Risk of Major Bleeding with Ibrutinib in Patients with Thrombocytopenia - a Retrospective Single-Center Canadian Study
Notice bibliographique
Résumé
Abstract Introduction: Ibrutinib, an oral Bruton Kinase inhibitor, is a highly effective treatment for patients with chronic lymphocytic leukemia (CLL). Previous studies reported an increased risk of bleeding due to impaired platelet function. Patients with CLL experience significant thrombocytopenia, which increases their risk for bleeding. This population was excluded from major trials and data is lacking to inform management in this setting. Methods: This is a single center retrospective study of all adult patients with CLL who received single agent ibrutinib in London, Ontario, Canada between January 2014 to December 2020. The primary objective was to investigate the risk of major bleeding associated with thrombocytopenia. Secondary objective was to investigate potential predictors of bleeding. Bleeding events were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) grading system. A major bleed was defined as CTCAE grade 3 or higher as well as bleeding in the central nervous system. To assess the effect of independent variables on the outcome of bleeding, univariate analysis using chi square and t-tests was performed. Multivariate analysis was then preformed with the variables that were significant (p<0.05) on univariate analysis, using logistic and cox regression models. Results: A total of 170 patients were included in this study. There were 54 bleeding events documented in 42 patients (24.7 %) of which 19(35 %) were major bleeding occurring in 17 patients. Median time to major bleeding was 2.4 months. Of the patients with major bleeding, 4(21%) were on anticoagulation, 2(10%) were on antiplatelet and 2(10%) were on combined anticoagulation and antiplatelet. There were 8 central nervous system (CNS) bleeding and 2 of them died. The mean platelet (PLT) nadir, defined as lowest PLT count at any point during ibrutinib treatment, was 73 x 10 9/Lin patients with major bleeding compared to 116 x 10 9/L in patients with minor and 91 x 10 9/L in patients with no bleeding events. On the univariate analysis, when compared patients with major bleeding to patients with no bleeding, potential predictors of major bleeding included PLT nadir (p=0.09), haemoglobin (Hb) < 100 g/L at ibrutinib initiation (p=0.027) and anticoagulation (p=0.009). When compared patients with major bleeding to patients with minor or no bleeding, potential predictors of major bleeding included PLT nadir (p=0.045), Hb <100 (p=0.036) and anticoagulation (p=0.06). Grade 3 thrombocytopenia, defined as PLT nadir < 50 at any point during treatment with ibrutinib was not associated with increased risk of major bleeding (p=0.2). To confirm the significance of these variables, multivariate analysis was performed. When compared patients with major bleeding to patients with no bleeding, PLT nadir (OR= 0.9, p=0.008) and anticoagulation (OR=4.02, p=0.001) were confirmed to be the potential predictors of major bleeding. When compared patients with major bleeding to patients with minor or no bleeding, PLT nadir (OR=0.9 p=0.005) and Hb <100 (OR=2.34, p=0.005) were the potential predictors of major bleeding. Conclusions: Although not common, Ibrutinib is associated with increased risk of bleeding and identifying high risk patients is essential to prevent major bleeding events. This retrospective Canadian study was done with the primary objective to assess the association between PLT count and major bleeding in patients on ibrutinib for treatment of CLL. In this analysis patients with major bleeding tend to have lower PLT counts compared to patients with minor or no bleeding, with mean PLT nadir of 73x 10 9/L. However, grade 3 thrombocytopenia (PLT nadir<50) was not associated with increased risk of major bleeding. Other important predictors of increased risk of major bleeding while on ibrutinib include anticoagulation and anemia (Hb <100). Figure 1 Figure 1. Disclosures Louzada: Amgen: Honoraria; Pfizer: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Lam: AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Hoffmann-La Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; SeaGen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Meyers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Johnson & Johnson: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Beigene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees. Phua: Amgen: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; NovoNordisk: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».