Evidence map›Paper›PMID 41694089›Full record

ArticleEJHaem2026

High miR-202-5p Expression at Initial Diagnosis is Associated With Tyrosine Kinase Inhibitor Resistance In Chronic Myeloid Leukemia-A Result From a Nested Case-Control Study.

Zi-Yuan Nie, Jia Wang, Zi-Yu Zhao, Ya-Bei Zuo, Jin-Ao Li, Tie-Jun Gong

Abstract read
In one paragraph

Article in EJHaem, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zi-Yuan NieDepartment of Hematology The Second Hospital of Hebei Medical University Shijiazhuang Hebei China.
Jia WangHospital Bossiness Management Office The Second Hospital of Hebei Medical University Shijiazhuang Hebei China.
Zi-Yu ZhaoDepartment of Hematology The Second Hospital of Hebei Medical University Shijiazhuang Hebei China.
Ya-Bei ZuoDepartment of Hematology The Second Hospital of Hebei Medical University Shijiazhuang Hebei China.
Jin-Ao LiDepartment of Hematology The Second Hospital of Hebei Medical University Shijiazhuang Hebei China.
Tie-Jun GongInstitute of Harbin Hematology & Oncology The First Hospital of Harbin Harbin Heilongjiang China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tyrosine kinase inhibitor (TKI) resistance remains a critical challenge in chronic myeloid leukemia (CML). While mechanistic studies implicate miR-202-5p in resistance, its clinical relevance as a biomarker at diagnosis requires validation. Methods: A nested case-control design was employed within a prospective cohort of 797 newly diagnosed chronic-phase CML patients. Of these, 31 patients who developed TKI resistance (per ELN 2020 criteria, without ABL mutations) were matched 1:4 to 124 TKI-sensitive controls on age, sex, Sokal score, and baseline white blood cell count. miR-202-5p expression was quantified by qRT-PCR from diagnostic peripheral blood mononuclear cells (PBMCs). Statistical analyses included conditional logistic regression and receiver operating characteristic (ROC) curve analysis. Results: The expression level of miR-202-5p was significantly elevated in the TKI-resistant group (1.68 ± 0.45) compared to the TKI-sensitive group (1.26 ± 0.32) ( Conclusion: Elevated miR-202-5p expression at diagnosis is significantly associated with TKI resistance in CML. These findings support its potential as a clinical biomarker for identifying high-risk patients, which could aid in early risk stratification and guide therapeutic strategy. Trial Registration: The authors have confirmed clinical trial registration is not needed for this submission.

Indexed as

biomarkerchronic myeloid leukemiamiR‐202‐5pnested case‐control study

Identifiers

PMID41694089
PMCPMC12896366

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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.