P397 Advanced therapy persistence and need for dose optimisation in a cohort of Inflammatory Bowel Disease patients in Argentina: a real-world evidence multicenter study (REMAR study)
Notice bibliographique
Résumé
Abstract Background Treatment persistence, as well as time to dose optimisation, can be a proxy for a drug’s real-world therapeutic benefit. We sought to describe treatment persistence of biologics or small molecules in inflammatory bowel disease (IBD) patients and need for optimisation in patients with IBD in Argentina and their potential predictors. Methods A retrospective cohort study involving 13 hospitals from Argentina was undertaken. Adult patients with a diagnosis of Crohn’s disease (CD) or ulcerative colitis (UC) who received therapy with a biologic or a small molecule were included. Initiation date was registered for every therapy each patient received; in addition, treatment finalization as well as need for optimisation were registered. Treatment persistence was defined as the time between treatment initiation and treatment finalization, or as time between treatment initiation and last follow-up if patient continued with the treatment. Time to optimisation was defined as the time between treatment initiation and treatment dose optimisation. In patients that received more than one type of advanced therapy, treatment persistence and need for optimisation was analyzed separately for each treatment received. Kaplan-Meier analysis as well as Cox regression model were used to determine predictors of treatment persistence and need for optimisation. Results A total of 403 patients were included; 55.28% had a diagnosis of UC, mean age was 44.57±16 and 47.71% were male. Median time of follow-up was 80 months [IQR 41-152]. Adalimumab was the most frequently used biologic as a first-line treatment for CD and UC (59.78% and 51.39%, respectively), whereas ustekinumab and vedolizumab were the most frequently used agents for CD and UC patients previously exposed to biologics, respectively (41.42% and 36.73%). Median treatment persistence duration was 68 months [IQR 22-146]. History of steroid-dependency [HR 2.87 (1.02-8.12)], CD [0.42 (0.22-0.78]), prior biologic exposure [HR 2.25 (1-5.06)], dose optimisation [HR 2.93 (1.36-6.33)] and need for systemic steroids 6 months from treatment initiation [HR 4.98 (1.57-15.75)] were significant predictors of shorter treatment persistence. Median time to optimisation was 34 months [IQR 9-132]. CD [0.81 (0.55-0.94)], moderate-to-severe endoscopic activity [HR 1.91 (1-3.95)], prior biologic exposure [HR 2.29 (1.27-4.14)] and biologic initiation after 2017 [2.06 (1.09-3.55)] were significant predictors of need for dose optimisation. Conclusion A considerable proportion of IBD patients required dose optimisation or treatment finalization. Lower treatment persistence and time for dose optimisation were observed in UC patients and other factors were identified.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».