Symptoms associated with concurrent chemoradiotherapy in patients with cervical cancer: Application of latent profile analysis and network analysis

IF 2.4 3区医学 Q1 NURSING

Asia-Pacific Journal of Oncology Nursing Pub Date : 2024-12-27 DOI:10.1016/j.apjon.2024.100649

Xiangyu Lu , Lingling Zheng , Xue Jin , Yuejia Wang , Shengwu Wu , Yin Lv , Hua Du

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引用次数: 0

Abstract

Objective

This study aims to explore symptom subgroups and influencing factors among patients undergoing concurrent chemoradiotherapy (CCRT) for cervical cancer, to construct a symptom network, and to identify core symptoms within the overall sample and its various subgroups.

Methods

A cross-sectional survey was conducted with 378 patients undergoing CCRT for cervical cancer from June 2023 to May 2024 at a tertiary hospital in Anhui Province. Participants completed the General Information Questionnaire, the Symptom Assessment Scale for Patients Undergoing CCRT for Intermediate and Advanced Cervical Cancer, and the Dyadic Coping Inventory. Latent profile analysis (LPA) identified symptom subgroups, while multivariate logistic regression examined influences on these subgroups. Symptom networks were developed using R language to analyze centrality indices and identify core symptoms.

Results

Patients were classified into three subgroups: low symptom burden (n = 200, 52.91%), moderate symptom burden with prominent intestinal response (n = 75, 19.84%), and high symptom burden (n = 103, 27.25%). Multivariate logistic regression indicated that age, tumor stage, chemotherapy frequency, and dyadic coping (DC) were predictive of subgroup membership (P < 0.05). Network analysis revealed sadness (r_s = 1.320) as the core symptom for the overall sample, nausea (r_s = 0.801) for the low symptom burden group, and vomiting (r_s = 0.705, 0.796) for both the moderate symptom burden with intestinal response prominence group and the high symptom burden group.

Conclusions

Three symptom subgroups exist among patients undergoing CCRT for cervical cancer, with sadness, nausea, and vomiting identified as core symptoms. Health care professionals should provide individualized symptom management tailored to these subgroups.

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宫颈癌患者同步放化疗相关症状：潜伏剖面分析和网络分析的应用

目的：本研究旨在探讨宫颈癌同步放化疗（CCRT）患者的症状亚群及其影响因素，构建症状网络，在整体样本及其各亚群中识别核心症状。方法：对安徽省某三级医院于2023年6月至2024年5月行宫颈癌CCRT的378例患者进行横断面调查。参与者填写《一般情况问卷》、《中晚期宫颈癌CCRT患者症状评定量表》和《二元应对量表》。潜在特征分析（LPA）确定了症状亚组，而多变量逻辑回归检查了对这些亚组的影响。采用R语言构建症状网络，分析中心性指数，识别核心症状。结果：患者分为低症状负担组（n = 200, 52.91%）、中度症状负担组（n = 75, 19.84%）和高症状负担组（n = 103, 27.25%）。多因素logistic回归分析显示，年龄、肿瘤分期、化疗频率和二元应对（DC）是亚组成员的预测指标（P rs = 1.320），低症状负担组为恶心（r s = 0.801），中度症状负担伴肠反应突出组和高症状负担组均为呕吐（r s = 0.705, 0.796）。结论：宫颈癌行CCRT患者存在三个症状亚组，以悲伤、恶心和呕吐为核心症状。卫生保健专业人员应针对这些亚组提供个性化的症状管理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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