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Record W3097014108 · doi:10.1182/blood-2020-136625

Comparative Efficacy of CC-486 Versus Injectable Azacitidine (AZA) in Patients (Pts) with Acute Myeloid Leukemia (AML) in First Remission after Intensive Induction Chemotherapy: Findings from an Indirect Treatment Comparison (ITC)

2020· article· en· W3097014108 on OpenAlexaff
Clara Chen, Tim Disher, Muhaimen Siddiqui, Ignazia La Torre, Barry Skikne, Beatrice Suero, Heather Cameron, Roya Gavanji, Chris Cameron

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsEVERSANA (Canada)
Fundersnot available
KeywordsMedicineInternal medicineChemotherapyChemotherapy regimenInduction chemotherapyAzacitidineOncologyGastroenterologySurgery

Abstract

fetched live from OpenAlex

Introduction: Standard treatment with intensive induction chemotherapy (IC) for pts with AML can induce remission, but responses are often short-lived, and the majority of pts will relapse (Chen Y, et al. Medicine 2016;95:e4182). Although maintenance therapy with injectable AZA has improved disease-free survival in pts with AML in complete remission (CR) or CR with incomplete hematologic recovery (CRi) after intensive chemotherapy (Huls G, et al. Blood 2019;133:1457; Oliva EN, et al. Blood 2019;134(Supp 1):117), overall survival (OS) benefits have been more difficult to achieve. In the randomized, phase 3 QUAZAR AML-001 study (NCT01757535), maintenance therapy with CC-486, a novel oral formulation of AZA, demonstrated a significant 9.9-month improvement in OS and a 31% reduction in mortality versus placebo (PBO) for pts with AML in first CR/CRi following intensive chemotherapy (Wei AH, et al. Blood 2019;134:LBA-3). In the absence of direct head-to-head clinical studies to guide treatment selection, we used an ITC to evaluate the comparative efficacy of CC-486 versus injectable AZA as maintenance therapy in pts with AML in first remission after intensive chemotherapy. Methods: Relative OS was calculated by using individual patient data (IPD) derived from published Kaplan-Meier (KM) OS curves from the QUAZAR AML-001 (NCT01757535) study of CC-486 versus PBO, and 2 studies of injectable AZA versus control (HOVON 97 [EudraCT 2008-001290-15] and QoLESS [EudraCT 2010-019710-24]) using Engauge digitization software (Guyot P, et al. BMC Med Res Methodol 2012;12:9). Unlike pts from the intervention arm (CC-486, AZA), pts in the PBO/control arm did not receive cancer therapy post-IC. For each study, time-specific relative OS benefit was calculated by dividing the difference in the KM OS estimate between each intervention arm and the respective PBO/control arm by the KM OS estimate for the PBO/control arm (Betts KA, et al. poster presented at EHA 2017:E1300). Treatment effect was measured by fitting parametric survival curves to the IPD from the intervention arm and PBO/control arms, respectively. The restricted mean survival time (RMST) was estimated as the area under the OS curve (AUC) at 1, 2, 3, 4, and 5 years. The incremental AUC (ΔAUC) was determined at selected timepoints by subtracting the RMST of the PBO/control arm from the RMST of the intervention arm for each study. A 95% confidence interval for the incremental mean survival time was estimated via simulation from the variance-covariance matrix of the fitted parametric model using ≥ 10,000 iterations. Results: Follow-up was longest for QUAZAR AML-001 (5 years) with both HOVON 97 and QoLESS limited to 30 months at time of analysis. Overall, CC-486 showed a sustained and numerically higher relative OS benefit through 60 months compared with AZA in HOVON 97 and QoLESS (Figure). The relative benefit of AZA versus control in the initial 18 months appeared to fade, reaching close to or below zero around month 21. Indeed, the relative OS benefit with CC-486 and AZA (HOVON 97, QoLESS) was 30.4%, 20.3%, and 15.5% at 12 months; 35.5%, 17.0%, and 21.8% at 18 months; and 36.4%, −7.7%, and 2.2% at 24 months, respectively. Log-normal survival curves were fitted to IPD from each intervention arm and the respective PBO/control arm. Comparing the RMST, CC-486 showed a statistically meaningful improvement in mean survival time at 1, 2, 3, 4, and 5 years and for the entire extrapolation period, while AZA was not associated with significant OS benefits at any time point in HOVON 97 or QoLESS (Table). The mean incremental survival benefit with CC-486 versus PBO and AZA (HOVON 97 and QoLESS) versus control at 3 years was 4.18 versus 1.18 and 2.35 months, respectively; at 5 years was 6.14 versus 1.11 and 0.99 months, respectively; and for the entire extrapolation period was 10.12 versus −6.58 and −18.32 months, respectively. The improvement in mean OS of 10.12 months with CC-486 was consistent with the median OS improvement (9.9 months) reported in QUAZAR AML-001. Conclusions: In this ITC, CC-486 had a longer duration of follow-up than injectable AZA and an earlier and more durable relative OS benefit, which was maintained beyond 60 months. This analysis demonstrates that CC-486 was associated with a meaningful improvement in mean survival time, and that maintenance treatment with CC-486 provides a long-term survival benefit compared with the relative short-term benefit observed with AZA. Disclosures Chen: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Disher:Eversana: Current Employment. Siddiqui:Eversana: Current Employment. La Torre:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Skikne:Bristol Myers Squibb: Current Employment. Suero:Eversana: Current Employment; Bristol Myers Squibb: Consultancy. Cameron:Eversana: Current Employment. Gavanji:Eversana: Current Employment. Cameron:Eversana: Current Employment, Current equity holder in private company.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.035
GPT teacher head0.303
Teacher spread0.268 · 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 designMeta-analysis
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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Citations0
Published2020
Admission routes1
Has abstractyes

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