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Record W4407977458 · doi:10.1016/j.jtct.2025.01.432

The Effects of Prior Lines of Therapy on Clinical Outcomes for Patients with Chronic Graft-Versus-Host Disease Receiving Axatilimab: A Post Hoc Analysis of Agave-201

2025· article· en· W4407977458 on OpenAlexaff
Carrie L. Kitko, Rohtesh S. Mehta, Gizelle Popradi, Eduardo Olavarría, Dries Deeren, B.H. Thomas, John P. Galvin, Song Lou, Vedran Radojčić, Catherine J. Lee

Bibliographic record

VenueTransplantation and Cellular Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsPost-hoc analysisAgavePost hocHost (biology)DiseaseMedicineInternal medicineBiologyGenetics

Abstract

fetched live from OpenAlex

Axatilimab (AXA) is a novel colony-stimulating factor 1 receptor (CSF-1R)–blocking antibody that targets the monocytes and macrophages associated with chronic graft-versus-host disease (cGVHD) pathogenesis. In the AGAVE-201 pivotal trial (NCT04710576), AXA 0.3 mg/kg once every 2 wk (Q2W; FDA-approved dose), demonstrated high response rates and was generally well tolerated in patients with cGVHD. To evaluate the effects of prior lines of therapy (LOT) on clinical outcomes with AXA among patients with cGVHD in AGAVE-201. Patients were randomized 1:1:1 to intravenous AXA (0.3 mg/kg Q2W; 1 mg/kg Q2W; 3 mg/kg Q4W). Overall response rate (ORR), time to first response (TTR), sustained response rate (SRR; proportion of patients with responses lasting ≥20 wk based on a landmark analysis of duration of response), and organ-specific responses were assessed post hoc by number of prior LOT and last therapy (ruxolitinib [RUX], belumosudil [BEL], and other therapies [all therapies other than RUX, including BEL]). LOT were clinically adjudicated for this analysis. The demographics and baseline clinical characteristics of patients in AGAVE-201 are summarized in Table 1 . ORRs with AXA were similar for patients whose best response to last prior treatment was a complete or partial response (65%), no change (62%), and progression (63%; Table 2 ). ORRs were consistent, with slight increases among patients who received a greater number of prior LOT (2 LOT, 51%; 3 LOT, 61%; 4 LOT, 63%; ≥4 LOT, 67%). ORR in the 68 patients treated with RUX in last LOT was 62%, with a median (range) TTR of 1.9 (0.9–5.8) months and SRR of 43% (95% CI, 31%–55%). Among those treated with BEL in last LOT (n=34), ORR was 50%, median (range) TTR was 1.9 (0.9–3.9) months, and SRR was 26% (95% CI, 13%–44%); responses in patients with any therapy other than RUX in last LOT are shown in Table 2 . Organ-specific responses among patients with RUX, other therapies, or BEL in last LOT are summarized in the Figure . In AGAVE-201, ORRs and response durability with AXA were consistent regardless of the number of prior LOT received. Patients who received AXA immediately after a regimen with RUX demonstrated rapid, durable clinical responses. Organ-specific responses to AXA were noted regardless of last prior therapy, and there is a trend towards higher organ-specific response rates for those treated in their last LOT with RUX compared with BEL in some organs (joints/fascia, mouth, lungs, eyes, and skin). This finding warrants further investigation and may be attributable to the novel mechanism of action of AXA or LOT. Small patient numbers and mixed treatment regimens may limit interpretation. These data demonstrate the efficacy of AXA for steroid-refractory cGVHD after 2 LOT, including patients treated with RUX as last LOT.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.355
Teacher spread0.334 · 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 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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Citations1
Published2025
Admission routes1
Has abstractno

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