Discrepancy Among Observational Studies: Example of Naproxen- Associated Adverse Events
Notice bibliographique
Résumé
BACKGROUND: Observational studies assessing the cardiovascular adverse effect of naproxen have had conflicting results. It is not clear whether variation in population characteristics between studies may explain some of this discrepancy. OBJECTIVE: To determine whether changes in patient characteristics of naproxen users occurred between 1999 and 2004 in Québec, Canada and to examine whether these temporal changes were accompanied by changes in estimates of naproxen-related hospitalizations for gastrointestinal (GI) ulcers and myocardial infarction, using provincial health services administrative databases. METHODS: Demographic, pharmaceutical and physician billing records of patients 65 years and older, who received naproxen or acetaminophen prescriptions between 1999 and 2004 were used. Two identical cohort studies, labeled Study 1 and Study 2 were conducted and their results were compared. One study was confined to the time period 1999-2001 and the other to 2002-2004. Patient characteristics at index date (the date of the first naproxen or acetaminophen prescription during the corresponding period) were compared between the study cohorts in naproxen and acetaminophen users, respectively, and within each study cohort between naproxen and acetaminophen users, using logistic regression models. Cox regression models with time dependent exposure were used to assess the association between naproxen vs acetaminophen and hospitalizations for GI events or AMI, respectively within each study. Results were then compared between the two studies. RESULTS: Study 1 (1999-2001) cohort included 240,568 patients (205,238 acetaminophen and 35,330 naproxen) and Study 2 (2002-2004) cohort included 213,802 patients (193,918 acetaminophen and 19,884 naproxen). Patient characteristics of naproxen and acetaminophen users differed between the two studies. Naproxen users in Study 2 vs Study 1 were slightly younger, less likely to be females, less likely to have concomitant GI disease, less likely to have osteoarthritis and other co-morbidities and more likely to have used proton pump inhibitors, antihypertensive agents, anticoagulants, clopidogrel and aspirin. In general, similar changes in patient characteristics were observed in acetaminophen users between the two study cohorts. Compared to acetaminophen (without aspirin), the estimates of the GI risks with naproxen whether, used with or without aspirin, were significantly higher in Study 2 vs Study 1 [Hazard Ratio (HR) (95% CI): 4.94 (3.48, 7.02)] vs [2.22 (1.62, 3.06)], naproxen with aspirin [4.94 (2.93, 8.33) vs 2.47 (1.48, 4.12)], and acetaminophen and aspirin: [2.31 (1.89, 2.82) vs 1.46 (1.20, 1.77)]. The estimate of the AMI risk with naproxen also seemed to be higher in Study 2 vs Study 1, however the increase was not statistically significant [HR (95% CI) in the naproxen group: 1.18 (0.83, 1.67) in Study 1 vs 0.94 (0.70, 1.25) in Study 2], naproxen with aspirin. [1.44 (0.95, 2.18) vs 1.05 (0.68, 1.61)]; and acetaminophen and aspirin. 1.15 (1.01, 1.30) vs 1.10 (0.97, 1.26). CONCLUSION: Variation in patient characteristics in naproxen users was observed between 1999 and 2004. This variation was likely to be accompanied by a variation in patient pre-disposition to GI events that may explain the increase in estimates of naproxen-related GI adverse events observed during this period.
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 | 0,002 | 0,001 |
| 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 ».