PB1809 REAL‐WORLD HEALTHCARE RESOURCE UTILIZATION (HRU) AND COSTS OF PRIMARY MEDIASTINAL LARGE B‐CELL LYMPHOMA (PMBCL) PATIENTS INITIATED ON ANTI‐CANCER THERAPIES IN THE UNITED STATES (US)
Notice bibliographique
Résumé
Background: There is limited data describing HRU and treatment costs associated with PMBCL, a rare mature B‐cell neoplasm accounting for 2–4% of all non‐Hodgkin lymphoma. In October 2015, PMBCL administrative claims were differentiated from diffuse large B‐cell lymphoma (DLBCL) with the advent of ICD‐10‐CM disease‐specific codes in the US. In light of this new classification, a more reliable assessment of HRU and costs in patients with PMBCL could be performed. Aims: This study aimed to describe real‐world HRU and costs among patients diagnosed with PMBCL who initiated anti‐cancer therapies using a US claims database. Methods: A retrospective database analysis was conducted using the Optum Clinformatics TM Data Mart database (01/2013–03/2018). Patients who had a first encounter with an ICD‐10‐CM diagnosis for PMBCL (with or without an antecedent ICD‐10‐CM diagnosis of DLBCL/other lymphoma, which may have been assigned before PMBCL confirmation) after October 1 st , 2015 (index date for incident patients) were classified as (1) incident if they had no prior ICD‐9‐CM diagnosis for unspecified PMBCL or DLBCL, or as (2) prevalent if they had a prior ICD‐9‐CM diagnosis for unspecified PMBCL or DLBCL before October 2015 (index date for prevalent patients). Patients ≥18 years of age as of the index date with PMBCL diagnoses on ≥2 medical visits and ≥12 months of continuous enrollment pre‐index date (baseline period) were included. Patients with baseline diagnoses of Hodgkin or follicular lymphoma, or multiple myeloma, were excluded. All‐cause HRU (i.e., inpatient stays, outpatient [OP], emergency room, and other visits), and associated costs, including pharmacy costs, were calculated per patient per year (PPPY). HRU and costs were assessed from the start of the first line (1L) treatment up to the earliest of end of data availability or end of insurance coverage and reported for all treated patients and those treated with R‐CHOP (i.e., the most used 1L treatment). Results: Among 148 PMBCL patients (118 incident; 30 prevalent), median (IQR) age was 66 (42–77) years; ∼60% were female. Incident and prevalent patients had mean Charlson comorbidity index scores of 2.2 and 1.7, respectively. Mean ± SD total healthcare (medical plus pharmacy) costs for all incident PMBCL patients treated and those treated with R‐CHOP were $149,340 ± 117,757 and $129,881 ± 88,637 PPPY, respectively. Corresponding OP costs (including costs of administered therapies) were $90,329 ± 87,548 and $74,063 ± 63,099, and were the main cost driver of total healthcare costs. Mean (± SD) total healthcare costs for all treated prevalent patients ($92,799 ± 106,770) and those treated with R‐CHOP ($97,961 ± 125,702) were lower relative to incident patients; however, the follow‐up periods for prevalent patients (∼2.3 years) were approximately double that of incident patients. A sensitivity analysis restricting patients’ evaluation periods up to 12 months (mean follow‐up periods of 9 months for incident and 12 months for prevalent patients) showed more similar costs findings among incident and prevalent patients (mean ± SD total healthcare costs, all treated patients: $187,241 ± 104,938 and $167,553 ± 75,788, respectively) and highlighted higher costs of care over the first year. Similar trends were found for the associated HRU results (Table). Summary/Conclusion: Overall, this study highlighted the substantial economic burden of patients with PMBCL, particularly within the first year following the initiation of treatment. image
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».