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Enregistrement W4389229390 · doi:10.1182/blood-2023-178660

Real-World Patterns of Targeted Therapy Use in Chronic Lymphocytic Leukemia and Small Lymphocytic Lymphoma in the United States: A Longitudinal Study

2023· article· en· W4389229390 sur OpenAlexaff
Enrico De Nigris, Wendy Y. Cheng, Eric Sarpong, Siyang Leng, Mohammed Z.H. Farooqui, Uchechukwu Samuel Agu, Maryaline Catillon, Dominique Lejeune, Nathaniel Downes, Lisa Matay, Mei Sheng Duh, Scott F. Huntington

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Lymphocytic Leukemia Research
Établissements canadiensGroup for Research in Decision Analysis
Organismes subventionnairesnon disponible
Mots-clésIbrutinibChronic lymphocytic leukemiaDiscontinuationMedicineLymphomaOncologyInternal medicineLeukemia

Résumé

récupéré en direct d'OpenAlex

Introduction: Clinical guidelines and practice have shifted toward increasing use of novel Bruton's tyrosine kinase inhibitors (BTKi) or B-cell lymphoma 2 inhibitor (BCL2i) for treatment of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). To highlight recent changes in clinical practice, this study evaluated real-world treatment sequences, with a focus on sequential novel targeted therapy, among patients with CLL/SLL in the US over time. Methods: Adult patients with ≥2 medical claims for CLL/SLL diagnosis on distinct days and ≥1 claim for CLL/SLL therapy were identified in the Optum Clinformatics DataMart database (2014-2021). The index date was the date of initiation of the first observed line of therapy (LOT) following the first observed CLL/SLL diagnosis. The observation period spanned from index to the earliest of end of eligibility, data availability, or death. LOTs were identified using a claims-based algorithm adapted from published literature during the observation period. Each LOT spanned from the initiation of a new agent to discontinuation of all agents in the LOT (i.e., 90-day gap without any dispensing), a switch to another agent, or the addition of a new agent. The proportion of patients receiving sequential targeted therapy in the first 2 LOTs (i.e., BTKi/BCL2i as first-line [1L] and second-line [2L] treatments in any order) was described. For sequential BTKi in 1L and 2L, treatments were also described by agent (i.e., ibrutinib, acalabrutinib, zanubrutinib, and combinations thereof). To assess longitudinal patterns, Sankey plots were created for 2 temporal data cohorts: patients with a 1L in 2014-2017 and patients with a 1L in 2018-2021. Results: We identified 7,146 eligible patients, 40.6% female, median age 73 years, with a median follow-up of 2 years after 1L initiation. The most common 1L treatment was BTKi (36.8%), then chemoimmunotherapy (CIT; 27.4%), CD20 (22.2%), chemotherapy (7.6%), and BCL2i (5.4%). In the first 2 LOTs, 22.3% of patients had sequential targeted therapy, comprising 70.0% BTKi→BTKi (i.e., BTKi retreated), 23.8% BTKi→BCL2i, 3.6% BCL2i→BCL2i, and 2.6% BCL2i→BTKi. The most common BTKi sequences by agent were ibrutinib→ibrutinib (61.6%) and ibrutinib→acalabrutinib (28.4%). Among patients with a 1L in 2014-2017 (N=2,612; median follow-up=3 years; Figure A), the most common 1L treatment class was CIT (44.6%), followed by CD20 (25.2%), BTKi (21.7%), chemotherapy (7.6%), and BCL2i (0.3%). For those receiving a 2L treatment (N=905), the 3 most common treatment classes were BTKi (37.6%), CD20 (30.2%), and CIT (17.2%). The proportion of patients receiving sequential targeted therapy in the first 2 LOTs was 11.2%; among these patients, 80.2% had BTKi→BTKi; 17.8% had BTKi→BCL2i; 2.0% had BCL2i→BCL2i; and 0% had BCL2i→BTKi. The most common BTKi sequences by agent were ibrutinib→ibrutinib (81.5%) and ibrutinib→acalabrutinib (17.3%). Among patients with a 1L in 2018-2021 (N=4,534; median follow-up=1 year; Figure B), the most common 1L treatment class was BTKi (45.5%), followed by CD20 (20.4%), CIT (17.5%), BCL2i (8.3%), and chemotherapy (7.6%). For 2L (N=833), the 3 most common treatment classes were BTKi (40.9%), CD20 (24.4%), and BCL2i (14.9%). The proportion of patients receiving sequential targeted therapy in the first 2 LOTs was 34.3%, comprising 66.4% BTKi→BTKi; 25.9% BTKi→BCL2i; 4.2% BCL2i→BCL2i; and 3.5% BCL2i→BTKi). Among those receiving sequential BTKi, the most common sequences by agent were ibrutinib→ibrutinib (53.2%), ibrutinib→acalabrutinib (33.2%), and acalabrutinib→acalabrutinib (5.3%). Conclusions: This longitudinal real-world study found a substantial increase in patients with CLL/SLL receiving targeted therapies in 1L over time. In particular, the proportion receiving BTKi in 1L doubled in 2018-2021 relative to 2014-2017 and accounted for almost half of the recent 1L CLL/SLL initiations. A third of patients with 1L observed in 2018-2021 also received a targeted agent in 2L, relative to about 1 in 10 patients in 2014-2017, with BTKi→BTKi being the most common sequence. Surprisingly, patients who received a BTKi in 1L were more likely to receive a BTKi in 2L than they were to switch to a BCL2i. Future studies should assess clinical outcomes to determine optimal sequences for CLL/SLL as well as the reasons for re-treatment with BTKi.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,053

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,070
Tête enseignante GPT0,326
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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