One-year risk of serious infection in patients treated with certolizumab pegol as compared with other TNF inhibitors in a real-world setting: data from a national U.S. rheumatoid arthritis registry
Notice bibliographique
Résumé
BACKGROUND: Registry studies provide a valuable source of comparative safety data for tumor necrosis factor inhibitors (TNFi) used in rheumatoid arthritis (RA), but they are subject to channeling bias. Comparing safety outcomes without accounting for channeling bias can lead to inaccurate comparisons between TNFi prescribed at different stages of the disease. In the present study, we examined the incidence of serious infection and other adverse events during certolizumab pegol (CZP) use vs other TNFi in a U.S. RA cohort before and after using a methodological approach to minimize channeling bias. METHODS: Patients with RA enrolled in the Corrona registry, aged ≥ 18 years, initiating CZP or other TNFi (etanercept, adalimumab, golimumab, or infliximab) after May 1, 2009 (n = 6215 initiations), were followed for ≤ 12 months. A propensity score (PS) model was used to control for baseline characteristics associated with the probability of receiving CZP vs other TNFi. Incidence rate ratios (IRRs) of serious infectious events (SIEs), malignancies, and cardiovascular events (CVEs) in the CZP group vs other TNFi group were calculated with 95% CIs, before and after PS matching. RESULTS: Patients were more likely to initiate CZP later in the course of therapy than those initiating other TNFi. CZP initiators (n = 975) were older and had longer disease duration, more active disease, and greater disability than other TNFi initiators (n = 5240). After PS matching, there were no clinically important differences between CZP (n = 952) and other TNFi (n = 952). Before PS matching, CZP was associated with a greater incidence of SIEs (IRR 1.53 [95% CI 1.13, 2.05]). The risk of SIEs was not different between groups after PS matching (IRR 1.26 [95% CI 0.84, 1.90]). The 95% CI of the IRRs for malignancies or CVEs included unity, regardless of PS matching, suggesting no difference in risk between CZP and other TNFi. CONCLUSIONS: After using PS matching to minimize channeling bias and compare patients with a similar likelihood of receiving CZP or other TNFi, the 1-year risk of SIEs, malignancies, and CVEs was not distinguishable between the two groups.
Conservé avec la notice de tri, où il sert de preuve aux étiquettes ci-dessus.
Comment cette classification a été obtenuedéplier
Le tri à trois modèles
les 5 600 travaux triés →Les trois modèles l'ont jugé hors champ.
Registry comparison of infection risk across TNF inhibitors that applies propensity matching to reduce channeling bias; bias adjustment is used as a tool and the knowledge produced is about drug safety.
The registry study estimates medication safety in rheumatoid arthritis patients rather than studying research practice.
Real-world drug safety comparison in RA; uses propensity methods to answer a clinical question, not to study methods.
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 | 0,007 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 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 ».