Myung Sook Cho; In Gak Kwon; Hee Sun Kim; Kyunghee Kim; Eunjung Ryu

doi:10.4040/jkan.2009.39.5.683

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Original Article
Identification and Validation of Symptom Clusters in Patients with Hepatocellular Carcinoma: Myung Sook Cho, In Gak Kwon, Hee Sun Kim, Kyunghee Kim, Eunjung Ryu; Journal of Korean Academy of Nursing 2009;39(5):683-692.
DOI: https://doi.org/10.4040/jkan.2009.39.5.683
Published online: October 31, 2009

¹Associate Professor, Department of Clinical Nursing Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.

²Unit Manager, Department of Nursing, Samsung Medical Center, Seoul, Korea.

³Professor, Department of Nursing, Chung-Ang University, Seoul, Korea.

⁴Professor, Department of Nursing, Konkuk University, Chungju, Korea.

Address reprint requests to: Kwon, In Gak. Department of Clinical Nursing Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-dong, Gangnam-gu, Seoul 135-710, Korea. Tel: 82-2-3410-2904, Fax: 82-2-3410-6616, ingak.kwon@samsung.com

• Received: March 4, 2009 • Accepted: September 17, 2009

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Abstract
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Abstract

Purpose
The purpose of this study was to identify cancer-related symptom clusters and to validate the conceptual meanings of the revealed symptom clusters in patients with hepatocellular carcinoma.
Methods
This study was a cross-sectional survey and methodological study. Patients with hepatocellular carcinoma (N=194) were recruited from a medical center in Seoul. The 20-item Symptom Checklist was used to assess patients' symptom severity. Selected symptoms were factored using principal-axis factoring with varimax rotation. To validate the revealed symptom clusters, the statistical differences were analyzed by status of patients' performance status, Child-Pugh classification, and mood state among symptom clusters.
Results
Fatigue was the most prevalent symptom (97.4%), followed by lack of energy and stomach discomfort. Patients' symptom severity ratings fit a four-factor solution that explained 61.04% of the variance. These four factors were named pain-appetite cluster, fatigue cluster, itching-constipation cluster, and gastrointestinal cluster. The revealed symptom clusters were significantly different for patient performance status (ECOG-PSR), Child-Pugh class, anxiety, and depression.
Conclusion
Knowing these symptom clusters may help nurses to understand reasonable mechanisms for the aggregation of symptoms. Efficient symptom management of disease-related and treatment-related symptoms is critical in promoting physical and emotional status in patients with hepatocellular carcinoma.
Keywords: Symptom; Cluster; Hepatocellular carcinoma

REFERENCES

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Table 1

Characteristics of Participants (N=194)

^*Missing value excluded; ^†Multiple response.

TACE=transcatheter arterial chemoembolization; RFA=radiofrequency ablation; ECOG PS=Eastern Cooperative Oncology Group Performance Status.

Table 2

Symptom Prevalence and Severity (N=194)

^*Symptom severity was computed by averaging the symptom severity scores of those who had one or more symptoms.

Table 3

Factor Matrix for the Four-factor Model (N=194)

Table 4

Correlations Matrix among Factors (N=194)

Table 5

Symptom Scores of Factors by Performance Status and Liver Function (N=194)

ECOG=Eastern Cooperative Oncology Group Performance Status.

Table 6

Symptom Scores of Factors by Anxiety and Depression (N=194)

Figure & Data

REFERENCES

Citations

Citations to this article as recorded by

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Identification and Validation of Symptom Clusters in Patients with Hepatocellular Carcinoma

J Korean Acad Nurs. 2009;39(5):683-692. Published online October 31, 2009

DOI: https://doi.org/10.4040/jkan.2009.39.5.683

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Identification and Validation of Symptom Clusters in Patients with Hepatocellular Carcinoma

Table 1

Characteristics of Participants (N=194)

^*Missing value excluded; ^†Multiple response.

TACE=transcatheter arterial chemoembolization; RFA=radiofrequency ablation; ECOG PS=Eastern Cooperative Oncology Group Performance Status.

Table 2

Symptom Prevalence and Severity (N=194)

^*Symptom severity was computed by averaging the symptom severity scores of those who had one or more symptoms.

Table 3

Factor Matrix for the Four-factor Model (N=194)

Table 4

Correlations Matrix among Factors (N=194)

Table 5

Symptom Scores of Factors by Performance Status and Liver Function (N=194)

ECOG=Eastern Cooperative Oncology Group Performance Status.

Table 6

Symptom Scores of Factors by Anxiety and Depression (N=194)

Table 1 Characteristics of Participants (N=194)

^*Missing value excluded; ^†Multiple response.

TACE=transcatheter arterial chemoembolization; RFA=radiofrequency ablation; ECOG PS=Eastern Cooperative Oncology Group Performance Status.

Table 2 Symptom Prevalence and Severity (N=194)

^*Symptom severity was computed by averaging the symptom severity scores of those who had one or more symptoms.

Table 3 Factor Matrix for the Four-factor Model (N=194)

Table 4 Correlations Matrix among Factors (N=194)

Table 5 Symptom Scores of Factors by Performance Status and Liver Function (N=194)