医学
生存曲线
粘膜炎
头颈部癌
癌症
潜在类模型
内科学
放射治疗
统计
数学
作者
Hayley Dunnack Yackel,Wanli Xu,Jung Wun Lee,Xiaomei Cong,Andrew Salner,Valerie B. Duffy,Michelle Judge
出处
期刊:Cancer Nursing
[Lippincott Williams & Wilkins]
日期:2023-03-07
卷期号:47 (4): 261-270
被引量:8
标识
DOI:10.1097/ncc.0000000000001227
摘要
BACKGROUND: Patients with head and neck cancer (HNC) experience a multitude of symptoms because of the tumor and its treatment. OBJECTIVE: To identify the symptom patterns present in cancer treatment and survivorship periods for patients with HNC using latent class analysis. METHODS: A retrospective longitudinal chart review was conducted to examine symptoms reported by patients who received concurrent chemoradiation for HNC in a regional Northeastern United States cancer institute. Latent class analysis was performed to identify the latent classes present across multiple timepoints during treatment and survivorship for the most commonly reported symptoms. RESULTS: In 275 patients with HNC, the latent transition analysis revealed 3 latent classes for both treatment and survivorship periods: (1) mild, (2) moderate, and (3) severe symptoms. Patients were more likely to report a greater number of symptoms in a more severe latent class. During treatment, moderate and severe classes had representation of all most common symptoms: pain, mucositis, taste alterations, xerostomia, dysphagia, and fatigue. Different symptom patterns emerged for survivorship, with prominence of taste alterations and xerostomia across all classes, and all symptoms present in the severe class. The probability of symptom expression varied more in the survivorship period compared with the treatment period. CONCLUSIONS: Patients reported numerous symptoms during active treatment persisting into survivorship. Patients tended to transition to more severe symptomatology as treatment progressed and to more moderate symptomatology as survivorship evolved. IMPLICATIONS FOR PRACTICE: Examining the trend of persistent moderate symptomatology into survivorship is useful to optimize symptom management.
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