{"title":"头颈癌患者的症状群、轨迹及影响因素:一项纵向研究。","authors":"Qiling Shen, Jiaxin Li, Ziyue Fu, Biaoxin Zhang, Yaling Zheng, Kaile Wu","doi":"10.1097/NCC.0000000000001509","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>While head and neck cancer (HNC) patients often experience many concurrent symptoms, most research has focused on the assessment and management of individual, isolated symptoms.</p><p><strong>Objective: </strong>The aim of this study was to investigate the longitudinal trajectories of symptom clusters in patients with HNC and analyze the predictive factors of each trajectory subgroup.</p><p><strong>Methods: </strong>An exploratory factor analysis was conducted to analyze symptom clusters using the M. D. Anderson Symptom Inventory-Head and Neck in 218 HNC patients at 3 time points: during hospitalization, 1 month after discharge, and 3 months after discharge. The latent growth mixture modeling was used to identify the trajectory subgroups, and multinomial logistic regression was used to analyze the predictive factors of trajectory changes.</p><p><strong>Results: </strong>The 4 symptom clusters were referred to as the mouth and throat symptom cluster, gastrointestinal symptom cluster, psychotherapeutic symptom cluster, and energy deficit symptom cluster. Three to 4 trajectory subgroups were identified in the symptom cluster using the latent growth mixture modeling. High-risk trajectory subgroups were influenced by female patients, low family per-capita monthly income, laryngeal cancer, high clinical staging, and age ( P < .05).</p><p><strong>Conclusions: </strong>Mouth and throat symptom cluster is unique to HNC. The high-risk trajectory categories are influenced by gender, family per-capita monthly income, tumor site, TNM clinical staging, and age.</p><p><strong>Implications for practice: </strong>Identifying high-risk trajectories and influencing factors of symptom clusters can help cancer caregivers in implementing individualized and tailored interventions.</p>","PeriodicalId":50713,"journal":{"name":"Cancer Nursing","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Symptom Clusters Trajectories and Influencing Factors in Patients With Head and Neck Cancer: A Longitudinal Study.\",\"authors\":\"Qiling Shen, Jiaxin Li, Ziyue Fu, Biaoxin Zhang, Yaling Zheng, Kaile Wu\",\"doi\":\"10.1097/NCC.0000000000001509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>While head and neck cancer (HNC) patients often experience many concurrent symptoms, most research has focused on the assessment and management of individual, isolated symptoms.</p><p><strong>Objective: </strong>The aim of this study was to investigate the longitudinal trajectories of symptom clusters in patients with HNC and analyze the predictive factors of each trajectory subgroup.</p><p><strong>Methods: </strong>An exploratory factor analysis was conducted to analyze symptom clusters using the M. D. Anderson Symptom Inventory-Head and Neck in 218 HNC patients at 3 time points: during hospitalization, 1 month after discharge, and 3 months after discharge. The latent growth mixture modeling was used to identify the trajectory subgroups, and multinomial logistic regression was used to analyze the predictive factors of trajectory changes.</p><p><strong>Results: </strong>The 4 symptom clusters were referred to as the mouth and throat symptom cluster, gastrointestinal symptom cluster, psychotherapeutic symptom cluster, and energy deficit symptom cluster. Three to 4 trajectory subgroups were identified in the symptom cluster using the latent growth mixture modeling. High-risk trajectory subgroups were influenced by female patients, low family per-capita monthly income, laryngeal cancer, high clinical staging, and age ( P < .05).</p><p><strong>Conclusions: </strong>Mouth and throat symptom cluster is unique to HNC. The high-risk trajectory categories are influenced by gender, family per-capita monthly income, tumor site, TNM clinical staging, and age.</p><p><strong>Implications for practice: </strong>Identifying high-risk trajectories and influencing factors of symptom clusters can help cancer caregivers in implementing individualized and tailored interventions.</p>\",\"PeriodicalId\":50713,\"journal\":{\"name\":\"Cancer Nursing\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Nursing\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/NCC.0000000000001509\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NCC.0000000000001509","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
Symptom Clusters Trajectories and Influencing Factors in Patients With Head and Neck Cancer: A Longitudinal Study.
Background: While head and neck cancer (HNC) patients often experience many concurrent symptoms, most research has focused on the assessment and management of individual, isolated symptoms.
Objective: The aim of this study was to investigate the longitudinal trajectories of symptom clusters in patients with HNC and analyze the predictive factors of each trajectory subgroup.
Methods: An exploratory factor analysis was conducted to analyze symptom clusters using the M. D. Anderson Symptom Inventory-Head and Neck in 218 HNC patients at 3 time points: during hospitalization, 1 month after discharge, and 3 months after discharge. The latent growth mixture modeling was used to identify the trajectory subgroups, and multinomial logistic regression was used to analyze the predictive factors of trajectory changes.
Results: The 4 symptom clusters were referred to as the mouth and throat symptom cluster, gastrointestinal symptom cluster, psychotherapeutic symptom cluster, and energy deficit symptom cluster. Three to 4 trajectory subgroups were identified in the symptom cluster using the latent growth mixture modeling. High-risk trajectory subgroups were influenced by female patients, low family per-capita monthly income, laryngeal cancer, high clinical staging, and age ( P < .05).
Conclusions: Mouth and throat symptom cluster is unique to HNC. The high-risk trajectory categories are influenced by gender, family per-capita monthly income, tumor site, TNM clinical staging, and age.
Implications for practice: Identifying high-risk trajectories and influencing factors of symptom clusters can help cancer caregivers in implementing individualized and tailored interventions.
期刊介绍:
Each bimonthly issue of Cancer Nursing™ addresses the whole spectrum of problems arising in the care and support of cancer patients--prevention and early detection, geriatric and pediatric cancer nursing, medical and surgical oncology, ambulatory care, nutritional support, psychosocial aspects of cancer, patient responses to all treatment modalities, and specific nursing interventions. The journal offers unparalleled coverage of cancer care delivery practices worldwide, as well as groundbreaking research findings and their practical applications.