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An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling

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An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling. / Molassiotis, Alex; Farrell, Carole; Bourne, Kathryn et al.
In: Journal of Pain and Symptom Management, Vol. 44, No. 5, 11.2012, p. 692-703.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Molassiotis, A, Farrell, C, Bourne, K, Brearley, SG & Pilling, M 2012, 'An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling', Journal of Pain and Symptom Management, vol. 44, no. 5, pp. 692-703. https://doi.org/10.1016/j.jpainsymman.2011.11.003

APA

Vancouver

Molassiotis A, Farrell C, Bourne K, Brearley SG, Pilling M. An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling. Journal of Pain and Symptom Management. 2012 Nov;44(5):692-703. doi: 10.1016/j.jpainsymman.2011.11.003

Author

Molassiotis, Alex ; Farrell, Carole ; Bourne, Kathryn et al. / An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling. In: Journal of Pain and Symptom Management. 2012 ; Vol. 44, No. 5. pp. 692-703.

Bibtex

@article{b31a49814a5f4089b30b78e0fb397064,
title = "An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling",
abstract = "CONTEXT: Chemotherapy-related nausea is experienced by most cancer patients receiving chemotherapy. Although vomiting is managed well with current antiemetics, nausea is difficult to manage and little is understood about its development. OBJECTIVES: The aim was to determine whether nausea exists as part of a symptom cluster and evaluate the symptom cluster's impact on patients' quality of life, psychological distress, and nutritional status. METHODS: A prospective observational design over two cycles of chemotherapy was used. Patients completed the Memorial Symptom Assessment Scale, Hospital Anxiety and Depression Scale, Functional Assessment of Cancer Therapy-General, and Patient-Generated Subjective Global Assessment before chemotherapy and at the end of the first and second cycles of treatment. Random forest modeling, a state-of-the-art prediction method, was used to analyze the data. RESULTS: One hundred four patients participated in the study. Nausea was found to be a dynamic experience, changing over time. {"}Core{"} symptoms, predictive of the presence of nausea, were identified and included appetite loss, feeling bloated, vomiting, taste changes, and lack of energy. Although nausea alone did have an impact on patient outcomes, the impact was significantly higher in relation to physical and functional quality of life and nutritional status in those patients who had more than two symptoms from the nausea cluster. CONCLUSION: This exploratory study, using an innovative analytical approach, has shown that nausea is a complex symptom affected by the presence and/or severity of other concurrent symptoms (the symptom cluster). The findings have implications for the measurement of nausea and also to target people for interventions to manage nausea and its cluster of symptoms.",
keywords = "Nausea, chemotherapy , symptom cluster , quality of life , nutritional status , random forests",
author = "Alex Molassiotis and Carole Farrell and Kathryn Bourne and Brearley, {Sarah G} and Mark Pilling",
note = "Copyright {\textcopyright} 2012 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.",
year = "2012",
month = nov,
doi = "10.1016/j.jpainsymman.2011.11.003",
language = "English",
volume = "44",
pages = "692--703",
journal = "Journal of Pain and Symptom Management",
issn = "0885-3924",
publisher = "Elsevier Inc.",
number = "5",

}

RIS

TY - JOUR

T1 - An exploratory study to clarify the cluster of symptoms predictive of chemotherapy-related nausea using random forest modeling

AU - Molassiotis, Alex

AU - Farrell, Carole

AU - Bourne, Kathryn

AU - Brearley, Sarah G

AU - Pilling, Mark

N1 - Copyright © 2012 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

PY - 2012/11

Y1 - 2012/11

N2 - CONTEXT: Chemotherapy-related nausea is experienced by most cancer patients receiving chemotherapy. Although vomiting is managed well with current antiemetics, nausea is difficult to manage and little is understood about its development. OBJECTIVES: The aim was to determine whether nausea exists as part of a symptom cluster and evaluate the symptom cluster's impact on patients' quality of life, psychological distress, and nutritional status. METHODS: A prospective observational design over two cycles of chemotherapy was used. Patients completed the Memorial Symptom Assessment Scale, Hospital Anxiety and Depression Scale, Functional Assessment of Cancer Therapy-General, and Patient-Generated Subjective Global Assessment before chemotherapy and at the end of the first and second cycles of treatment. Random forest modeling, a state-of-the-art prediction method, was used to analyze the data. RESULTS: One hundred four patients participated in the study. Nausea was found to be a dynamic experience, changing over time. "Core" symptoms, predictive of the presence of nausea, were identified and included appetite loss, feeling bloated, vomiting, taste changes, and lack of energy. Although nausea alone did have an impact on patient outcomes, the impact was significantly higher in relation to physical and functional quality of life and nutritional status in those patients who had more than two symptoms from the nausea cluster. CONCLUSION: This exploratory study, using an innovative analytical approach, has shown that nausea is a complex symptom affected by the presence and/or severity of other concurrent symptoms (the symptom cluster). The findings have implications for the measurement of nausea and also to target people for interventions to manage nausea and its cluster of symptoms.

AB - CONTEXT: Chemotherapy-related nausea is experienced by most cancer patients receiving chemotherapy. Although vomiting is managed well with current antiemetics, nausea is difficult to manage and little is understood about its development. OBJECTIVES: The aim was to determine whether nausea exists as part of a symptom cluster and evaluate the symptom cluster's impact on patients' quality of life, psychological distress, and nutritional status. METHODS: A prospective observational design over two cycles of chemotherapy was used. Patients completed the Memorial Symptom Assessment Scale, Hospital Anxiety and Depression Scale, Functional Assessment of Cancer Therapy-General, and Patient-Generated Subjective Global Assessment before chemotherapy and at the end of the first and second cycles of treatment. Random forest modeling, a state-of-the-art prediction method, was used to analyze the data. RESULTS: One hundred four patients participated in the study. Nausea was found to be a dynamic experience, changing over time. "Core" symptoms, predictive of the presence of nausea, were identified and included appetite loss, feeling bloated, vomiting, taste changes, and lack of energy. Although nausea alone did have an impact on patient outcomes, the impact was significantly higher in relation to physical and functional quality of life and nutritional status in those patients who had more than two symptoms from the nausea cluster. CONCLUSION: This exploratory study, using an innovative analytical approach, has shown that nausea is a complex symptom affected by the presence and/or severity of other concurrent symptoms (the symptom cluster). The findings have implications for the measurement of nausea and also to target people for interventions to manage nausea and its cluster of symptoms.

KW - Nausea

KW - chemotherapy

KW - symptom cluster

KW - quality of life

KW - nutritional status

KW - random forests

U2 - 10.1016/j.jpainsymman.2011.11.003

DO - 10.1016/j.jpainsymman.2011.11.003

M3 - Journal article

C2 - 22672920

VL - 44

SP - 692

EP - 703

JO - Journal of Pain and Symptom Management

JF - Journal of Pain and Symptom Management

SN - 0885-3924

IS - 5

ER -