PS1244 REAL‐WORLD HEALTHCARE RESOURCE UTILIZATION (HRU) OF PATIENTS DIAGNOSED WITH CLASSICAL HODGKIN LYMPHOMA (CHL) TREATED WITH ANTI‐PD1 CHECKPOINT INHIBITORS IN THE UNITED STATES (US)
Notice bibliographique
Résumé
Background: cHL patients with relapsed/refractory (RR) disease who relapse after or are ineligible for autologous stem cell transplantation have a poor prognosis. Recently, the anti‐PD1 monoclonal antibodies nivolumab and pembrolizumab were approved by the FDA (May 2016 and March 2017, respectively) as treatment options for RR cHL patients. Aims: This study aims to describe real‐world patient characteristics and HRU (hospitalizations and outpatient [OP] visits) among patients with RR cHL receiving pembrolizumab or nivolumab in the US. Methods: A retrospective database analysis was conducted using Symphony Health's Patient Integrated Dataverse ® (07/2014–06/2018). The date of the first dispensing or administration of pembrolizumab or nivolumab was termed the index date. Patients with ≥12 months of clinical activity prior to the index date, ≥1 hospitalization or ≥2 OP encounters with an ICD‐9/10‐CM diagnosis of cHL prior to the index date, no diagnosis of nodular lymphocyte‐predominant HL, and ≥18 years of age were included. Baseline patient characteristics were assessed in the 12 months prior to the index date. HRU was evaluated over the entire follow‐up period, from the index date to the end of clinical activity or data availability. Crude rates of hospitalizations and OP visits were calculated as number of events divided by person‐time of observation, expressed as rate per person per year (PPPY), to account for varying durations of observation across patients. Mean and median hospital length of stay (LOS) were reported. Results: Among cHL patients, 92 received pembrolizumab and 225 received nivolumab. The mean age was 59 and 53 years among those treated with pembrolizumab and nivolumab, of whom 40% and 44% were female, respectively. Corresponding median (IQR) follow‐up periods were 214 (92–325) and 249 (126–443) days. Mean baseline Quan‐Charlson comorbidity index score for pembrolizumab and nivolumab patients was 4.9 and 4.0; 18% and 14% had depressive disorders, and 16% and 8% had substance‐related and addictive disorders, respectively. Of pembrolizumab patients, 7% had received nivolumab and 26% brentuximab vedotin (BV). Of nivolumab patients, none had received pembrolizumab, 40% received BV, and 2% received ibrutinib. Pembrolizumab and nivolumab patients had an average of 1.5 and 1.4 all‐cause hospitalizations during the baseline period, respectively, while the corresponding rate of all‐cause hospitalizations during follow‐up was 0.9 and 1.3 PPPY with an associated mean [median] LOS of 3.1 [1.5] and 4.2 [2] days ( Figure ). The rate of all‐cause OP visits during follow‐up was 36.4 and 35.5 PPPY for pembrolizumab and nivolumab patients, respectively. The rate of cHL‐related hospitalizations during follow‐up was 0.1 PPPY for pembrolizumab patients, with a mean [median] LOS of 4.7 [1] days, and 0.4 PPPY for nivolumab patients, with a mean [median] LOS of 7.4 [4] days. Summary/Conclusion: This real‐world descriptive study attempts to provide an early assessment of nivolumab and pembrolizumab user profiles and resource utilization outcomes since their market approval in the US. cHL patients treated with pembrolizumab are found to be older at treatment initiation, with greater comorbidity burden and baseline hospitalization rates than the nivolumab group. 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) | 0,001 | 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 ».