# Development and validation of a clinical sleep assessment tool for patients with cancer during treatment

## TL;DR

This study develops a tool to assess sleep issues in cancer patients, identifying two key factors that can help improve their care and quality of life.

## Contribution

The study introduces two new factors—Sleep Quality and Daytime Sleepiness—for assessing sleep disruption in cancer patients.

## Key findings

- Sleep Quality and Daytime Sleepiness factors were strongly linked to sleep-related impairments in cancer patients.
- The factors showed no correlation with tested biomarkers like melatonin, cortisol, or gene expression.
- A simplified scoring tool was developed for practical use in clinical oncology settings.

## Abstract

Sleep disruption is common among patients with cancer, negatively impacting treatment outcomes, survival, and quality of life. However, it is often overlooked in cancer care. This study aimed to explore shared characteristics of sleep disruption in patients with cancer to facilitate simple and accurate identification in routine clinical practice. A secondary aim was to identify potential biomarkers in urine, serum, or leukocytes associated with sleep disruption before and/or after oncological therapy.

Ninety cancer patients scheduled for either adjuvant or palliative oncological therapy at Ryhov County Hospital, Jönköping, Sweden, were consecutively enrolled. Of these, 72 completed all questionnaires and provided urine and blood samples at both baseline and three-month follow-up. Data were collected using the 12-item Medical Outcomes Study Sleep Scale (MOS-SS) and the 30-item European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Biomarker analysis was conducted on urine and blood samples, and data were analyzed using ordinal factor and Rasch modeling.

Two distinct factors—Sleep Quality (SQ) and Daytime Sleepiness (DTS)—emerged from the MOS-SS, effectively capturing key aspects of sleep disruption. Both SQ and DTS were strongly associated with sleep-related impairments identified via the EORTC QLQ-C30 and clinical history, but showed no correlation with urinary melatonin or cortisol, serum inflammatory cytokines, or Bmal1 and Per2 gene expression in blood leukocytes. Neither SQ nor DTS was significantly influenced by patient age, body mass index (BMI), or oncological therapy. However, women reported significantly lower DTS compared to men (P ​< ​0.05), while SQ remained unaffected by sex. A simplified scoring tool for SQ and DTS was developed for practical use in clinical oncology settings.

This study identifies SQ and DTS as robust measures of sleep quality and daytime sleepiness in cancer patients. These new factors derived from the MOS-SS can support the early detection and management of sleep disruption in routine oncological care.