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Record W7094944311 · doi:10.6084/m9.figshare.30435128

Additional file 1 of High IL1R1 expression predicts poor survival and benefit from stem cell transplant in intermediate-risk acute myeloid leukemia from the Leucegene cohort

2025· article· W7094944311 on OpenAlexaff

Bibliographic record

VenueFigshare · 2025
Typearticle
Language
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineHôpital Maisonneuve-RosemontUniversity Health NetworkUniversity of TorontoInstitute for Research in Immunology and Cancer
Fundersnot available
KeywordsInterleukin 1 receptor, type IExact testContingency tableCensoring (clinical trials)Survival analysisInterleukin-1 receptor

Abstract

fetched live from OpenAlex

Additional file 1. Supplementary methods. Table S1 Treatments received by patients in the Leucegene cohort. Table S2 Clinical outcomes according to IL1R1 expression. Table S3 Multivariable analyses for OS and RFS without censoring at time of HSCT in CR1. Table S4 Characteristics of patients according to HSCT status. Table S5 Clinical outcomes post-HSCT according to IL1R1 expression. Table S6 C-index in MVA including ELN 2022 and IL1R1 expression as covariable. Table S7 Primers and probes for the IL1R1 RT-qPCR test. Table S8 Analytical validation performance specifications for the IL1R1 RT-qPCR test. Table S9 Prognostic analyses of genes involved in the IL1 signaling pathway and other related genes. Fig. S1 Identification of IL1R1 expression as a prognostic and predictive biomarker. Fig. S2 Identification of the optimal cutoff value for dichotomization of IL1R1 expression. Fig. S3 Benefit from HSCT in CR1 for overall survival using different cutoffs for IL1R1 expression. Fig. S4 Expression of IL1R1 according to the type of sample sequenced and myelomonocytic differentiation of the AML. Fig. S5 Cumulative incidence of death in remission according to IL1R1 expression. Fig. S6 Prognostic impact of IL1R1 expression according to the type of sample sequenced and the sequencing cohort. Fig. S7 Prognostic impact of IL1R1 expression according to NPM1 or FLT3-ITD mutational status. Fig. S8 Prognostic impact of IL1R1 expression according to age. Fig. S9 Prognostic impact of IL1R1 expression according to 2022 ELN risk classification. Fig S10 Prognostic impact of IL1R1 with a higher cutoff value in patients with ELN 2022 favorable-risk AML. Fig. S11 Benefit from HSCT in CR1 for RFS in clinicopathological subgroups of patients. Fig. S12 Impact of HSCT in CR1 on survival outcomes according to NPM1 mutational status and IL1R1 expression in patients FLT3-ITD negative. Fig. S13 Correlation between IL1R1 expression quantification by the RT-qPCR test and RNA sequencing and clinical validation of the IL1R1 RT-qPCR test in the Leucegene cohort. Fig. S14 Additional Gene Set Enrichment Analyses between patients with high and low expression of IL1R1. Fig. S15 Analysis of IL1R1 expression in normal blood and bone marrow populations and in acute leukemias sequenced in the Leucegene project. Fig. S16 Single-cell RNA sequencing of normal bone marrow and AML specimens.

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)0.002
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.750
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7500.068

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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