S823 The Impact of Treatment Switch Among Prevalent Patients With Crohn’s Disease Treated With a First-Line Biologic: A U.S. Retrospective Claims Database Study
Notice bibliographique
Résumé
Introduction: Treatment switching often occurs with biologic use among patients with Crohn’s disease (CD) and has been associated with worsened clinical symptoms and functional impairment. However, little is known about its impact on healthcare resource utilization (HRU) and costs. This study assessed the economic burden associated with treatment switching among adults with CD in the United States (US). Methods: Data from the IBM® MarketScan® Commercial Subset (10/01/2015-03/31/2020) were used to identify adult patients newly diagnosed with CD (at least 2 CD diagnoses at least 30 days apart) and that were treated with a first line biologic (prescription fill/injection) on or after their CD diagnosis. The index date was defined as the date of the first line biologic. Patients were classified into the switchers or non-switchers cohort based on whether or not they switched to another biologic or 5-aminosalicylic acid or immunomodulator during the 12-month study period after the index date. Mean time to treatment switch was estimated using Kaplan-Meier analyses. All-cause HRU and healthcare costs (2020 USD) during the study period were described and compared (unadjusted) overall and for the 2 cohorts. Results: Among 4,006 patients included in the study, 640 were switchers and 3,366 were non-switchers. Overall, mean age was 39.5 years and 50.9% were female. Rates of treatment switch were 7.1% at 6 months and 16.0% at 12 months (Figure). Additionally, rates of prolonged corticosteroid use (at least 90 days) was higher in switchers compared to non-switchers (31.6% vs 8.2%; p< 0.01). Switchers also had higher rates of inpatient admissions (25.9% vs 12.6%; p< 0.01), emergency department visits (41.6% vs 35.4%; p< 0.01), and number of outpatient visits (22.8 vs 17.0; p< 0.01) compared to non-switchers (Table). Similarly to HRU, total all-cause healthcare costs were higher among switchers than non-switchers ($95,689 vs $81,027; p< 0.01), which was mainly driven by higher medical costs ($24,135 vs $14,416; p< 0.01). Among age groups, switchers 30-39 years incurred the highest total cost ($100,676 vs 78,265, p< 0.01). Conclusion: In this real-world study, patients with CD who switched biologic treatments, which is a marker of inadequate treatment, incurred significantly higher HRU and healthcare costs. These findings suggest a potential unmet need with current treatment options and highlight the impact of switching biologics on the economic burden of patients with CD.Figure 1.: Kaplan-Meier analysis for time to switch CI: confidence interval Table 1. - All-cause HRU and healthcare costs incurred during the study period Number of patients, N Switchers (N=640) Non-switchers (N=3,366) All-cause HRU, N (%) Inpatient admission 166 (25.9%) 423 (12.6%) Inpatient days, mean ± SD [median] 2.5 ± 6.4 [0.0] 1.1 ± 4.6 [0.0] Emergency department visits 266 (41.6%) 1,192 (35.4%) Days with outpatient visits 639 (99.8%) 3,331 (99.0%) Number of days with outpatient visits, mean ± SD [median] 22.8 ± 17.0 [19.0] 17.0 ± 16.3 [13.0] Healthcare costs (2020 USD), mean ± SD [median] Total (medical + pharmacy) $95,689 ± $52,295 [$85,713] $81,027 ± $50,743 [$72,464] Medical $24,135 ± $39,519 [$9,434] $14,416 ± $33,575 [$4,847] Inpatient $11,491 ± $31,526 [$0] $5,279 ± $22,861 [$0] Outpatient $10,906 ± $17,172 [$5,956] $7,909 ± $17,732 [$3,687] Emergency department $1,738 ± $4,666 [$0] $1,228 ± $5,330 [$0] Pharmacy (including biologics) $71,554 ± $35,174 [$66,355] $66,611 ± $39,793 [$62,937] HRU: healthcare resource utilization; SD: standard deviation; USD: United States dollar.
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».