Specific sleep disorders have been linked to disease progression in different cancers.We hypothesised sleep symptom clusters would differ between cancer types. The aim of this study was to compare sleep symptom clusters in post-treatment melanoma, breast and endometrial cancer patients. Data were collected from 124 breast cancer patients (1 male, 60 ± 15 years, 28.1 ± 6.6 kg/m 2 ), 82 endometrial cancer patients (64.0 ± 12.5 years, 33.5 ± 10.4 kg/m 2 ) and 112 melanoma patients (59 male, 65.0 ± 18.0 years, 29.1 ± 6.6 kg/m 2 ). All patients completed validated questionnaires to assess sleep symptoms, including the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Functional Outcomes of Sleep Questionnaire-10 (FOSQ-10). Snoring, tiredness, observed apneas, age, BMI, and gender data were also collected. Binary values (PSQI, ISI, FOSQ), or continuous variables for sleepiness (ESS) and perceived sleep quality (PSQI), were created and sleep symptom clusters were identified and compared across cancer cohorts. Four distinct sleep symptom clusters were identified: minimally symptomatic (n = 152, 47.7%); insomnia-predominant (n = 87, 24.9%); very sleepy with upper airway symptoms (n = 51, 16.3%), and severely symptomatic with severe dysfunction (n = 34, 11.1%). Breast cancer patients were significantly more likely to be in the insomnia predominant or severely symptomatic with severe dysfunction clusters, whereas

Background and aims: For cancer patients, comorbid obstructive sleep apnea (OSA) poses additional risk to their surgical/anaesthetic outcomes, quality of life, and survival. However, OSA screening is not well-established in oncology settings. We tested two screening tools (STOP-Bang questionnaire [SBQ] and the at-home monitoring device, ApneaLink™Air), for predicting polysomnography (PSG) confirmed OSA in post-treatment cancer patients.Methods: Breast (n = 56), endometrial (n = 37) and melanoma patients (n = 50) were recruited from follow-up clinics at Westmead Hospital (Sydney, Australia). All underwent overnight PSG, 137 completed SBQ, and 99 completed ApneaLink™Air. Positive (PPV) and negative (NPV) predictive values for PSG-determined moderate-to-severe OSA and severe OSA, were calculated using an SBQ threshold ≥3 au and ApneaLin-k™Air apnoea-hypopnea index thresholds of ≥10, ≥15 and ≥30 events/h.Results: Both SBQ and ApneaLink™Air had high NPVs (92.7% and 85.2%-95.6% respectively) for severe OSA, but NPVs were lower for moderate-to-severe OSA (69.1% and 59.1%-75.5%, respectively). PPV for both tools were relatively low (all <73%). Combining both tools did not improve screening performance.Conclusions: These screening tools may help identify cancer patients without severe OSA, but both are limited in identifying those with moderate-to-severe or severe OSA. PSG remains optimal for adequately identifying and managing comorbid OSA in cancer patients.