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

  • Daisuke Ikeda,
  • Tatsuya Isezaki,
  • Kentaro Narita,
  • Satoshi Yuyama,
  • Mitsuaki Oura,
  • Atsushi Uehara,
  • Rikako Tabata,
  • Masami Takeuchi,
  • Kosei Matsue

摘要

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.