Analyzing the Symptom Clusters Among Children With Acute Lymphoblastic Leukemia During Chemotherapy Based on

Yuxin Wang1, Hongxia Xie, Hao Jiang

  • 1Author Affiliations: School of Nursing, Wenzhou Medical University (Ms Wang, Mr Jiang, Mss Chen and Ren, and Dr Dong); and School of Computer and Computing Science, Hangzhou City University (Ms Xie), China.

Cancer Nursing
|October 10, 2023
PubMed

Insights

Symptom clusters in children with acute lymphoblastic leukemia (ALL) during chemotherapy are dynamic yet stable. Understanding these patterns helps improve symptom management for pediatric cancer patients.

Area of Science:

  • Pediatric Oncology
  • Nursing Informatics
  • Symptom Science

Background:

  • Children undergoing chemotherapy for acute lymphoblastic leukemia (ALL) experience numerous physical and psychological symptoms.
  • Previous research using fixed inventories has limitations in capturing complex symptom dynamics.

Purpose of the Study:

  • To investigate the evolving symptom clusters in pediatric ALL patients during different chemotherapy phases.
  • Utilize electronic nursing records for a comprehensive analysis of symptom presentation.

Main Methods:

  • Analysis of 14,490 electronic nursing records from a pediatric hematology department.
  • Natural language processing identified 46 symptoms across induction, consolidation, and maintenance chemotherapy phases.
  • Principal component and cluster analyses were applied to symptoms with >15% incidence.

Main Results:

  • Common symptoms included bleeding, cough, and vomiting.
  • Symptom clusters varied by phase: 7 in induction, 6 in consolidation, 4 in maintenance.
  • Persistent clusters (gastrointestinal, respiratory, skin) were observed, with neurological and other discomfort emerging in consolidation.

Conclusions:

  • Symptom clusters in pediatric ALL chemotherapy exhibit both stability and dynamic changes.
  • Findings support the development of continuous, phase-specific symptom management strategies for healthcare providers.
  • Targeted interventions based on cluster characteristics can enhance symptom management efficiency and reduce patient burden.
Abstract

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