Abstract
Purpose
To investigate the frequency of sleep disturbance and its effects on quality of life in adults with untreated primary brain tumors.
Methods
This cross-sectional study recruited 68 and 35 patients with newly diagnosed benign and malignant brain tumors, respectively. All participants completed the Chinese versions of the Athens Insomnia Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Hospital Anxiety and Depression Scale, Brief Fatigue Inventory, and EORTC-QLQ-BN20 for quality-of-life assessment. An actigraph was used to measure sleep parameters [e.g., dichotomy index (I < O)], for at least 3 consecutive days in untreated status.
Results
The majority of the patients with benign and malignant tumors had meningioma (57.4%) and glioblastoma (40%), respectively. The prevalence of insomnia, poor sleep quality, and excessive daytime sleepiness was 59.2%, 77.7%, and 4.9%, respectively. The prevalence rates of sleep disturbances were not affected by tumor locations (suprasellar vs. non-suprasellar tumors) and tumor types (benign vs. malignant tumors). Only 36 participants completed actigraphy assessments (I < O = 95.4) due to having a tight schedule, actigraph malfunction, or not having the habit of wearing a wristwatch; 61% of them experienced circadian rhythm disruption (I < O ≤ 97.5). Insomnia was the only sleep parameter that significantly affected quality of life after controlling for potential confounders (B = 0.54, p = 0.03, adjusted R2 = 0.60).
Conclusion
More than 60% of the patients with primary malignant and benign brain tumors experienced insomnia, poor sleep quality, and circadian rhythm disruption. Insomnia was independently correlated with quality of life in untreated status. Health-care providers can apply these findings to design effective interventions targeting sleep disturbance to improve quality of life in this population.
Supplementary Information
The online version contains supplementary material available at 10.1007/s41105-022-00436-y.
Keywords: Primary brain tumors, Sleep disturbance, Circadian rhythm, Quality of life
Introduction
Sleep disturbance (e.g., insomnia, poor sleep quality, and excessive daytime sleepiness) is a common complaint reported by adults with primary malignant and benign brain tumors at different treatment stages, including the postoperative stage, chemo/radiotherapy stage, and completion and follow-up stages of chemo/radiotherapy [1, 2]. In addition, sleep disturbance is associated with poor quality of life and shorter survival throughout disease and treatment trajectories [1–3]. Therefore, understanding changes that occur in sleep patterns at different treatment stages in patients with primary brain tumor can help health-care providers develop effective strategies targeting critical problems.
Previous studies that have examined sleep disturbance in patients with primary brain tumor have mainly focused on posttreatment and follow-up stages, and few studies have explored sleep disturbance in untreated patients with primary brain tumor [4, 5]. In addition, although sleep disturbance is a common and severe symptom in patients with primary brain tumor [6], most of the previous studies that have investigated sleep disturbance in patients with brain tumor did not compare sleep disruption between patients with brain tumor and healthy controls [6]. Most importantly, patients with malignant brain tumors might experience a higher level of psychological distress (e.g., depression) [7] compared to those with benign brain tumors, which may in turn cause sleep problem in the population [8]. Thus, whether the manifestations of sleep disturbance differ between patients with untreated benign and malignant brain tumors remains unclear. Furthermore, whether tumor location affects the manifestations of sleep disturbance in patients with primary malignant and benign tumors is yet to be determined.
Disruption of rest–activity circadian rhythm is observed in various types of cancer, including breast, colon, and lung [9–11], and is recognized as a clinically relevant circadian biomarker that can be monitored using a wrist-worn actimeter [12]. Disruption in rest–activity circadian rhythm may reduce quality of life and increase mortality in patients with advanced cancer [13–15]. In a recent study, nearly 60% of patients with untreated benign brain tumors reported experiencing rest–activity circadian rhythm disruption [16]. However, whether the same phenomenon is experienced by patients with untreated primary malignant brain tumors remains to be determined.
This study explored whether tumor locations and tumor types affected the manifestations of sleep disturbance and the disruption of rest–activity circadian rhythm. The effect of sleep disturbances on quality of life in adults with untreated primary brain tumors was investigated as well.
Methods
Study design and participants
In this cross-sectional study, participants were selected using convenience sampling. This study was approved by the Institutional Review Boards of Taipei Medical University Hospital (no. N201901028), National Taiwan University Hospital (no. 201812054RINB), and Chang Gung Memorial Hospital (no. 202000470B0). Patients were recruited from two medical centers and one teaching hospital in northern Taiwan between March 2019 and January 2020.
We recruited consecutive patients who were aged between 20 and 65 years, had received a new pathologically confirmed diagnosis of primary benign or malignant brain tumor, had not undergone any treatment targeting brain tumors (i.e., chemotherapy, radiotherapy, craniotomy, and craniectomy), and could communicate in Mandarin or Taiwanese. Participants were excluded if they were shift workers, pregnant, survivors of other types of cancer, or diagnosed as having psychiatric or sleep disorders before the study. Furthermore, participants who underwent surgery or certain treatments not targeting brain tumors were excluded.
Instruments
Demographic and disease characteristics
We collected information on demographic and disease characteristics, namely sex, age, body mass index, education level, marital status, job status, Charlson Comorbidity Index, Karnofsky performance score, type(s) of benign or malignant tumor(s), and use of steroid and antiepileptic drugs. These factors have been associated with sleep disturbance or quality of life in patients with brain tumors [17, 18].
Sleep assessments
We evaluated insomnia symptoms using the Chinese version of the Athens Insomnia Scale (CAIS), which is a self-reported questionnaire used for evaluating insomnia and sleep difficulties over the prior month. This questionnaire comprises two components, namely nighttime and daytime symptoms (items 1–5 and 6–8, respectively), with a total score of ≥ 8 indicating suspected insomnia. The internal consistency (Cronbach’s α = 0.82–0.84) and test–retest reliability (r = 0.84 and 0.86) of the CAIS are satisfactory [19].
Excessive daytime sleepiness was measured using the eight-item Chinese version of the Epworth Sleepiness Scale (CESS). Each item was scored on a 4-point Likert scale ranging from 0 to 3, resulting in a total score of 0–24. A total score of > 10 indicates daytime sleepiness. A previous study reported that the internal consistency (Cronbach’s α = 0.81) and test–retest reliability (r = 0.74, p = 0.001) of the CESS are satisfactory [20].
The Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) was used to assess subjective sleep quality and sleep disturbance over the past month when patients stayed at home. The CPSQI comprises 19 items; each item is scored from 0 to 3, and the sum of these scores ranges from 0 to 21. A score of ≥ 5 indicates poor sleep quality. The CPSQI was reported to have satisfactory internal consistency (Cronbach’s α = 0.82–0.83) and test–retest reliability (r = 0.77–0.85) [21]. Subjective total sleep time (TST), sleep onset latency (SOL), and sleep efficiency (SE) were obtained from the CPSQI.
The Mini Motionlogger Actigraph, a watch-like device, was used to examine objective sleep parameters, namely TST, SOL, wake after sleep onset (WASO), and SE. The normal values for TST, SOL, WASO, and SE for healthy individuals aged 50 years are 400 min (6.67 h), 17 min, 32 min, and 87%, respectively [22]. In addition, rest–activity circadian rhythm [13] was evaluated using the dichotomy index (I < O value; the percentage of in-bed activity counts that are less than the median of out-of-bed counts). The I < O value is an interpretable objective index ranging from 0 to 100 [23]. An I < O value of ≤ 97.5 indicates disruption in rest–activity circadian rhythm [24, 25]. In our study, all participants were asked to wear an actigraph unit for at least 3 consecutive days [9]. A sleep log was used in conjunction with actigraph records.
Quality of life assessment
The Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ-BN20) was used to assess patients’ quality of life. The EORTC-QLQ-BN20, a disease-specific supplement to the EORTC-QLQ-C30, is used to evaluate symptoms specific to treated and untreated brain cancer or related treatment [16, 26]. The EORTC-QLQ-BN20 consists of 20 self‐reported items and is organized into four subscales that address future uncertainty (four items), visual disorder (three items), motor dysfunction (three items), and communication deficits (three items) and seven single‐item scales assessing headache, seizure, drowsiness, itchy skin, hair loss, weakness of legs, and bladder control. All questionnaire items are rated on a 4-point Likert-type scale, and scale scores are linearly transformed to a 0–100 scale, with high scores indicating poor quality of life. The EORTC-QLQ-BN20 was reported to have acceptable internal consistency (Cronbach’s α = 0.75–0.87) [26].
Confounding factors
The Taiwanese version of the Brief Fatigue Inventory (TBFI) was used to assess fatigue severity (nine items) and its interference with daily life (six items) in the past 24 h. The first three items of fatigue severity were rated by patients at its worst, in usual scenarios, and presently within the past 24 h; each item is rated from 0 (no fatigue) to 10 (fatigue as bad as you can imagine). A score of ≥ 7 indicates “severe fatigue,” and scores of 0–6 indicate “nonsevere fatigue.” The next six items describe the extent to which fatigue interfered with general activities, mood, gait, day-to-day work, interpersonal relationships, and enjoyment within the past 24 h; each item is rated from 0 (does not interfere) to 10 (completely interferes). The TBFI was reported to have excellent internal consistency (Cronbach’s α = 0.96 and 0.95) and test–retest reliability (Cronbach’s α = 0.89 and 0.91) for fatigue severity and interference, respectively [27].
The Chinese version of the Hospital Anxiety and Depression Scale consists of 14 items, with seven items each for anxiety and depression. Each item is rated on a 4-point Likert scale (0–3), resulting in a total score of 0–21 points for each domain. A higher score indicates higher severity of depression and anxiety. The scale was reported to have acceptable internal consistency (Cronbach’s α ≥ 0.84) [28].
Statistical analysis
All statistical analyses were performed using SPSS for Windows (version 22.0; IBM Corporation, Armonk, NY, USA). Statistical significance was defined as p < 0.05. Descriptive analyses and frequency distributions were used to estimate demographic and disease characteristics. The independent t test and Chi-square test were used to compare demographic and disease characteristics as well as sleep parameters between the groups. A univariate linear regression model was used to identify variables related to quality of life. After checking for multicollinearity (variance inflation factor < 5) [29], variables with a p value of < 0.05 were selected for further analyses in the multivariate linear regression model to determine the association between sleep disturbance and quality of life after adjustment for possible confounders. We performed a post hoc power analysis using G power 3.1.9.7 [30] after considering an effect size estimated from the variance explained by predictors, a two-tailed α of 0.05, and numbers of predictors.
Results
Participant characteristics
In this study, we enrolled 103 participants (68 and 35 with benign and malignant untreated brain tumors, respectively). All the participants were included in the study within 24 h of receiving a new diagnosis of brain tumor. Only 36 patients with untreated brain tumors (26 with benign and 10 with malignant) completed the 3 consecutive days of actigraphy recording before treatment. Reasons for not completing actigraphy recording were having a tight schedule (n = 50), experiencing actigraph malfunction (n = 7), and not having the habit of wearing a wristwatch (n = 10). No significant difference was observed between the patients who completed and did not complete actigraphy recording (all p > 0.05, Online Appendix 1). The majority of the patients with benign and malignant tumors had meningiomas (57.4%) and glioblastomas (40%), respectively (Table 1). Only 30% of participants had suprasellar tumors. No significant differences in demographic and clinical characteristics were observed between the groups, except for sex, anticonvulsant drug use, and depression level. The malignant tumor group had a higher proportion of men, had a higher proportion of patients using anticonvulsants, and had a higher level of depression than the benign tumor group did (p = 0.001, 0.001, and 0.01, respectively).
Table 1.
Demographic and clinical characteristics of patients with benign and malignant brain tumor (n = 103)
| Characteristics | Benign tumor (n = 68) | Malignant tumor (n = 35) | p | ||
|---|---|---|---|---|---|
| n | % | n | % | ||
| Male | 20 | 29.4 | 24 | 68.6 | 0.001 |
| Age, M (SD) | 49.2 | 11.1 | 47.8 | 12.5 | 0.55 |
| BMI, M (SD) | 24.7 | 4.3 | 24.2 | 3.9 | 0.57 |
| College degree or above | 32 | 47.1 | 15 | 42.9 | 0.69 |
| Married | 58 | 85.3 | 26 | 74.3 | 0.17 |
| Employment | 46 | 67.6 | 26 | 74.3 | 0.49 |
| Charlson Comorbidity Index, M (SD) | 1.1 | 1.2 | 1 | 1.2 | 0.72 |
| KPS score, M (SD) | 89.9 | 3.2 | 88 | 6.8 | 0.13 |
| Steroids use | 2 | 2.9 | 2 | 5.7 | 0.60 |
| Anticonvulsant drug use | 2 | 2.9 | 11 | 31.4 | 0.001 |
| Sedative-hypnotic use | 11 | 16.2 | 3 | 8.6 | 0.37 |
| Type of benign tumor | NA | ||||
| Meningioma | 39 | 57.4 | - | ||
| Pituitary tumor | 27 | 39.7 | - | ||
| Others1 | 2 | 2.9 | - | ||
| Type of malignant tumor | NA | ||||
| Glioblastoma | - | 14 | 40 | ||
| Astrocytoma | - | 7 | 20 | ||
| Anaplastic oligodendroglioma | - | 4 | 11.4 | ||
| Others2 | - | 10 | 28.6 | ||
| WHO grade of brain tumor | NA | ||||
| Grade 1 | 61 | 89.7 | - | ||
| Grade 2 | 7 | 10.3 | 13 | 37.1 | |
| Grade 3 | - | 6 | 17.1 | ||
| Grade 4 | - | 16 | 45.7 | ||
| Tumor location | NA | ||||
| Supratentorial area | 29 | 42.6 | 28 | 80 | |
| Infratentorial area | 2 | 3 | - | ||
| Suprasellar | 31 | 45.6 | 1 | 2.9 | |
| Brain stem | 3 | 4.4 | 4 | 11.4 | |
| Ventricle | - | 2 | 5.7 | ||
| Cerebellopontine angle | 3 | 4.4 | - | ||
| TBFI, M (SD) | 1.9 | 1.8 | 2.7 | 2.4 | 0.10 |
| HADS-anxiety, M (SD) | 5.7 | 3.4 | 6.1 | 3.8 | 0.55 |
| HADS-depression, M (SD) | 4.6 | 3.6 | 6.5 | 3.6 | 0.01 |
M mean, SD standard deviation, BMI body mass index, KPS Karnofsky performance scale, WHO World Health Organization, HADS Hospital Anxiety and Depression Scale, TBFI Taiwanese version of Brief Fatigue Inventory, NA not applicable
Others1: hemangioblastoma, Schwannoma
Others2: anaplastic astrocytoma, anaplastic ependymoma, chordoid glioma, chondrosarcoma, large B cell lymphoma, neurocytoma, oligodendroglioma, pineal tumor
Distribution of self-reported sleep disturbance
The mean scores and prevalence of self-reported sleep outcomes corresponding to tumor type (untreated malignant vs. benign tumors) and tumor location (suprasellar vs. non-suprasellar tumors) are presented in Tables 2 and 3, respectively. The mean scores and prevalence of self-reported sleep outcomes did not significantly differ between the malignant and benign tumor groups or between the suprasellar and non-suprasellar tumor (including brain stem tumor) groups, indicating that neither tumor type nor location affected the manifestations of sleep disturbance in the patients with untreated primary brain tumors. In general, the prevalence of insomnia, poor sleep quality, and excessive daytime sleepiness was 59.2%, 77.7%, and 4.9%, respectively.
Table 2.
Self-reported sleep parameters in benign and malignant brain tumor patients (n = 103)
| Variables | All (n = 103) | Benign (n = 68) | Malignant (n = 35) | p | |||
|---|---|---|---|---|---|---|---|
| CAIS, mean (SD) | 7.8 | (4.7) | 7.5 | (4.1) | 8.3 | (5.7) | 0.49 |
| Insomnia, n (%) | 61.0 | (59.2) | 42 | (61.8) | 19 | (54.3) | 0.46 |
| CPSQI, mean (SD) | 11.0 | (5.5) | 11.1 | (5.3) | 10.8 | (6.1) | 0.79 |
| Poor sleep quality, n (%) | 80 | (77.7) | 55 | (80.9) | 25 | (71.4) | 0.28 |
| CESS, mean (SD) | 2.6 | (3.6) | 2.3 | (3.4) | 3.2 | (3.9) | 0.24 |
| Excessive daytime sleepiness, n (%) | 5 | (4.9) | 3 | (4.4) | 2 | (5.7) | 1.00 |
CAIS Chinese version of Athens Insomnia Scale, CPSQI Chinese version of Pittsburg Sleep Quality Index, CESS Chinese version of Epworth Sleepiness Scale; total sleep time, sleep onset latency, and sleep efficiency were derived from the reports of the CPSQI. Insomnia was determined if the score of CAIS ≥ 8. Poor sleep quality was defined if the score of CPSQI > 5. Excessive daytime sleepiness was identified if the score of CESS > 10
Table 3.
Comparison of sleep disturbances manifestations between patients with suprasellar tumors and non-suprasellar (including brain stem tumor) tumors (n = 103)
| Characteristics | Suprasellar tumor (n = 31) | Non-suprasellar tumor (n = 67) | p | ||
|---|---|---|---|---|---|
| Mean | (SD) | Mean | (SD) | ||
| CAIS, mean (SD) | 7.4 | (3.9) | 7.9 | (5.1) | 0.55 |
| Insomnia, n (%) | 20 | (62.5) | 41 | (57.7) | 0.67 |
| CPSQI, mean (SD) | 11.5 | (5.1) | 10.7 | (5.8) | 0.52 |
| Poor sleep quality, n (%) | 28 | (87.5) | 52 | (73.2) | 0.13 |
| CESS, mean (SD) | 2.3 | (3.1) | 2.7 | (3.8) | 0.60 |
| Excessive daytime sleepiness, n (%) | 1 | (3.1) | 4 | (5.6) | 0.50 |
CAIS Chinese version of Athens Insomnia Scale, CPSQI Chinese version of Pittsburg Sleep Quality Index, CESS Chinese version of Epworth Sleepiness Scale; total sleep time, sleep onset latency, and sleep efficiency were derived from the reports of the CPSQI. Insomnia was determined if the score of CAIS ≥ 8. Poor sleep quality was defined if the score of CPSQI > 5. Excessive daytime sleepiness was identified if the score of CESS > 10
Distribution of objective sleep parameters
Objective sleep parameters are listed in Table 4. A total of 36 participants with brain tumors (26 benign and 10 malignant) completed the actigraphy assessment. The mean values for TST, SOL, SE, and WASO were 374.2 min, 4.4 min, 92.5%, and 31.6 min, respectively. The four sleep parameters did not significantly differ between the benign and malignant groups (all p > 0.05). The prevalence of circadian rhythm disruption (I < O value ≤ 97.5) was higher in the malignant tumor group (70%) than in the benign tumor group (57.7%); however, the difference was not statistically significant (p = 0.71). No participant had tumors located nearby sella.
Table 4.
Distribution of objective sleep parameters measured by actigraphy (n = 36)
| Variables | ALL (n = 36) | Benign (n = 26) | Malignant (n = 10) | p | |||
|---|---|---|---|---|---|---|---|
| Mean | (SD) | Mean | (SD) | Mean | (SD) | ||
| Total sleep time (min) | 374.2 | (124.8) | 386.0 | (126.8) | 343.8 | (120.5) | 0.53 |
| Sleep onset latency (min) | 4.4 | (2.6) | 4.1 | (2.4) | 5.2 | (2.9) | 0.66 |
| Sleep efficiency (%) | 92.5 | (4.1) | 93 | (3.3) | 91.2 | (5.7) | 0.51 |
| Wake after sleep onset (min) | 31.6 | (16.2) | 32.1 | (16.7) | 30.4 | (15.5) | 0.86 |
| Dichotomy I < O value | 95.4 | (6.1) | 96 | (5.3) | 93.7 | (7.9) | 0.75 |
| I < O ≤ 97.5, n (%) | 22 | (61.1) | 15 | (57.7) | 7 | (70.0) | 0.71 |
Mann–Whitney U test and Chi-square tests were used to perform the analyses. I < O ≤ 97.5 indicates having circadian disruption
Association between sleep disturbances and quality of life
The distribution of quality of life scores in the patients with untreated benign and malignant brain tumors is presented in Online Appendix 2. Headache and future uncertainty were the most common complaints in both groups. Overall, the global score of the malignant group was significantly higher than that of the benign group (18.4 vs. 10.3, p = 0.004), indicating that quality of life was more impaired in the patients with malignant brain tumors than in those with benign brain tumors.
Because only a small number of patients completed actigraphy recording, objective sleep data were not included in regression models. The univariate linear regression model suggested that steroid use, brain tumor type (malignant), physical performance status, insomnia, excessive daytime sleepiness, poor sleep quality, fatigue, anxiety, and depression were associated with quality of life (all p < 0.05), and these were sequentially entered into a multivariate linear regression model (Table 5). After adjustment for age, sex, and significant confounding factors, the patients with untreated malignant brain tumors were determined to have poorer quality of life than did those with untreated benign tumors (p = 0.02). Insomnia (B = 0.54, p = 0.03) was the only sleep variable independently correlated with quality of life in the patients with untreated benign and malignant brain tumors after adjustment for potential confounders (adjusted R2 = 0.60).
Table 5.
The univariate and multivariate linear regression models of quality of life (n = 103)
| Variables | Univariate | Multivariate | ||||||
|---|---|---|---|---|---|---|---|---|
| B | SE | 95% CI | p | B | SE | 95% CI | p | |
| Female | − 2.90 | 2.26 | − 7.38 to 1.59 | 0.20 | − 0.02 | 1.61 | − 3.22 to 3.17 | 0.99 |
| College degree or above | − 1.69 | 2.26 | − 6.17 to 2.78 | 0.46 | ||||
| Married | − 1.72 | 2.90 | − 7.48 to 4.03 | 0.55 | ||||
| Employment | − 2.44 | 2.44 | − 7.29 to 2.41 | 0.32 | ||||
| Recurrent | − 1.66 | 3.99 | − 9.56 to 6.25 | 0.68 | ||||
| Steroids use | 13.72 | 5.67 | 2.47 to 24.96 | 0.02 | 10.51 | 3.88 | 2.81 to 18.2 | 0.01 |
| Anticonvulsant drug use | 3.27 | 3.38 | − 3.43 to 9.97 | 0.34 | ||||
| Sedative-hypnotic use | 5.63 | 3.24 | − 0.80 to 12.05 | 0.09 | ||||
| Malignant brain tumor | 8.03 | 2.24 | 3.59 to 12.48 | 0.001 | 4.27 | 1.72 | 0.86 to 7.69 | 0.02 |
| Suprasellar tumor | 3.21 | 3.33 | − 3.48 to 9.98 | 0.36 | ||||
| Age | 0.01 | 0.10 | − 0.18 to 0.21 | 0.92 | 0.06 | 0.07 | − 0.07 to 0.2 | 0.35 |
| BMI | − 0.18 | 0.27 | − 0.72 to 0.37 | 0.52 | ||||
| CCI | 0.31 | 0.97 | − 1.61 to 2.24 | 0.75 | ||||
| KPS | − 0.80 | 0.22 | − 1.24 to − 0.36 | 0.001 | − 0.3 | 0.17 | − 0.63 to − 0.03 | 0.07 |
| CAIS | 1.42 | 0.19 | 1.03 to 1.80 | 0.001 | 0.54 | 0.24 | 0.07 to 1.02 | 0.03 |
| CESS | 1.17 | 0.30 | − 9.56 to 6.25 | 0.001 | 0.25 | 0.24 | − 0.23 to 0.74 | 0.3 |
| CPSQI | 0.82 | 0.19 | 0.45 to 1.19 | 0.001 | 0.12 | 0.18 | − 0.25 to 0.48 | 0.52 |
| BFI | 2.68 | 0.48 | 1.73 to 3.63 | 0.001 | 0.67 | 0.47 | − 0.26 to 1.61 | 0.16 |
| HADS-anxiety | 1.62 | 0.28 | 1.07 to 2.18 | 0.001 | 0.45 | 0.28 | − 0.09 to 1.0 | 0.1 |
| HADS-depression | 1.92 | 0.24 | 1.44 to 2.40 | 0.001 | 0.89 | 0.28 | 0.34 to 1.43 | 0.002 |
The final multivariable linear regression model yielded adjusted R2 = 0.6, p = 0.001
BMI body mass index, CCI Charlson comorbidity index, KPS Karnofsky performance scale, B B coefficient (slope) of linear regression model, CI confidence interval, CAIS Chinese version of the Athens Insomnia Scale, CESS Chinese version of the Epworth Sleepiness Scale, CPSQI Chinese version of the Pittsburg Sleep Quality Index, TBFI Taiwanese version of Brief Fatigue Inventory, HADS Hospital Anxiety and Depression Scale
After considering an effect size of 0.3, derived from the variance explained by predictors (0.6), a two-tailed α of 0.05, and numbers of predictors (k = 9), a post hoc power of 0.98 was suggested.
Discussion
Similar to the finding of a previous population-based study [31], this study demonstrated that patients with untreated benign and malignant brain tumors complained of sleep disturbance at the untreated stage; specifically, the patients had a high prevalence of self-reported insomnia and poor sleep quality. In patients with brain tumors, the disruption of sleep–wake patterns (e.g., excessive daytime sleepiness and insomnia) is associated with major dysfunction in the hypothalamic–pituitary axis [32], which can disrupt the secretion of cortisol, melatonin, and orexin. Furthermore, tumors invading the third ventricle may affect the regulation of core body temperature, resulting in a dysregulated sleep–wake cycle [33].
Psychologically predisposing factors, such as depression and anxiety, may contribute to sleep disturbance in patients with untreated brain tumors [26]. The findings of our study regarding the psychological relationship between mood and sleep disturbance in patients with untreated malignant and benign tumors were contradictory, with results for the patients with untreated malignant brain tumors supporting a positive association and those for the patients with untreated benign brain tumors disproving the association. Because the exact underlying mechanism could not be ascertained in the current study, future studies on this topic are warranted.
Our results revealed that the manifestations of sleep disturbance in the patients with untreated brain tumors were similar between the suprasellar and non-suprasellar tumor groups. This finding indicates that tumor location may not affect the manifestations of sleep disturbance in patients with untreated primary malignant and benign brain tumors. This finding agrees with that of a previous study [16]. Previous studies have demonstrated that the presence of a tumor near the sella (e.g., the hypothalamus or third ventricle) may increase the risk of sleep disturbance in patients with brain tumors [33, 34]. The discrepancy between our findings and those of previous studies might be because the patients in our study did not undergo invasive surgery.
The I < O value is recognized as a biomarker of rest–activity circadian rhythm [12]. Our findings revealed that 70% and 57.7% of patients with malignant and benign tumors, respectively, experienced circadian rhythm disruption in untreated status; these rates are considerably higher than those reported for other advanced cancers (ranging from 31.3 to 54.9%) [12]. In addition, a recent scoping review suggested that circadian rhythm disruption is linked to not only physical and psychological symptoms (e.g., fatigue, appetite loss, pain, and depression) but also low quality of life and survival [12]. Thus, health-care providers should provide timely and effective interventions that target circadian rhythm disruption in patients with untreated brain cancer to optimize recovery in this population.
We determined that only 5.7% and 4.4% of patients with malignant and benign brain tumors, respectively, experienced excessive daytime sleepiness before any treatment; these rates are considerably lower than those reported previously (25–70%) [2, 31]. One of the reasons for the discrepancy between our findings and those of previous studies is the type of cancer-related treatment received by the patients; a previous study reported that > 90% of the patients with primary brain tumors who underwent cranial radiation therapy experienced excessive daytime sleepiness [4]. Cranial radiation therapy may affect melatonin and hypocretin (orexin) secretion, thus contributing to excessive daytime sleepiness in patients with brain tumors [35]. This is the first study to report a low frequency of excessive daytime sleepiness in patients with untreated malignant and benign brain tumors, and further investigation is required to verify our findings.
Although previous studies have suggested that insomnia is associated with poor quality of life, increased risks of incident cardiocerebral vascular diseases, and mortality in cancer survivors [36–38], knowledge regarding this association in patients with brain tumors is still limited. Our study revealed that self-reported insomnia is the only sleep parameter associated with quality of life in patients with untreated primary brain tumors. Patients with brain cancer who have insomnia may experience impaired neuropsychological functioning, which may subsequently affect their work productivity and the return-to-work process, leading to poor quality of life [39]. Programs aimed at improving sleep quality and quantity should be implemented to help patients with primary brain tumors to improve or maintain their quality of life as much as possible.
Limitations
Although we adopted standardized, multifaceted sleep assessments to evaluate sleep disturbance in the patients with untreated malignant and benign brain tumors, our study still has several limitations. First, we enrolled patients from only three medical centers in northern Taiwan, limiting the external generalizability of our findings. Second, this study used self-reported questionnaires to evaluate sleep disturbance in the patients with untreated brain tumors; this may limit the internal validity of our findings. Future studies should use objective sleep measures to verify our data. Third, only approximately one-third of the participants completed the actigraphy assessment; this may compromise the internal validity of objective sleep data. Future studies are warranted to examine the effect of the dichotomy index on quality of life. Fourth, the effects of tumor size on the manifestations of sleep disturbance could not be examined due to a lack of data on tumor size for all the participants. Future studies should investigate the effect of tumor size on sleep disturbance. Finally, our patients, particularly those with malignant brain tumors, reported their sleep manifestations within 24 h of receiving a brain tumor diagnosis, which may, in turn, influence their sleep perception and misestimate their quality of life. Our data should be interpreted with caution.
Conclusion
The current study determined that the prevalence of insomnia, poor sleep quality, and excessive daytime sleepiness was 59.2%, 77.7%, and 4.9%, respectively, in patients with primary brain tumors. Approximately 60% of the patients with primary brain tumors experienced circadian rhythm disruption. Insomnia was the only sleep parameter that was independently correlated with quality of life. Additional research on adults with untreated benign or malignant tumors is required to determine the association between sleep disturbance and tumor histology. Future studies should explore sleep trajectory before and after treatment in patients with benign or malignant tumors.
Supplementary Information
Below is the link to the electronic supplementary material.
Author contributions
Each author made a substantive intellectual contribution to the study. P-CL, H-YC, and P-YC: conceptualization and study design, data collection, data analysis, data interpretation, manuscript writing, and approval of the final manuscript as submitted. K-CW and J-HL: data collection and interpretation and approval of the final manuscript as submitted. M-RL and H-CW: data collection and approval of the final manuscript as submitted.
Funding
This study was supported by grants from Chang Gung Memorial Hospital (CMRPG2K0251 and CLRPG2L0051) and the Ministry of Science and Technology, Taiwan (MOST 111-2628-B-038-008 and 111-2314-B-038-033-MY3).
Data availability
Data supporting the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Conflict of interest
The authors declare no potential conflict of interest regarding the authorship and publication of this article.
Ethical committee permission (includes permission number, if applicable)
This study was approved by the Institutional Review Boards of Taipei Medical University Hospital (no. N201901028), National Taiwan University Hospital (no. 201812054RINB), and Chang Gung Memorial Hospital (no. 202000470B0).
Research involving human participants and/or animals
The study involved human participants and was approved by the ethics committee.
Informed consent (if applicable)
Written informed consent was obtained from all the participants before study initiation.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Pei-Ching Lin and Pin-Yuan Chen contributed equally to the work.
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Data Availability Statement
Data supporting the findings of this study are available from the corresponding author upon reasonable request.