Analysis of Real‐World Treatment Patterns and Outcomes Among Patients With Relapsed/Refractory Follicular Lymphoma Including POD24 Patients
Notice bibliographique
Résumé
Introduction: Although follicular lymphoma (FL) is an indolent disease, there is much heterogeneity in outcomes. Patients with early relapsed disease within 24 months (POD24) have been reported to be a poor prognostic subgroup, although this finding has not been confirmed in several recent real-world studies. This study describes treatment patterns, prognostic factors, and outcomes in patients with relapsed/refractory (R/R) FL, including those who progress through multiple lines of therapy (LOTs). Methods: This study was conducted using the COTA database, which is comprised of electronic health records drawn from academic centers (50%) and community practices (50%) in the US. Patients included in this study had a confirmed diagnosis of FL (index date) between 1 January 1990 and 31 December 2022, were ≥18 y of age at index date, were administered treatment for FL, and were followed >3 months after first-line (L) treatment initiation. The utilization of novel treatment options was captured progressively throughout the study period. Patients who progressed from 1L chemoimmunotherapy (CIT) within 24 months were identified as POD24 patients. A landmark approach was taken to assess the overall survival (OS) of the POD24 patients who had at least 24 months of follow-up from 1L CIT versus non-POD24 patients as described in previous studies (Casulo et al., Blood 2022). Patient demographics, treatment patterns, and OS were also assessed by LOT. Results: Overall, 3568 FL patients met inclusion criteria. Among these, 2465 received 1L CIT, with 459 (18.6%) identified as POD24. Of these POD24 patients, 264 had ≥24 months of follow-up from 1L CIT and were included in the landmark analysis. This sub-group of POD24 patients had a median age of 64 y at diagnosis and 86.6% had stage III/IV disease. Non-POD24 patients (n = 2006) had a median age of 61 y at diagnosis and 81.4% had stage III/IV disease. POD24 patients had worse OS (hazard ratio [HR] 2.24; 95% confidence interval [CI] 1.79, 2.80) versus non-POD24 patients. Of the 3568 1L FL patients, 862 continued to 2L, 328 continued to 3L, 146 continued to 4L, and 59 continued to 5L+ treatment. Across all LOTs, the most common therapy was rituximab or obinutuzumab + chemotherapy. The utilization of novel treatments (ie, kinase inhibitors, CAR T-cell therapy, tazemetostat) increased through LOTs, with 6.4% utilization at 3L, 9.6% at 4L, and 20.7% at 5L. Patients who progressed through successive LOTs experienced worsening OS (Figure 1). The research was funded by: This study was funded by Genmab A/S and AbbVie Inc. Keywords: Cancer Health Disparities, Late Effects in Lymphoma Survivors Conflicts of interests pertinent to the abstract. L. H. Sehn Consultant or advisory role: AbbVie, Bayer, BeiGene, BMS/Celgene, Epizyme, Genentech/Roche, Genmab, Incyte, Janssen, Kite/Gilead, Loxo, Miltenyi, MorphoSys, Novartis, Rapt, Regeneron, Takeda A. Wang Employment or leadership position: AbbVie Stock ownership: AbbVie J. Yu Employment or leadership position: AbbVie R. Kamalakar Employment or leadership position: AbbVie K. Sail Employment or leadership position: AbbVie Stock ownership: AbbVie W. Sinai Employment or leadership position: AbbVie Stock ownership: AbbVie D. Arnette Employment or leadership position: AbbVie S. Yang Employment or leadership position: Genmab A. Mutebi Employment or leadership position: Genmab Stock ownership: Genmab F. R. Navarro Employment or leadership position: Genmab G. Salles Consultant or advisory role: AbbVie, Bayer, BeiGene, BMS/Celgene, Epizyme, Genentech/Roche, Genmab, Incyte, Janssen, Kite/Gilead, Loxo, Miltenyi, MorphoSys, Novartis, Rapt, Regeneron, Takeda
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) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 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 ».