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Record W3213000652 · doi:10.1182/blood-2021-147317

Mitapivat Improves Ineffective Erythropoiesis and Reduces Iron Overload in Patients with Pyruvate Kinase Deficiency

2021· article· en· W3213000652 on OpenAlexaff
Eduard J. van Beers, Hanny Al‐Samkari, Rachael F. Grace, Wilma Barcellini, Andreas Glenthoej, Malia P. Judge, Penelope A. Kosinski, Emily Xu, Vanessa Beynon, Bryan McGee, John B. Porter, Kevin H.M. Kuo

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePyruvate kinase deficiencyTransferrin saturationAnemiaIneffective erythropoiesisSoluble transferrin receptorInternal medicineFerritinErythropoiesisHepcidinGastroenterologyIron deficiencyPyruvate kinase

Abstract

fetched live from OpenAlex

Abstract Background: Pyruvate kinase (PK) deficiency is a rare hereditary disease resulting in chronic hemolytic anemia, which is associated with serious complications, including iron overload, regardless of transfusion status. Ineffective erythropoiesis is linked to iron overload in patients (pts) with hemolytic anemias. Mitapivat is a first-in-class, oral, allosteric activator of the red blood cell PK enzyme (PKR) that has demonstrated improvement in hemoglobin (Hb), hemolysis, and transfusion burden in pts with PK deficiency. This analysis assessed the effect of mitapivat on markers of erythropoiesis and iron overload in pts with PK deficiency enrolled in 2 phase 3 studies, ACTIVATE (NCT03548220) and ACTIVATE-T (NCT03559699), and the long-term extension (LTE) study (NCT03853798). Methods: In ACTIVATE (double-blind, placebo-controlled study), 80 pts (age ≥ 18 years [yrs]) with a confirmed diagnosis of PK deficiency who were not regularly transfused (≤ 4 transfusion episodes in the prior yr; none in the prior 3 months) were randomized to receive mitapivat or placebo. In ACTIVATE-T (open-label, single-arm study), 27 pts (age ≥ 18 yrs) with a confirmed diagnosis of PK deficiency who were regularly transfused (≥ 6 transfusion episodes in the prior yr) were treated with mitapivat. Pts who completed either trial (24 weeks [wks] [ACTIVATE], 40 wks [ACTIVATE-T]) were eligible to continue in the LTE. Erythropoiesis markers included erythropoietin (EPO), erythroferrone, reticulocytes, and soluble transferrin receptor (sTfR). Markers of iron overload included hepcidin, iron, transferrin saturation (TSAT), ferritin, and liver iron concentration (LIC) by magnetic resonance imaging (MRI). In the LTE all pts received mitapivat. Pts from ACTIVATE were categorized into either the mitapivat-to-mitapivat arm (M/M) or the placebo-to-mitapivat arm (P/M). The ACTIVATE-T/LTE analysis includes pts who achieved transfusion-free status in ACTIVATE-T. The ACTIVATE/LTE analysis assessed change in markers from baseline (BL) over time in both study arms. Results: Eighty pts were included in the ACTIVATE/LTE analysis (M/M = 40; P/M = 40). Pts in both arms had abnormal BL erythropoiesis markers consistent with underlying ineffective erythropoiesis, and BL abnormal markers of iron overload. In the M/M arm, mean (SD) EPO, erythroferrone, reticulocytes, and sTfR decreased from BL to Wk 24 of mitapivat treatment by -32.9 IU/L (62.47), -9834.9 ng/L (13081.15), -202.0 10 9/L (246.97), and -56.0 nmol/L (82.57), respectively, while they remained stable or increased in the P/M arm on placebo (Figure). Twenty-four wks after starting mitapivat in the LTE (Wk 48 post BL), pts in the P/M arm had comparable beneficial decreases in mean (SD) EPO, erythroferrone, reticulocytes, and sTfR of -11.6 IU/L (30.74), -9246.1 ng/L (8314.17), -283.7 10 9/L (374.27), and -38.7 nmol/L (48.37), respectively. Improvements in hepcidin, iron, TSAT, and LIC were also observed with mitapivat treatment; ferritin remained stable (Table). Mean (SD) hepcidin increased in the M/M arm at Wk 24 and in the P/M arm 24 wks after starting mitapivat (Wk 48 post BL). At Wk 24, mean (SD) iron and TSAT, and median (Q1, Q3) LIC decreased in the M/M arm, while they increased on placebo. In the P/M arm, iron, TSAT, and LIC decreased 24 wks after starting mitapivat (Wk 48 post BL). Transfusion-free responders from ACTIVATE-T (n = 6) also experienced improvements in markers of erythropoiesis and iron overload in the LTE. Conclusions: In addition to improving Hb, hemolysis, and transfusion burden, data from ACTIVATE, ACTIVATE-T, and the LTE study indicate that activation of PKR with mitapivat improves markers of ineffective erythropoiesis and iron homeostasis in PK deficiency, thereby decreasing iron overload in these pts. Mitapivat has the potential to become the first approved therapy in PK deficiency with beneficial effect on iron overload. Figure 1 Figure 1. Disclosures Van Beers: Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; RR Mechatronics: Research Funding; Pfizer: Research Funding. Al-Samkari: Amgen: Research Funding; Argenx: Consultancy; Rigel: Consultancy; Novartis: Consultancy; Dova/Sobi: Consultancy, Research Funding; Agios: Consultancy, Research Funding; Moderna: Consultancy. Grace: Agios: Research Funding; Dova: Membership on an entity's Board of Directors or advisory committees, Research Funding; Principia: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding. Barcellini: Bioverativ: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees; Alexion Pharmaceuticals: Honoraria; Novartis: Honoraria; Agios: Honoraria, Research Funding. Glenthoej: Bluebird Bio: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Calgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Alexion: Research Funding; Novo Nordisk: Honoraria. Judge: Agios Pharmaceuticals: Current Employment, Current holder of stock options in a privately-held company. Kosinski: Agios Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Xu: Agios Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Beynon: Agios Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. McGee: Agios Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Porter: La Jolla Pharmaceuticals: Honoraria; Protagonism: Honoraria; Agios: Consultancy, Honoraria; bluebird bio, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene (BMS): Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Vifor: Honoraria, Membership on an entity's Board of Directors or advisory committees; Silence Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kuo: Celgene: Consultancy; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Bioverativ: Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Research Funding; Bluebird Bio: Consultancy; Apellis: Consultancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.209
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2021
Admission routes1
Has abstractyes

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