Symptom clusters and characteristics of cervical cancer patients receiving concurrent chemoradiotherapy: A cross-sectional study

Hao Tie; Limei Shi; Li Wang; Xinyu Hao; Hongyan Fang; Lirong Li

doi:10.1016/j.heliyon.2023.e22407

Symptom clusters and characteristics of cervical cancer patients receiving concurrent chemoradiotherapy: A cross-sectional study

Heliyon. 2023 Nov 17;9(12):e22407. doi: 10.1016/j.heliyon.2023.e22407. eCollection 2023 Dec.

Authors

Hao Tie^{1

2}, Limei Shi³, Li Wang⁴, Xinyu Hao², Hongyan Fang¹, Lirong Li¹

Affiliations

¹ Oncology Center Radiotherapy Ward 1, Guangxi Academy of Medical Sciences, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
² School of Nursing, Guangxi University of Chinese Medicine, Nanning, China.
³ Oncology Center Radiotherapy Ward 2, Guangxi Academy of Medical Sciences, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
⁴ School of Nursing and Health, Zhengzhou University, Zhengzhou, China.

Abstract

Background: Cervical cancer patients have a high symptom burden during concurrent chemoradiotherapy (CCRT) and urgently need precise symptom management strategies. Nonetheless, the symptom profile and influencing factors are unclear.

Methods: A total of 234 patients with cervical cancer who underwent CCRT in a tertiary care hospital clinical oncology center in Guangxi Zhuang Autonomous Region from March 2022 to March 2023 were included in the study. The general information questionnaire, M.D. Anderson symptom inventory, Fatigue Scale-14, Pittsburgh Sleep Quality Index, and grip strength test were used for the investigation. Symptom clusters were extracted by exploratory factor analysis, and latent profile analysis was performed using Mplus 8.0 software. Multinomial logistic regression was used to explore the factors influencing the potential categories of symptom clusters.

Results: Exploratory factor analysis extracted four symptom clusters: a fatigue-related symptom cluster, a gastrointestinal-related symptom cluster, a mood-related symptom cluster, and a physical-related symptom cluster, of which the fatigue-related symptom cluster was more severe and was divided into three potential categories: low fatigue-good muscle fitness type (25.63%), general fatigue-moderate muscle fitness type (68.37%) and high fatigue-low muscle fitness type (6%). Multinomial logistic regression analysis showed that hemoglobin levels, tumor stage, absence of complications, and unemployment were factors influencing the fatigue-related symptom cluster in patients undergoing CCRT for cervical cancer.

Conclusions: Cervical cancer patients experience multiple symptom clusters during CCRT. Different characteristics appeared in different clusters. Among them, fatigue-related symptom clusters were more severe and heterogeneous. In clinical practice, we should pay attention to and use high symptom feature predictors, focusing on the core symptoms that play a dominant role, achieving early identification and management, and reducing patients' symptom burden.

Keywords: Cervical cancer; Concurrent chemotherapy; Influencing factors; Latent profile analysis; Symptom clusters.