Predicting delayed methotrexate elimination in pediatric acute lymphoblastic leukemia patients: an innovative web-based machine learning tool developed through a multicenter, retrospective analysis

Jian, Chang; Chen, Siqi; Wang, Zhuangcheng; Zhang, Yang; Li, Ziyu; Jian, Jie; Wang, Tingting; Xiang, Tianyu; Wang, Xiao; Jia, Yuntao; Wang, Huilai; Gong, Jianya

doi:10.1186/s12911-023-02248-7

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…For patients experiencing delayed elimination of MTX, the medication regimens were analyzed and adjusted accordingly to mitigate toxic damage. According to previous literature(Jian et al, 2023), delayed elimination of MTX was defined as C24h ≥ 10.0 μM, C48h ≥ 1.0 μM, and C72h ≥ 0.1 μM.…”

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confidence: 99%

An ultrahigh‐performance liquid chromatography–tandem mass spectrometry method for quantification of methotrexate and 7‐hydroxy‐methotrexate and application for therapeutic drug monitoring in patients with central nervous system lymphoma

Huo,

Zhang,

Zhang

et al. 2023

Biomedical Chromatography

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A method using ultrahigh‐performance liquid chromatography–tandem mass spectrometry was developed, validated, and applied to simultaneously determine plasma methotrexate (MTX) and 7‐hydroxy‐methotrexate (7‐OH‐MTX) in 117 patients with central nervous system (CNS) lymphoma. The ion transitions utilized were m/z 455.2 > 308.2 for MTX and m/z 471.2 > 324.1 for 7‐OH‐MTX. Samples were prepared through protein precipitation using methanol. Chromatographic separation was achieved within 3.0 min on a CMS9030 column (Ruixi, 2.1 × 50 mm, 3 μm) through a gradient elution of methanol and a 10% ammonium acetate solution at a flow rate of 0.4 mL/min. The method demonstrated linearity in the concentration range of 0.05–10 μM for MTX and 0.25–50 μM for 7‐OH‐MTX. The intra‐ and inter‐day inaccuracy ranged from –7.38% to 7.83%, and the imprecision was less than 6.00% for both analytes. The recovery and matrix effect normalized by the internal standard (MTX‐D3) remained consistent. Both analytes remained stable under nine different storage conditions. In patients with CNS lymphoma, MTX levels at 12 h and 7‐OH‐MTX levels at 12, 36, and 60 h after dosing in individuals with impaired renal function were significantly higher compared with those with normal renal function. 7‐OH‐MTX could potentially serve as a superior indicator for nephrotoxicity compared with MTX.

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confidence: 99%

An ultrahigh‐performance liquid chromatography–tandem mass spectrometry method for quantification of methotrexate and 7‐hydroxy‐methotrexate and application for therapeutic drug monitoring in patients with central nervous system lymphoma

Huo,

Zhang,

Zhang

et al. 2023

Biomedical Chromatography

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Development of a novel nomogram for predicting delayed methotrexate excretion following high-dose methotrexate in adult patients with hematologic malignancies

Ikeda,

Isezaki,

Narita

et al. 2024

Preprint

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Purpose: High-dose methotrexate (HDMTX) is integral in treating hematologic malignancies but carries risks of severe toxicities due to prolonged MTX exposure. However, knowledge of delayed MTX excretion is primarily derived from pediatric and adolescent cohorts, with the reported predictors being presented as rough dichotomous values. This study aimed to identify risk factors for delayed MTX excretion exclusively in adult patients with hematologic malignancies and develop a more applicable predictive nomogram based on continuous clinical and laboratory variables. Methods: 517 HDMTX cycles in 194 patients were retrospectively analyzed. Delayed MTX excretion was defined as either MTX concentration ≥1.0 μmol/L at 48 h or ≥0.1 μmol/L at 72 h after HDMTX initiation. Multivariate logistic regression analysis was used to construct the nomogram internally validated with the bootstrap method. Results: Delayed MTX excretion was observed in 24.0% of cycles. Six significant predictors were identified: relapsed/refractory disease (Odds ratio [OR] 2.03), fewer HDMTX cycles (OR 0.771), treatment intent (OR 2.13), lower albumin (OR 0.563) and creatinine clearance levels (OR 0.993), and increased γ-glutamyl transpeptidase levels (OR 1.004, all P <0.05). These were incorporated into a web-based nomogram as continuous variables with good prediction accuracy (area under the curve, 0.73) and without significant overfitting. Delayed MTX excretion increased risks of developing acute kidney injury, even solely at the 72 h timepoint (OR 2.57, P = 0.025), without providing any benefit of clinical outcomes. Conclusion: This study comprehensively characterized MTX elimination failure following HDMTX in adult patients and could pave the way for individualized risk prediction.

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Enhancing Disease Diagnosis: Statistical Analysis of Haematological Parameters in Sickle Cell Patients, Integrating Predictive Analytics

Dash,

Naveen,

2024

EAI Endorsed Trans Perv Health Tech

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Sickle cell disease (SCD) affects 30 million people worldwide, causing a range of symptoms from mild to severe, including Vaso occlusive crises (VOC). SCD leads to damaging cycles of sickling and desickling of red blood cells due to HbS polymer formation, resulting in chronic haemolytic anaemia and tissue hypoxia. We propose using machine learning to categorize SCD patients based on haemoglobin, reticulocyte count, and LDH levels, crucial markers of hemolysis. Statistical analysis, particularly Linear Regression, demonstrates how haemoglobin depletion occurs using LDH and reticulocyte parameters. Bilirubin and haemoglobin, two integral biomarkers in clinical biochemistry and haematology, serve distinct yet interconnected roles in human physiology. Bilirubin, a product of heme degradation, is a critical indicator of liver function and various hepatic disorders, while haemoglobin, found in red blood cells, is responsible for oxygen transport throughout the body. Understanding the statistical relationship between these biomarkers has far-reaching clinical implications, enabling improved diagnosis, prognosis, and patient care. This research paper conducts a comprehensive statistical analysis of bilirubin and haemoglobin using various regression techniques to elucidate their intricate association. The primary objective of this study is to characterize the relationship between bilirubin and haemoglobin. Through meticulous data analysis, we explore whether these biomarkers exhibit positive, negative, or no correlation. Additionally, this research develops predictive models for estimating haemoglobin levels based on bilirubin data, offering valuable tools for healthcare professionals in clinical practice.

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Predicting delayed methotrexate elimination in pediatric acute lymphoblastic leukemia patients: an innovative web-based machine learning tool developed through a multicenter, retrospective analysis

Cited by 3 publications

References 30 publications

An ultrahigh‐performance liquid chromatography–tandem mass spectrometry method for quantification of methotrexate and 7‐hydroxy‐methotrexate and application for therapeutic drug monitoring in patients with central nervous system lymphoma

An ultrahigh‐performance liquid chromatography–tandem mass spectrometry method for quantification of methotrexate and 7‐hydroxy‐methotrexate and application for therapeutic drug monitoring in patients with central nervous system lymphoma

Development of a novel nomogram for predicting delayed methotrexate excretion following high-dose methotrexate in adult patients with hematologic malignancies

Enhancing Disease Diagnosis: Statistical Analysis of Haematological Parameters in Sickle Cell Patients, Integrating Predictive Analytics

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