Pyruvate Kinase Activators in Sickle Cell Anemia: A Systematic Review and Single-Arm Meta-Analysis
Notice bibliographique
Résumé
Introduction Pyruvate kinase (PK) activators, initially developed for patients with pyruvate kinase deficiency, have the potential to increase ATP production and decrease red blood cells' (RBCs) 2,3-diphosphoglycerate (2,3-DPG), which would reduce RBC sickling. Given their potential to address key pathophysiological aspects of sickle cell disease (SCD), PK activators are a promising new therapeutic option. This study aims to comprehensively assess the efficacy of PK activators in changing hemoglobin levels and reducing hemolysis in patients with SCD. Methods We performed a systematic review and meta-analysis of PK activators in patients with SCD. The included studies were clinical trials of adult patients diagnosed with SCD and treated with a PK activator for at least two weeks. In cases of overlapping study populations, we prioritized and included studies with the most extended follow-up and highest patient numbers, excluding duplicated data. We searched PubMed, Embase, and Cochrane databases for studies published up to June 2024. Data were extracted from published reports, and quality assessment was performed per Cochrane recommendations. Mean differences with 95% CI were pooled across trials. The primary endpoint of interest was the change in hemoglobin levels. Secondary endpoints included the mean differences in lactate dehydrogenase (LDH) and absolute reticulocyte count. A statistical analysis of the single-arm meta-analysis was performed using a random-effects model to calculate mean differences (MDs) with 95% confidence intervals (CIs) for continuous outcomes. The software R with the metamean package was used. Heterogeneity was assessed with I² statistics. Results A total of 4 clinical trials were analyzed, comprising 99 patients with SCD receiving PK activators. Three studies administered Mitapivat (n=76), and one administered Etavopivat (n=23). The studies included two Phase 1 trials and two Phase 2 trials. The mean age was 31.3 (±10.2) years, with 42.4% male patients. Among the patients, the majority had the Hb SS genotype, and a high percentage (67% to 86.7%) were concurrently using hydroxyurea. Most studies' data on concurrent hydroxyurea use and Hb SS genotype were available, though one Phase 2 study (n=52) did not report information regarding these factors. The mean baseline hemoglobin was 8.78 (±1.12) g/dL. PK activators were associated with a statistically significant increase in hemoglobin levels, showing a mean difference of 1.15 g/dL (95% CI: 0.99 to 1.32, I² = 0%). Treatment with PK activators statistically significantly reduced serum LDH, showing a mean difference of -83.21 U/L (95% CI -109.23 to -57.20, I²=50%). Additionally, there was a significant reduction in the absolute reticulocyte count, with a mean difference of -62.86 109/L (95% CI: -84.72 to -41.00, I² = 53%). Conclusion Our study demonstrates that PK activators have a promising impact on the management of sickle cell disease (SCD). The data indicate that these medications significantly increase hemoglobin levels and reduce reticulocyte counts and LDH. These findings suggest that PK activators could potentially improve anemia and reduce hemolysis in SCD patients. However, the small sample size, observed heterogeneity, and variations in concurrent hydroxyurea use highlight the need for larger, comparative trials to confirm these findings and assess PK activators relative to existing treatments. Future research should focus on more extensive and homogeneous cohorts to validate these results and investigate long-term outcomes.
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 | 0,013 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,024 | 0,041 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».