Profiling of psychoneurological symptoms in newly diagnosed head and neck cancer patients.

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.