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Record W4239376504 · doi:10.1182/blood-2019-122506

Dynamic and Time-to-Event Analyses Demonstrate Marked Reduction in Transfusion Requirements for Janus Kinase Inhibitor-Naïve Myelofibrosis Patients Treated with Momelotinib Compared Head to Head with Ruxolitinib

2019· article· en· W4239376504 on OpenAlexaff
Ruben A. Mesa, John Catalano, Francisco Cervantes, Timothy Devos, Jason Gotlib, Jean‐Jacques Kiladjian, Donal P. McLornan, Kazuya Shimoda, Elisabeth Coart, Koenraad D’Hollander, Rafe Donahue, Mark Kowalski

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsSierra Wireless (Canada)
Fundersnot available
KeywordsRuxolitinibAnemiaMyelofibrosisMedicineHepcidinInternal medicineGastroenterologyBone marrow

Abstract

fetched live from OpenAlex

Momelotinib (MMB) is a potent, selective, orally-bioavailable, small-molecule inhibitor of JAK1, JAK2 and ACVR1 being developed for the treatment of intermediate and high risk myelofibrosis (MF). Systemic inflammation integral to the pathogenesis of MF leads to increased ACVR1 activity which in turn increases secretion of hepcidin, resulting in perturbed iron homeostasis and an iron-restricted anemia (Physiol Rev. 2013;93:1721-41, Am J Hematol. 2014;89:470-9). MMB's inhibition of ACVR1, unique amongst the JAK inhibitor (JAKi) class, leads to a reduction of hepcidin, restoring iron homeostasis and RBC production and alleviating anemia and transfusion dependency (TD). Chronic, progressive anemia is the key hallmark feature of MF; anemia and TD are strongly predictive of reduced survival (Am J Hematol. 2013;88:312-6). MMB is the only clinical stage JAKi to possess potent ACVR1 inhibitory activity, resulting in improvement of anemia in contrast to ruxolitinib (RUX) which results in worsening. The SIMPLIFY-1 (S1) trial, a double-blind, active-controlled Phase 3 study in which 432 patients received randomized treatment with MMB or RUX for 24 weeks was previously reported (JCO. 2017;35:3844-50). In addition to a significant reduction in splenomegaly and improvement in constitutional symptoms, the study demonstrated that patients in the MMB arm achieved nominal-statistical significance for all anemia endpoints tested, including a higher rate of transfusion independence (p<0.001) and lower rates of TD (p=0.019) at Week 24, compared to patients on RUX, consistent with MMB's pro-erythropoietic effect. Overall, a demonstrably decreased transfusion requirement was noted in patients who received MMB vs RUX. Since transfusion burden is of significant concern to clinicians and patients, to better understand the dynamics of RBC transfusions we further examined the S1 data through statistical models utilizing a variety of novel anemia benefit endpoints including time until transfusion and overall intensity of transfusions across time. The proportions of patients with 0 and 4 transfusions were calculated and time-to-event analyses examining time-to-first and time-to-fifth units transfused also conducted. Since transfusions typically comprise 2 units, the fifth unit transfused represents a de facto third transfusion event. The number of units transfused were also considered to be recurrent events and examined with and without patients' baseline characteristics as covariates. Finally, a mixture model, based on a zero-inflated negative binomial (ZINB) distribution fit to the transfusion data, was employed to compare between the treatment groups the proportions of subjects with zero transfusion burden and the mean transfusion rates. Kaplan-Meier estimates of the proportion of patients who did not require any units transfused during the 24 week randomized treatment period were 73% and 46% for MMB and RUX respectively (p<0.0001; Figure 1), while the proportion of patients requiring 4 or fewer units were 83% and 62% (p<0.0001). When examining units transfused as recurrent events, patients receiving MMB possessed a hazard ratio of approximately one-half that for patients on RUX (HR 0.522; p<0.0001) for models both with and without patients' baseline characteristics as covariates. The ZINB covariate model demonstrated that MMB increased the odds of having zero units transfused in the first 24 weeks by a factor of 9.3 (p<0.0001) vs RUX. Taken together, the novel dynamic and time-to-event analysis methods described are relevant and informative additions to standard measures of transfusion burden in patients with MF. The results of these analyses allow more detailed description of MMB's differentiated anemia benefit as compared to RUX in a double-blind study of JAKi-naïve patients. These results when combined with additional data from the SIMPLIFY studies demonstrate that MMB is able to address the three hallmark features of MF, namely anemia, constitutional symptoms and splenomegaly, differentiating it from other JAK inhibitors. The benefit of MMB in reducing transfusion burden will be further evaluated in MOMENTUM, a future Phase 3 study of MMB in MF patients. In addition to assessment of constitutional symptoms, anemia and splenomegaly, MOMENTUM will provide opportunity to further evaluate associations between anemia benefit and patient reported measures of clinical benefit. Disclosures Mesa: Promedior: Research Funding; Gilead Sciences: Research Funding; Galena Biopharma: Consultancy; AbbVie: Research Funding; Incyte: Other: travel, accommodations, expenses, Research Funding; Genotech: Research Funding; CTI: Research Funding; Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses; Celgene Corporation: Research Funding; Sierra Oncology: Consultancy; PharmaEssentia: Research Funding; Genentech: Consultancy; NS Pharma: Research Funding; Pfizer: Research Funding; AOP Orphan Pharmaceuticals: Honoraria, Other: travel, accommodations, expenses; LaJolla: Consultancy; Samus: Research Funding; Shire: Honoraria; Baxalta: Consultancy. Catalano:Celgene: Other: Travel support (ASH 2018). Cervantes:Novartis: Honoraria, Speakers Bureau; Celgene: Consultancy, Speakers Bureau. Gotlib:Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Research Funding; Promedior: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Allakos: Honoraria, Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Deceiphera: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kiladjian:Novartis: Honoraria, Research Funding; Celgene: Consultancy; AOP Orphan: Honoraria, Research Funding. McLornan:Jazz Pharmaceuticals: Honoraria, Speakers Bureau; Novartis: Honoraria. Coart:IDDI: Consultancy, Employment. D'Hollander:IDDI: Consultancy, Employment. Donahue:Sierra Oncology Inc.: Employment. Kowalski:Sierra Oncology Inc.: Employment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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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Citations7
Published2019
Admission routes1
Has abstractyes

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