Evidence map›Paper›PMID 40179376›Full record

ArticleBlood2025

Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.

Patrick K Reville, Bofei Wang, Jennifer Marvin-Peek, Bin Yuan, Yu-An Kuo, Araceli Garza, Jessica Root, Wei Qiao, Andrea Arruda, Ivo Veletic and 12 more

Abstract read
In one paragraph

Article in Blood, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Refining favorable-risk classification in pediatricBlood science (Baltimore, Md.) · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

Patrick K RevilleDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0001-8433-3360
Bofei WangDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0003-3651-6802
Jennifer Marvin-PeekDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0001-9595-1279
Bin YuanDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Yu-An KuoDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0002-1002-3201
Araceli GarzaDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Jessica RootDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Wei QiaoDivision of Discovery Science, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
Andrea ArrudaDepartment of Medical Biophysics, Princess Margaret Cancer Centre, Toronto, ON, Canada.
Ivo VeleticDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0001-5802-5313
Yiwei LiuDivision of Discovery Science, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0002-9979-6269
Nicholas J ShortDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0002-2983-2738
Courtney D DiNardoDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0001-9003-0390
Tapan M KadiaDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Naval G DaverDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0001-7103-373X
Philip L LorenziDivision of Discovery Science, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0003-0385-7774
Koji SasakiDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0002-9140-0610
Steven KornblauDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Mark D MindenDepartment of Medical Biophysics, Princess Margaret Cancer Centre, Toronto, ON, Canada.ORCID 0000-0002-9089-8816
Farhad RavandiDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Hagop M KantarjianDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.
Hussein A AbbasDivision of Cancer Medicine, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0003-2946-3562

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

abstractInflammation is increasingly recognized as a critical factor in acute myeloid leukemia (AML) pathogenesis. We performed blood-based proteomic profiling of 251 inflammatory proteins in 543 patients with newly diagnosed AML. Using a machine learning model, we derived an 8-protein prognostic score termed the leukemia inflammatory risk score (LIRS). Individual proteins were evaluated in multivariable Cox models, and model performance was assessed by cumulative concordance index. Findings were validated in internal and external cohorts across 2 institutions. Blood-based LIRS significantly outperformed the European LeukemiaNet 2022 risk model and was independently prognostic of overall survival after accounting for known clinical and molecular prognostic factors. Oncostatin M receptor was uniquely identified as the strongest independent predictor of survival, early mortality, and induction chemotherapy response, and further validated in an independent assay. These blood-based biomarkers could have significant clinical implications for risk stratification and prognostication in patients with newly diagnosed AML.

Indexed as

Biomarkers, TumorLeukemia, Myeloid, AcuteProteomicsAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisYoung AdultBiomarkers, Tumor

Identifiers

PMID40179376
PMCPMC12226760

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.