Consensus in Identification and Stability of Symptom Clusters Using Different Symptom Dimensions in Newly Diagnosed Acute Myeloid Leukemia Patients Undergoing Induction Therapy.
J Pain Symptom Manage
; 57(4): 783-792, 2019 04.
Article
en En
| MEDLINE
| ID: mdl-30639731
ABSTRACT
CONTEXT An unresolved issue in symptom cluster (SC) research is that the numbers and types of SCs vary based on the multiple dimensions of the experienced symptoms that are used for SC identification. OBJECTIVE:
This study aimed to identify SCs using the ratings of occurrence, severity, and distress in newly diagnosed acute myeloid leukemia (AML) patients at three stages of their induction therapy (i.e., T1, T2, and T3). Then, we evaluated the consensus among the numbers and types of symptoms in each SC identified by multiple dimensions over time.METHOD:
The Chinese version of the Memorial Symptom Assessment Scale was used to evaluate the occurrence, severity, and distress ratings of 32 symptoms in patients newly diagnosed with AML during their induction therapy. Exploratory factor analysis was used for SCs identification.RESULTS:
Using the three dimensions in the AML patients (n = 126), four SCs were identified at T1 and T3 and three SCs were identified at T2. The number of symptoms in individual SCs varied over time, whereas the specific symptoms in SCs remained similar over time. The severity ratings fit the data better than did the ratings of occurrence and distress.CONCLUSION:
These findings provided insights into the most common SCs in AML patients undergoing induction therapy by multidimensional evaluation and could lay the foundation for future targeted symptom interventions. Further studies are needed to explore the mechanisms of SCs in AML patients undergoing the chemotherapy.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Leucemia Mieloide Aguda
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Quimioterapia Adyuvante
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Terapia Neoadyuvante
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Antineoplásicos
Tipo de estudio:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
Límite:
Adolescent
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Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Año:
2019
Tipo del documento:
Article