Development of Real-world Data-based Medication Instruction Sheet for Acute Myeloid Leukemia Patients Receiving High-dose Cytarabine Consolidation Therapy

Background/Aim: For quick and accurate monitoring of potential adverse events (AEs) during concurrent chemotherapy, we had previously developed innovative medication instruction sheets (MIS) for a variety of chemotherapy regimens. However, it is still unclear whether these sheets correctly predict the type and time course of the onset and recovery of AEs. Therefore, we monitored AEs in patients with acute myeloid leukemia (AML) receiving high-dose cytarabine (HD-AraC) using the original MIS. Patients and Methods: Patients who received HD-AraC following remission induction chemotherapy were included in this study. Data obtained from AE monitoring were evaluated, and the original MIS was modified as appropriate. Results: Among 41 patients, a total of 203 AEs (139 non-hematological and 64 hematological) were observed after chemotherapy. By contrast, all but one patient (97.6%) experienced 102 AEs (43 nonhematological and 59 hematological) before chemotherapy. The AEs that appeared after chemotherapy were all predicted items described in the original MIS; however, their onset and duration were not consistent with the predicted data, in which the prediction accuracy was 69.1% for non-hematological AEs and 1.6% for hematological events. Based on these monitoring data, the original MIS was revised, which led to an increase in the prediction accuracy to 94.2% for nonhematological events and 100% for hematological events. Conclusion: Preexisting AEs should be considered when preparing MIS for consolidation therapy with HD-AraC. The modified MIS based on AE monitoring exhibited a sufficiently high prediction accuracy.

Automated summary

The original medication instruction sheets (MIS) for monitoring adverse events (AEs) during chemotherapy did not accurately predict the type and time course of AEs in patients with acute myeloid leukemia (AML) receiving high-dose cytarabine (HD-AraC). However, after modifying the MIS based on AE monitoring data, the prediction accuracy significantly improved.