Evaluation of real-world outcomes among CLL patients based on sequencing of BTKi and BCL2i therapies
Notice bibliographique
Résumé
Abstract Background: Current first-line (1L) therapies for chronic lymphocytic leukemia (CLL) consist of Bruton tyrosine kinase inhibitors (BTKi) or B-cell lymphoma 2 inhibitors (BCL2i). However, many patients (pts) will require multiple therapies over the course of their treatment and often switch from one of the aforementioned drug classes into the other in second-line (2L). There is limited real-world evidence assessing the impact on clinical outcomes after switching drug classes in pts with relapsed or refractory CLL. This study evaluates real-world time to second subsequent treatment (TSST) among pts with prior BTKi or BCL2i that switched drug classes from the 1L to 2L setting. Methods: The IntegraConnect PrecisionQ de-identified electronic health record database was used to identify pts with CLL that either received BLC2i in the 2L setting after receiving BTKi or received BTKi in the 2L setting after receiving BLC2i. Analyses were restricted to pts that initiated 1L from 4/11/2016 to 1/7/2025. Regimens may consist of multiple drugs, such as the addition of anti-CD20 therapy, but pts that received any combination of BTKi and BLC2i in the 1L or 2L setting were excluded from the analysis. The index date was the initiation of 1L therapy. Descriptive statistics were used to summarize demographic and clinical characteristics by treatment group, including age at index date, race, and ECOG performance status. TSST was defined as the time to third-line (3L) regimen or death from index. Pts that were alive at the end of the observation period that did not initiate a 3L regimen were censored. TSST was analyzed using Kaplan-Meier (KM) survival curves, with median estimates reported. Multivariable Cox proportional hazards regression was used to evaluate the impact of treatment switching on TSST, adjusting for the aforementioned demographic and clinical covariates. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) are presented. Results: A total of 852pts met study eligibility, of whom 703 (83%) received BCL2i as 2L therapy after BTKi and 149 (17%) that received BTKi as 2L therapy after BCL2i. There were no significant differences in the distribution of demographic and clinical factors between groups. At the univariable level, there was no difference observed in TSST between treatment groups (Median TSST, BCL2i to BTKi: 66 months, BTKi to BCL2i: 71months, logrank P=0.69). Additionally, there was no significant difference observed in TSST between groups after adjustment for demographic and clinical covariates (HR: 0.97; 95% CI: 0.71–1.33; p=0.86). Conclusions: This study evaluated treatment outcomes in TSST between pts with CLL that had switched drug classes from the 1L to 2L setting (BTKi to BCL2i and BCL2i to BTKi). Overall, no significant differences in TSST were observed. Treatment sequencing considerations are complex, and considerations should be made based on individual pt risk profiles.
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 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 | 0,004 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 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 ».