Evaluation of Bleeding and Thrombocytopenia in Older Adults with Acute Myeloid Leukemia Treated with Hypomethylating Agents: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
Introduction: Acute myeloid leukemia (AML) is a myeloid malignancy associated with cytopenias and significant morbidity and mortality. Hypomethylating agents (HMA), such as azacitidine and decitabine, form the backbone of outpatient chemotherapy for many patients with AML. Thrombocytopenia, a well-established risk factor for bleeding, is common and related to both underlying disease and as well as treatment. However, the frequency and severity of bleeding, particularly with novel combination therapies, has not been well described (CRD42022339160). Objectives: Our primary objective was to evaluate the incidence and severity of bleeding in patients with AML receiving hypomethylating agents. We also aimed to explore the relationship between bleeding and thrombocytopenia and the use of supportive care strategies to prevent bleeding. Population: Adult patients (age ≥ 18 years) with AML (≥80% of the study population) treated with hypomethylating agents. Outcomes: Our primary outcome was grade 3 or 4 bleeding, defined using National Cancer Institute's Common Toxicity Criteria for Adverse Events (NCI-CTCAE). Secondary outcomes included bleeding of any grade, deaths due to bleeding, grade 3 or 4 thrombocytopenia using NCI-CTCAE, duration of thrombocytopenia, platelet count at time of bleeding, and number of patients who received tranexamic acid to prevent or treat bleeding. Methods: We searched Medline (Ovid), Embase (Ovid), CENTRAL (Cochrane Library) and CINAHL from inception to April 2021 to identify relevant citations of published trials, using individualized systematic search strategies for each database. We included randomized control trials of adults with AML receiving hypomethylating therapy. Studies were included if they evaluated HMA therapy in patients with AML and reported at least one outcome of interest related to bleeding, thrombocytopenia, or supportive measures used. We used Freeman-Tukey transformation to calculate the weighted summary proportion using a random effects model. Results: We included 12 unique trials enrolling 2,105 patients. Azacitidine was studied in 6 trials (n=998 patients), while 5 trials evaluated decitabine (n=580 patients), and 2 trials studied combination hypomethylating agent therapy (HMA and venetoclax) (n=401 patients). The median patient age was 75, and 69% were male. Grade 3 or 4 bleeding occurred in 9% of patients (95% confidence interval (CI) 6 to 12%; n=4 trials; 313 patients). Death due to bleeding was reported in 3% of patients (95% CI 1 to 6%; n=3 trials; 215 patients). Grade 3 or 4 thrombocytopenia occurred in 35% of patients (95% (CI) 26 to 44%; n=11 trials; 1,506 patients). Duration of thrombocytopenia, platelet count at time of bleeding event, and number of patients who received tranexamic acid to prevent or treat bleeding was not reported. Conclusion: The incidence and severity of bleeding and thrombocytopenia in patients with AML treated with hypomethylating agents have not been systematically reported. Further, the relationship between bleeding and thrombocytopenia and the use of supportive care strategies to prevent bleeding were not well characterized. Comprehensive reporting of bleeding risk factors and bleeding events, as well as prophylactic strategies used to prevent bleeding, are needed to inform best practice and optimize supportive care for this high-risk patient population.
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 | 0,006 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,012 | 0,018 |
| Bibliométrie | 0,005 | 0,008 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».