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

Abstract

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Cancer; Chemotherapy; Circadian rhythm; Sleep; Sleep disruption.

Fig. 1

Patient flow chart. Illustration of the patient inclusion process and how many patients were used in the different types of analysis presented in this study. SQ, sleep quality; DTS, daytime sleepiness.

Fig. 2

Ordinal factor and Rasch analyses identify SQ and DTS as the most important outputs from the MOS-SS scale. A) Cartoon illustrating the process of data collection and initial organization prior to further analysis. B) Scree plot of the Eigenvalue (mathematical significance requires an Eigenvalue > 2) of factors that may explain the variance in the data from patient-reported values to the MOS-SS. C) Proportion of the total variance in the data from patient-reported values to the MOS-SS explained by an increasing number of the factors identified in (B). D, E) Distribution of SQ (corresponding to Factor 1 in (B) and (C)) scores (D) and DTS (corresponding to Factor 2 in (B) and (C)) scores (E) among patients at the time om inclusion, prior to treatment onset (baseline) or following three months of oncological therapy (follow-up). F, G) Person-Item location distributions and Item Threshold Distributions derived from the Rasch analysis indicating the number (left axes) or frequency (right axes) of persons or items respectively found at each location within the SQ data (F) or DTS data (G). MOS-SS, medical outcomes study–sleep scale; SQ, sleep quality; DTS, daytime sleepiness.

Fig. 3

Correlation of SQ and DTS against other sleep scales and clinical data. A, B) Graph showing the association between SQ (A) or DTS (B) and the SLP9 sub-scale from the MOS Sleep Scale questionnaire at baseline (blue circles) and three months follow-up (orange squares). Each patient is represented by a blue and an orange data point in the graph. The correlation is significant at P ​< ​0.001 for both SQ (R² ​= ​0.91 and 0.95) and DTS (R² ​= ​0.13 and 0.13) and at both baseline and follow-up respectively. C) Graph showing the association between the change in SQ and change in DTS from baseline to follow-up. No statistically significant correlation was found (P ​> ​0.05, R² ​= ​0.040). D, E) Box plots showing the average SQ or DTS at baseline for patients reporting poor sleep (Sleep 1, orange boxes, n ​= ​17) compared to good sleep (Sleep 0, blue boxes, n ​= ​56) in D or for patients taking sleep medication (orange boxes, n ​= ​17) compared to not taking sleep medication (blue boxes, n ​= ​53) in E. F) Box plots showing the average change in SQ or DTS between baseline and follow-up for patients taking sleep medication (orange boxes, n ​= ​17) compared to not taking sleep medication (blue boxes, n ​= ​53). NS: non-significant, ∗∗: P ​< ​0.01, ∗∗∗: P ​< ​0.001. G-L) Box plots showing average SQ (G–I) or DTS (J–L) in patients reporting a 1 (orange boxes, n ​= ​15, 35, 11 at baseline and n ​= ​8, 40, 6 at follow-up), 2 (blue boxes, n ​= ​37, 27, 40 at baseline and n ​= ​39, 16, 33 at follow-up), 3 (green boxes, n ​= ​19, 9, 20 at baseline and n ​= ​18, 9, 24 at follow-up), or 4 (purple boxes, n ​= ​2, 2, 2 at baseline and n ​= ​4, 4, 5 at follow-up) to questions 10 (G, J), 11 (H, K) or 18 (I, L) of the EORTC-QLQ30 instrument at either baseline or follow-up. NS: non-significant, ∗: P ​< ​0.05, ∗∗: P ​< ​0.01, ∗∗∗: P ​< ​0.001. MOS-SS, medical outcomes study–sleep scale; SQ, sleep quality; DTS, daytime sleepiness; EORTC-QLQ30, 30 item European organization for research and treatment of cancer-quality of life.

Fig. 4

SQ and DTS are not correlated to levels of molecular biomarkers of sleep or circadian disruption in patients with cancer. A, B) Graphs showing the association between SQ (A) or DTS (B) levels and urinary relative levels of melatonin to creatinine (blue circles) or cortisol to creatinine (orange circles) at baseline or follow-up. Each patient is represented by a data point in each graph. C, D) Graphs showing the association between SQ (C) or DTS (D) levels and relative mRNA levels of Bmal1 to Gdpa (blue circles) or Per2 to Gdpa (orange circles) in blood leucocytes at baseline or follow-up. Each patient is represented by a data point in each graph. E, F) Graphs showing the association between SQ (E) or DTS (F) levels and serum levels of CRP (blue circles) or IL-2 (orange circles) at baseline or follow-up. Each patient is represented by a data point in each graph. There are no statistically significant correlations in any of the data sets (P-values indicated in each graph). SQ, sleep quality; DTS, daytime sleepiness; CRP, C-reactive protein; IL, interleukin.

Fig. 5

Correlation between SQ or DTS and demographic or clinical parameters in patients with cancer. A-D) Graphs showing the association between SQ (A, C) or DTS (B, D) and BMI (A, B) or Age (C, D) at baseline (blue circles) or follow-up (orange circles). Each patient is represented by a blue and an orange circle in each graph. There are no statistically significant correlations in any of the data sets (P ​> ​0.05). E, F), Box plots showing the average SQ (E) or DTS (F) levels for patients identifying as male (n ​= ​44) or female (n ​= ​26) at baseline (blue boxes) or follow-up (orange boxes). ∗: P ​< ​0.05. G, H), Box plots showing the average SQ (G) or DTS (H) levels for patients receiving adjuvant (Ad, n ​= ​25) or palliative (Pal, n ​= ​45) therapy at baseline (blue boxes) or follow-up (orange boxes). I, J), Box plots showing the average SQ (I) or DTS (J) levels for patients diagnosed with colorectal (C, n ​= ​31), gastric (G, n ​= ​19), urological (U, n ​= ​11), or breast (B, n ​= ​11) cancer at baseline (blue boxes) or follow-up (orange boxes). ∗: P ​< ​0.05. K, L), Box plots showing the average SQ (K) or DTS (L) levels for patients treated with therapies containing 5-FU (5, n ​= ​25), any -citabine (C, n ​= ​25), any taxane (T, n ​= ​11), or other (O, n ​= ​13) medical therapy at baseline (blue boxes) or follow-up (orange boxes). ∗: P ​< ​0.05. SQ, sleep quality; DTS, daytime sleepiness; BMI, body mass index.