Volume 22 Issue 4
Apr.  2024
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Article Navigation >  Chinese Journal of General Practice  > 2024  >  22(4): 574-577
ZHAO Yaoshun, YANG Baimei, LU Meng, LUO Sijun, WANG Zhihua, WU Huaying, WANG Fang. Correlation between mRNA expression levels related to iron death and prognosis in patients with acute myeloid leukemia and analysis of decision curve[J]. Chinese Journal of General Practice, 2024, 22(4): 574-577. doi: 10.16766/j.cnki.issn.1674-4152.003453
Citation: ZHAO Yaoshun, YANG Baimei, LU Meng, LUO Sijun, WANG Zhihua, WU Huaying, WANG Fang. Correlation between mRNA expression levels related to iron death and prognosis in patients with acute myeloid leukemia and analysis of decision curve[J]. Chinese Journal of General Practice, 2024, 22(4): 574-577. doi: 10.16766/j.cnki.issn.1674-4152.003453
shu

Correlation between mRNA expression levels related to iron death and prognosis in patients with acute myeloid leukemia and analysis of decision curve

doi: 10.16766/j.cnki.issn.1674-4152.003453
  • 1.

    Department of Hematology, General Hospital of North China Petroleum Administration Bureau, Cangzhou, Hebei 062550, China

Funds:

 20201252

  • Received Date: 2023-10-27
    Available Online: 2024-05-29
    Abstract
  •   Objective  Drug resistance and disease recurrence are primary factors contributing to poor prognosis in patients with acute myeloid leukemia (AML). In addition to the anti-death effects of malignant clones caused by genetic, epigenetic, and proteomic changes, iron death also plays a role in various cellular biological processes. The purpose of this study is to investigate the correlation between iron death related mRNA expression and prognosis in patients with AML.  Methods  A total of 88 AML patients admitted to the General Hospital of North China Petroleum Administration between January 2020 and March 2021 were included in this study. The patients were divided into two groups based on their prognosis at 24 months: a good prognosis group and a poor prognosis group. The expression levels of mRNA related to iron-death were compared between the two groups. LASSO-logistic regression analysis was used to identify iron-death related mRNA highly correlated with AML prognosis. Furthermore, a decision curve was drawn to compare the prognostic value of ELN risk classification with that of iron-death related mRNA expression levels in AML patients.  Results  After 24-month follow-up, 35 patients experienced death, recurrence, and disease progression were categorized as the poor prognosis group, while the remaining 53 patients were classed as the good prognosis group. Prognostic models were constructed using LASS-logistic regression analysis for the mRNA markers PHKG2, STEAP3, ARNTL, and DPP4. According to the ELN risk classification, 49 cases had a good prognosis, while the remaining 39 cases had a moderate or poor prognosis. The decision curve showed that the predictive models based on PHKG2, STEAP3, ARNTL, and DPP4 mRNA markers exhibited a higher net benefit rate for predicting AML outcomes compared to the ELN risk classification within the threshold range of 0-1.0.  Conclusion  The expression level of iron-death related mRNA is related to the prognosis of AML patients, and analyzing this expression level using a decision curve holds significant value in predicting AML prognosis.

     

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