COVID-19 pandemic stress and cancer symptom burden
Ce dossier présente un ensemble d'articles concernant la prise en charge des cancers durant la crise sanitaire liée à la COVID-19
Résumé en anglais
Objectives: In a sample of patients with cancer (n=1145) who were assessed during the height of the COVID-19 pandemic, latent profile analysis was used to identify subgroups of patients with distinct stress profiles and to evaluate for differences in demographic and clinical characteristics and symptom severity scores among these subgroups.
Methods: Patients completed measures of cancer-specific and COVID-19 stress, global stress, social isolation, loneliness, depression, state and trait anxiety, morning and evening fatigue, morning and evening energy, sleep disturbance, cognitive function, and pain. Latent profile analysis was used to identify subgroups of patients with distinct stress profiles. Differences among the subgroups in study measures were evaluated using parametric and non-parametric tests.
Results: Using clinically meaningful cut-off scores for the stress measures, four distinct stress profiles were identified (ie, none class (51.3%); low stress and moderate loneliness class (24.4%), high stress and moderate loneliness class (14.0%), and very high stress and moderately high loneliness class (high, 10.3%)). Risk factors associated with membership in the high class included: younger age, lower annual household income, lower functional status and higher comorbidity burden. The two worst stress profiles reported clinically meaningful levels of all of the common symptoms associated with cancer and its treatments.
Conclusion: Findings from this study, obtained prior to the availability of COVID-19 vaccines and anti-viral medications, provide important ‘benchmark data’ to evaluate for changes in stress and symptom burden in patients with cancer in the postvaccine era and in patients with long COVID-19.Data are available on reasonable request. Data are available on request to the corresponding author after a material transfer agreement is signed with the University of California, San Francisco.
