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Enregistrement W2530252650 · doi:10.1182/blood.v124.21.3344.3344

Comparison of Outcomes in Chronic Lymphocytic Leukemia (CLL) with the Addition of Rituximab to Initial Treatment: A Comparative Effectiveness Analysis in the Province of British Columbia (BC), Canada

2014· article· en· W2530252650 sur OpenAlexaffabout
Lauren J. Lee, Alina S. Gerrie, Hélène Bruyèrè, Tanya L. Gillan, Stephen Huang, Cynthia L. Toze, Khaled M. A. Ramadan

Notice bibliographique

RevueBlood · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Lymphocytic Leukemia Research
Établissements canadiensSt. Paul's HospitalVancouver General HospitalBC Cancer AgencyUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicineChemoimmunotherapyInternal medicineChronic lymphocytic leukemiaRituximabHazard ratioPopulationAlemtuzumabProportional hazards modelCohortOncologyProgression-free survivalFludarabineChemotherapyCyclophosphamideLeukemiaLymphomaConfidence intervalTransplantation

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Clinical trials report that chemoimmunotherapy with rituximab (R) improves overall survival (OS) and progression-free survival in the treatment (tx) of symptomatic CLL patients (pts). R has been available for first-line CLL tx in BC, population 4.5 million, since 2004. We compared clinical outcomes with and without addition of R to chemotherapy in a large unselected provincial cohort of pts treated for CLL, to determine the "real world" effectiveness of addition of R to standard chemotherapy. Methods: Three large provincial databases (db) were used to identify eligible pts: the BC Provincial CLL db, the BC Lymphoid Cancer db, and the Providence Hematology CLL db. All pts who received minimum 1 cycle of first-line tx for confirmed CLL were included. Pts with > 1 hematologic malignancy (n=8) were excluded. Baseline features of pts treated with (+R) or without R (No R) were compared using Chi-squared for categorical and Kruskal-Wallis test for continuous variables. OS was calculated from date of initial tx to date of death from any cause. Treatment-free survival (TFS) was calculated from date of initial tx to date of next tx/death from any cause. Multivariate analysis (MVA) was performed using Cox proportional hazard models to evaluate the effect of R on OS/TFS, after controlling for covariates including age (³60 yrs vs <60 yrs), Rai stage (3-4 vs 0-2), CD38 status (pos vs neg), presence of 17p (17p-) and 11q (11q-) deletions, and first-line tx with purine analogs (PAs). Results: A total of 1784 pts diagnosed with CLL from 1973-2014 were identified, of which 726 pts (41%) received tx in follow-up. Of treated pts, 393 (54%) received R and 333 (46%) received chemotherapy alone. Among the No R group, tx included: chlorambucil 56%; fludarabine (F) 34%; cyclophosphamide (C)-based 8%; cladrabine 2%. Among the +R group, tx included: FR 75%; C-based + R 17%; FCR 7%; chlorambucil + R 1%. 103 pts underwent bone marrow transplant (BMT) during their tx course (19% No R vs 10% +R, P=.002). Median age at diagnosis (dx) and tx between groups were not statistically different (No R vs +R: 60.6 vs 60.8 yrs and 64.7 vs 63.9 yrs, respectively). There were no clinically significant differences in diagnostic parameters including % with elevated LDH, lymphocyte count >20x109/L , Rai stage 3-4. Median follow-up time in survivors was longer in the No R group (13.0 vs 6.8 yrs, P<.001). Among 467 pts with known CD38 status, CD38 pos was more common in +R vs No R groups (47 vs 36%, P=.02). FISH was performed in 586 pts, with no significant differences in abnormalities between tx groups. Poor-risk FISH, 17p- or 11q-, were present in 29% (No R) and 27% (+R). Median time from dx to initial tx was 2.8 yrs (range 0-20.6) in No R vs 2.5 yrs (range 0-22.7) in +R groups (P=.84). OS was longer in the +R cohort (median OS 11.8 vs 7.1 yrs, P<.001), Fig. 1. Significant improvements in OS were also seen in pts <60 yrs of age at tx (median OS 11.3 vs 3.1 yrs, P<.0001), without 17p- (median OS 9.3 vs 5.2 yrs, P<.0001), and treated with PAs (median OS 9.4 vs 6.4 yrs, P=.0001). Median TFS was longer in pts treated with R (3.3 vs 2.3 yrs, P= .004), Fig. 2, and in those without 17p- (median TFS 3.1 vs 1.3 yrs, P<.001). MVA confirmed that the addition of R to chemotherapy remained a strong independent predictor of mortality (HR 0.66, 95% CI: 0.44-0.98, P=.04) and TFS (HR 0.6, 95% CI: 0.46-0.79, P<.001) after controlling for covariates. Other independent predictors of OS included age ³60 yrs (HR 2.77, 95% CI 1.87-4.10, P<.001) and presence of 17p- (HR 1.23, 95% CI 1.62-3.76, P<.001), whereas for TFS, presence of 17p- (HR 2.08, 95% CI: 1.49-2.91, P<.001) and CD38+ (HR 1.32, 95% CI: 1.03-1.68, P=.025) were independent negative predictors. Conclusion: In this large, population based cohort of pts treated for CLL, we confirm that the addition of R to chemoimmunotherapy as initial tx significantly improves OS, resulting in a 44% lower risk of overall mortality (95% CI, 2% to 66%) after controlling for covariates. We have also demonstrated that the addition of R to first-line therapy significantly delays the time to subsequent therapy, a finding not previously reported in a population based setting to our knowledge. This study complements clinical trial [Hallek, Lancet 2010] and US Registry data [Danese, Blood 2011], demonstrating benefit of the addition of R to standard therapy for first-line treatment of CLL and shows the generalizability of such results in a real world setting. Figure 1 Figure 1. Disclosures Gerrie: Roche: Honoraria, Research Funding. Ramadan:Roche: Honoraria, Research Funding.

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)0,007
score de la tête « metaresearch » (Gemma)0,018
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 enseignants0,132
Score d'incertitude au seuil0,265

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,018
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,003
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,018
Tête enseignante GPT0,314
Écart entre enseignants0,297 · 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

Citations1
Publié2014
Routes d'admission2
Résumé présentoui

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