P1497: MITAPIVAT IMPROVES IRON OVERLOAD IN PATIENTS WITH PYRUVATE KINASE DEFICIENCY WHO ARE REGULARLY TRANSFUSED
Notice bibliographique
Résumé
Topic: 29. Iron metabolism, deficiency and overload Background: Iron overload is highly prevalent in patients (pts) with pyruvate kinase (PK) deficiency, regardless of transfusion status, and can lead to serious complications including organ damage. Regular transfusions further add to the burden of iron overload, negatively impacting pts’ quality of life and healthcare costs. Mitapivat is a first-in-class, oral, allosteric activator of PK, approved by the US Food and Drug Administration for the treatment of hemolytic anemia in adults with PK deficiency and by the European Medicines Agency for the treatment of PK deficiency in adults. Previously reported data from ACTIVATE (NCT03548220) and its long-term extension (LTE; NCT03853798) showed that mitapivat improved iron overload in adults with PK deficiency who were not regularly transfused. Aims: Present long-term data from ACTIVATE-T and its LTE on the impact of continued mitapivat treatment on iron overload, as measured by liver iron concentration (LIC) by magnetic resonance imaging (MRI), in pts with PK deficiency who were regularly transfused and classified as achieving transfusion-reduction response (TRR) or transfusion-free status in ACTIVATE-T. Methods: ACTIVATE-T was a phase 3, global, single-arm study of mitapivat in adult pts with PK deficiency who were regularly transfused (≥6 episodes in the previous year). Pts who demonstrated a clinical benefit from mitapivat in the fixed-dose period of ACTIVATE-T, in the opinion of the investigator, were permitted to continue to the LTE. This analysis included pts who achieved a TRR (defined as ≥33% reduction in red blood cell units transfused during the fixed-dose period vs historical control) and pts who achieved transfusion-free status were a subset of the pts who achieved TRR. Change from baseline (BL) in LIC by MRI up to Week (Wk) 136 and changes in chelation therapy were assessed. Data were reported as of 27Mar2022 of the LTE study. Results: In ACTIVATE-T, 37% (10/27) of pts achieved a TRR, of which 6 pts achieved transfusion-free status. Clinically meaningful improvements over time in LIC were observed in these pts. Median (Q1, Q3) LIC decreases from BL to Wk 136 of mitapivat treatment were –2.5 (–4.4, –0.6) mg Fe/g dry weight (dw) and –4.4 (–13.7, –0.6) mg Fe/g dw for the pts who achieved TRR and the subset of pts who achieved transfusion-free status, respectively (Figure). Both (2/2) pts who achieved transfusion-free status, and 3 out of 4 pts who achieved TRR, with BL LIC ≥5 mg Fe/g dw had decreases to <5 mg Fe/g dw after treatment with mitapivat, which occurred between wks 112 and 136. Of the 6 pts who achieved transfusion-free status, 4 were receiving iron chelation at the start of mitapivat treatment. Of these 4 pts, 3 discontinued chelation, and 1 remained at a stable dose without increase. In 2 of the 3 pts who discontinued chelation, LIC continued to improve over time on mitapivat after chelation had been stopped. Furthermore, 2 of the 6 pts who achieved transfusion-free status did not receive chelation therapy and had improved LIC after starting mitapivat. Summary/Conclusion: Treatment with mitapivat improved iron overload in adults with PK deficiency who are regularly transfused and may therefore provide additional clinical benefits to those suffering from this condition. Importantly, pts that were chelation naïve as well as pts that discontinued chelation while on mitapivat continued to show meaningful improvements in LIC, suggesting that mitapivat’s beneficial effects on iron overload may occur independently from chelation therapy.Keywords: Iron overload, Iron chelation, Pyruvate kinase deficiency, Transfusion
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
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| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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.
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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 tête enseignante, pas un consensus.
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