Medina Joan C, Jansen Femke, Lissenberg-Witte Birgit I, de Bree Remco, Brakenhoff Ruud H, Hardillo Jose, Langendijk Johannes A, Leemans C René, Takes Robert P, Lamers Femke, Verdonck-de Leeuw Irma M
Department of Psychology and Education Sciences, Universitat Oberta de Catalunya, Barcelona, Spain.
eHealth ICOnnecta't Program, Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain.
Support Care Cancer. 2025 Aug 29;33(9):820. doi: 10.1007/s00520-025-09871-2.
He ad and neck cancer (HNC) can trigger a significant mental health burden, including psychoneurological symptoms (PNS). Better insight into the profiling of PNS is important for advancing personalized mental health screening and management.
Data from 538 newly diagnosed adult HNC patients participating in a prospective multicenter cohort study (NET-QUBIC) were used. Questionnaires were used to assess PNS. Sociodemographic, clinical, lifestyle, and biological variables were collected. Latent class analysis was performed to identify differential classes of PNS. Between-class comparisons and multivariable logistic regression analyses were conducted to characterize each profile in relation to sociodemographic, clinical, lifestyle, and biological variables.
Fit indexes supported a three-class solution, with patients distributed in mild (60%), moderate (26%), and severe (14%) PNS classes. Pain and sleep problems were featured in all classes, anxiety and depression in the moderate and severe classes, and fatigue only in the severe class. Patients in the moderate and severe classes were more often women, had oral cavity cancer, showed impaired performance, had a history of anxiety and depression disorders, were daily smokers, had higher CRP, and had a flatter cortisol slope compared to the mild class.
Newly diagnosed HNC patients can be classified according to the severity of PNS. Several sociodemographic, clinical, lifestyle, and biological variables are proposed as drivers for early detection and treatment of mental health burden.
头颈癌（HNC）会引发重大的心理健康负担，包括精神神经症状（PNS）。深入了解PNS的特征对于推进个性化心理健康筛查和管理至关重要。
使用了来自538名新诊断的成年HNC患者的数据，这些患者参与了一项前瞻性多中心队列研究（NET-QUBIC）。通过问卷调查评估PNS。收集了社会人口统计学、临床、生活方式和生物学变量。进行潜在类别分析以识别PNS的不同类别。进行类别间比较和多变量逻辑回归分析，以根据社会人口统计学、临床、生活方式和生物学变量来描述每个特征。
拟合指数支持三类解决方案，患者分为轻度（60%）、中度（26%）和重度（14%）PNS类别。所有类别都有疼痛和睡眠问题，中度和重度类别有焦虑和抑郁，重度类别仅有疲劳。与轻度类别相比，中度和重度类别的患者女性更多、患有口腔癌、表现受损、有焦虑和抑郁障碍病史、每天吸烟、CRP较高且皮质醇斜率较平缓。
新诊断的HNC患者可根据PNS的严重程度进行分类。提出了几个社会人口统计学、临床、生活方式和生物学变量作为心理健康负担早期检测和治疗的驱动因素。
