Identification of distinct symptom profiles in patients with gynecologic cancers using a pre-specified symptom cluster.
Depression
Fatigue
Gynecologic cancer
Pain
Sleep disturbance
Symptom cluster
Journal
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
ISSN: 1433-7339
Titre abrégé: Support Care Cancer
Pays: Germany
ID NLM: 9302957
Informations de publication
Date de publication:
22 Jul 2023
22 Jul 2023
Historique:
received:
29
01
2023
accepted:
17
07
2023
medline:
24
7
2023
pubmed:
22
7
2023
entrez:
22
7
2023
Statut:
epublish
Résumé
Pain, fatigue, sleep disturbance, and depression are four of the most common symptoms in patients with gynecologic cancer. The purposes were to identify subgroups of patients with distinct co-occurring pain, fatigue, sleep disturbance, and depression profiles (i.e., pre-specified symptom cluster) in a sample of patients with gynecologic cancer receiving chemotherapy and assess for differences in demographic and clinical characteristics, as well as the severity of other common symptoms and QOL outcomes among these subgroups. Patients completed symptom questionnaires prior to their second or third cycle of chemotherapy. Latent profile analysis was used to identify subgroups of patients using the pre-specified symptom cluster. Parametric and nonparametric tests were used to evaluate for differences between the subgroups. In the sample of 233 patients, two distinct latent classes were identified (i.e., low (64.8%) and high (35.2%)) indicating lower and higher levels of symptom burden. Patients in high class were younger, had child care responsibilities, were unemployed, and had a lower annual income. In addition, these women had a higher body mass index, a higher comorbidity burden, and a lower functional status. Patients in the high class reported higher levels of anxiety, as well as lower levels of energy and cognitive function and poorer quality of life scores. This study identified a number of modifiable and non-modifiable risk factors associated with membership in the high class. Clinicians can use this information to refer patients to dieticians and physical therapists for tailored interventions.
Identifiants
pubmed: 37480403
doi: 10.1007/s00520-023-07954-6
pii: 10.1007/s00520-023-07954-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
485Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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