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Challenges in predicting hydroxyurea resistance and reducing thrombotic risk in polycythemia vera patients: unmasking the limits of its machine learning study

Leukemia volume 39, pages 3052–3053 (2025)Cite this article

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Dear Editor,

We read with interest the article by Heidel et al. [1] on the PV-AIM machine learning study for predicting hydroxyurea resistance (HU-RES) in polycythemia vera (PV) patients, validated prospectively in the HU-F-AIM trial. While the study innovatively distinguishes molecular from clinical resistance and identifies RDW and HGB thresholds as predictors, several unaddressed aspects warrant scrutiny to enhance its clinical rigor and applicability, drawing from established PV literature.

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Data sharing is not applicable to this article as no new data were created or analyzed in this study.

References

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Acknowledgements

All authors would like to thank Second Affiliated Hospital of Xi’an Jiaotong University for its support.

Funding

This study was supported by the Natural Science Foundation of Shaanxi Province (2024JC-YBQN-0905).

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Authors and Affiliations

  1. Department of Vascular Surgery, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China

    Fangshi Xu, Zongyu Li, Hangyu Fu & Jiancang Ma

Authors
  1. Fangshi Xu
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  2. Zongyu Li
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  3. Hangyu Fu
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  4. Jiancang Ma
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Contributions

JCM conceived and designed the study. FSX, ZYL, and HYF wrote the manuscript. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Jiancang Ma.

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The authors declare no competing interests.

Governing declaration and use of AI

Our study is compliant with the TITAN Guidelines 2025 - governing declaration and use of AI. The authors declare that no AI technology was employed in this study.

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Xu, F., Li, Z., Fu, H. et al. Challenges in predicting hydroxyurea resistance and reducing thrombotic risk in polycythemia vera patients: unmasking the limits of its machine learning study. Leukemia 39, 3052–3053 (2025). https://doi.org/10.1038/s41375-025-02807-z

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