmacists were surveyed for published literature and Internet sources that contained drug interaction information on antineoplastics used most often during medication order review, patient counselling sessions and when responding to drug information requests. The contributors of these information sources claim to have reviewed existing references and thus the student relied on the accurate reporting of their findings instead of collecting data from the original works. The drugs reviewed for the purpose of the study were taken from the ACB OCDBP. Data extraction. There was an extensive data collection process. Dorland’s definition of a drug interaction was adopted. The student determined a potential interaction based on the words `may’ or `risk’ found in the statement of the interaction. The student extracted the drug interaction information into tables and a sample of 10 of 87 drugs from the ACB OCDBP are presented in this paper. A complete guide of the ACB drug interaction index can be obtained from the ACB Pharmacy. Data synthesis. Actual and potential antineo-plastic drug-drug, drug-disease, drug-natural products and drug-food interactions are summarized in tables. The information collected was as current as the date that the data were extracted. The determination of clinical significance relies on the expertise of the pharmacist or other healthcare professional. Moreover, the data contained in the tables is representative of the information collected exclusively from sources used most often by ACB pharmacists and therefore is only one source of drug interaction information. Conclusion. An indepth knowledge of actual and potential interactions with antineoplastic agents is critical for pharmacists in the management of patients with cancer. The ACB drug interaction index is an attempt to promote awareness of interactions with antineoplastic drugs and to encourage clinicians to investigate drug interactions during their treatment and management protocols.
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 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 | 0,003 | 0,006 |
| 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 | 0,003 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».