Relationship Between Cortisol Rhythm and Psychoneurological Symptom Cluster in Patients With Advanced Lung Cancer.

Abstract

Patients with advanced lung cancer commonly experience a high prevalence of physical and psychological symptoms, which tend to co-occur as a symptom cluster. Cortisol rhythm has the potential to influence psychoneurological symptom cluster based on neuroendocrine-immune models; however, little is known about the relationship between them. To examine the intercorrelation among symptoms in psychoneurological symptom cluster and the factors influencing the severity of psychoneurological symptom cluster. One hundred sixty-one patients with advanced lung cancer were recruited from 2018 to 2020 as part of a large study. Data on sleep disturbances, fatigue, and psychological distress were collected via self-report questionnaires, and the diurnal cortisol slope was analyzed using saliva samples. Linear regression analyses were adopted to examine the association between cortisol rhythm and demographic and clinical variables with psychoneurological symptom cluster. Psychoneurological symptoms (including sleep disturbances, fatigue, anxiety, and depression) were significantly correlated. Poor physical performance status (β = -0.061, P < .001), increased number of comorbidities (β = 0.533, P < .001), and flatter cortisol rhythm (β = 545.092, P < .001) were significantly associated with higher-severity psychoneurological symptom cluster. Diurnal cortisol slope (β = 328.829, P = .025) was identified as the most critical factor influencing the psychoneurological symptom cluster in multiple linear regression model after adjusting for covariates. Patients with flatter diurnal cortisol slopes were found to experience more severe psychoneurological symptom cluster, after controlling for demographic and clinical factors. Interventions targeting the improvement of associated factors, such as comorbidities and physical performance status, could potentially alleviate the severity of the psychoneurological symptom cluster.