Sleep Quality,Fatigue,and Quality of Life Among Teenage and Young Adult Cancer Survivors

Abstract

Purpose:

Teenage and young adult (TYA) cancer survivors experience a range of health-related problems during and beyond the active treatment period. This study examined associations between fatigue, sleep quality, and health-related quality of life (HRQOL) among TYA survivors.

Methods:

Self-reported data on sleep quality (Pittsburgh Sleep Quality Index), fatigue (Functional Assessment of Chronic Illness Therapy Fatigue), and HRQOL (EuroQoL-5) were gathered from United Kingdom TYA survivors between 13 and 24 years of age. TYA survivors were stratified into those on (n = 67) and off (n = 135) treatment. Linear regression analyses were used with HRQOL as the dependent variable to investigate potential associations. Fatigue and sleep were entered separately and together in the same model. Age at survey and diagnosis, gender, and ethnicity were included as covariates.

Results:

85.07% of TYAs on and 62.69% of TYAs off treatment had sleep quality scores suggestive of clinically significant sleep disorders. 56.72% of TYAs on and 26.67% of TYAs off treatment reported clinically significant levels of fatigue. Strong independent associations between sleep (B = 0.05, 95% confidence intervals [CI] = 0.03–0.07, p < 0.001), fatigue (B = 0.02, 95% CI = 0.01–0.03, p < 0.001), and HRQOL were observed among TYA survivors on treatment. TYAs off treatment showed moderate to strong associations between sleep (B = 0.04, 95% CI = 0.02–0.05, p < 0.001) and fatigue (B = 0.02, 95% CI = 0.01–0.02, p < 0.001), and HRQOL, when examined separately. Sleep was not independently associated with HRQOL among TYAs off treatment (B = 0.01, 95% CI = −0.01 to 0.02, p = 0.296).

Conclusion:

The significant associations reported suggest that sleep quality and fatigue are potential modifiable factors associated with HRQOL. Further research is warranted to understand the direction of associations.

Introduction

Each day seven young people between 13 and 24 years (teenage and young adult [TYA]) of age are diagnosed with cancer in the United Kingdom.¹ Advances in cancer therapies mean the 5-year survival rate among TYAs is now >80%.² However, TYA survivors suffer significant impairments in health-related quality of life (HRQOL) throughout and after treatment,^3,4 including psychosocial and physical limitations experienced up to ten years after treatment.⁵ Identifying potential modifiable factors associated with on and off treatment HRQOL in TYA survivors is important as targeting these in interventions may in the long-term improve outcomes in this population.

More recently, there has been an increasing interest in fatigue.⁶ Fatigue is defined as “a subjective, unpleasant symptom, which incorporates total body feelings ranging from tiredness to exhaustion creating an unrelenting overall condition, which interferes with individuals' ability to function to their normal capacity.”⁷ Fatigue experienced by cancer survivors that is, cancer-related fatigue (CRF), is often of greater magnitude, disproportionate to activity levels, and cannot be resolved through resting.⁸ CRF may be caused by tumor-related productions of cytokines, pain and neuroendocrine factors, and by medication and treatment.^9,10 A review of mainly quantitative observational cross-sectional and longitudinal studies suggests that CRF is the most prevalent symptom of TYA cancer treatment,⁶ with more than 75% of cancer patients reporting the condition.¹¹ Across 22 studies included in the review, CRF was found to often result in distress, and to impact on TYA survivors' cognitive and physical function.⁶ However, findings are limited in strength, as the studies conducted were of relatively low quality,⁶ and often evaluated fatigue mainly as a subcomponent of more general measures, such as the Memorial Symptom Assessment Scale Short Form (MSAS-SF).¹² Nevertheless cross-sectional studies involving survivors of childhood cancer and adult cancer survivors provide evidence for associations between CRF and HRQOL. Fatigue was found to be associated with poorer physical and psychosocial functioning in 86 survivors (age range = 8–18 years) of childhood cancer on average 7.8 years after treatment,¹³ and with poorer HRQOL in 954 adult cancer patients with mixed cancer diagnoses.¹⁴

While interest in investigating fatigue among TYA survivors has been increasing, there has been less emphasis on sleep quality. In general, engagement in poor sleep hygiene behaviors means many young people suffer from sleep problems.¹⁵ Among TYA survivors poor sleep may be associated both with increased fatigue and impaired HRQOL. Sleep problems in cancer survivors may arise as a direct effect of the cancer, and be caused by indirect effects, including aspects of poor HRQOL, such as pain and anxiety.¹⁶ Within one small longitudinal study of 20 TYAs receiving chemotherapy (mean age = 16.12 years) significant associations were found between poor sleep quality and poor cancer-related quality of life, including cognitive problems, pain, and anxiety.¹⁷ Another study found significant associations between poor sleep and impaired HRQOL in a sample of 61 TYA survivors (age range = 12–25 years) who had finished all treatment (r = −0.57, p > 0.001).¹⁸ Poor sleep quality was also correlated with bodily pain and impaired vitality, in a sample of 72 adult breast cancer survivors.¹⁹ Additionally, poor sleep in TYA survivors often occurs simultaneously with fatigue,²⁰ and the adult literature suggests a reciprocal relationship.¹²

Given that adolescence and young adulthood are characterized by unique psychosocial developmental changes, including increasing independence and transitions in school and work settings, good HRQOL is important. Thus, it is essential to explore potential modifiable factors associated with poor HRQOL in TYA survivors. Fatigue and poor sleep quality are suggested as such factors. However, findings that indicate associations within the TYA survivor population are limited in reliability, as studies suggesting an association between fatigue and HRQOL have mainly been of low quality⁶ and studies investigating sleep quality used predominantly small sample sizes.¹⁷ Furthermore, TYA survivors are a unique group in terms of tumor type and prognosis.²¹ While the majority of TYA survivors receive their cancer diagnosis during adolescence or young adulthood, survivors of childhood cancer will have been diagnosed during childhood. Evidence coming from this group or adult cancer survivors therefore cannot be directly extrapolated to TYA-aged survivors. Using distinct and detailed measures, the aim of this study was therefore to examine associations between sleep quality and fatigue, and HRQOL in a large sample of TYA survivors. It was hypothesized that there are associations between sleep quality and fatigue, and HRQOL in the TYA survivor population.

Methods

Study design, procedure, and participants

In 2015–2016 TYA survivors were recruited to participate in a cross-sectional survey study investigating their health behaviors, well-being, and interest in lifestyle advice. Detailed information regarding the recruitment procedure can be found in a previous publication.²² TYA survivors were eligible if they had a diagnosis of cancer at any point within their lifetime; have had, have, or were going to receive active treatment for their cancer; were between 13 and 24 years of age; were living in the United Kingdom during the time of data collection; and understood spoken and written English. TYAs with terminal cancer, receiving palliative care, or unable to provide consent themselves were excluded from the study. Interested participants were given an information sheet outlining the purpose of the study. All eligible TYAs could consent themselves independent of their age; interested young people were assumed to have Gillick competence.²³ Participants who agreed to participate were offered either a paper version of the survey, or a link, where it could be completed online. After finishing the questionnaire, participants could fill in their personal details to be included in a prize draw to win vouchers worth £15–£50. Ethical approval was obtained from UCL Research Ethics Committee (project number: 6206/001) and London Hampstead NHS Research Ethics Committee (reference no.: 15/LO/0764).

Measures

Demographic information and health characteristics

Self-reported data on age, gender, and ethnicity were collected alongside self-reported data on health characteristics, including cancer type, cancer stage, treatment type, treatment stage, and age at diagnosis. Since chemotherapy and radiotherapy are known to have a negative impact on sleep and fatigue,²⁰ TYA survivors were classified as having received/receiving chemotherapy and/or radiotherapy or having received/receiving neither of the two. Additionally, information on health problems other than the primary cancer was gathered. Participants were asked to indicate whether they have had any health problems in addition to their primary cancer, including osteoporosis, diabetes, asthma, irregular heart rhythm, extreme fatigue, mental health problems, lung disease, arthritis, any other heart trouble, another cancer, sensory impairments, or specified other problems. Responses were categorized into “no health problem present” and “health problem present” (≥ one additional health problem present).

Fatigue

Fatigue was measured as the total score of the 13-item fatigue subscale of the Functional Assessment of Chronic Illness Therapy Fatigue (FACIT-F) questionnaire. On a five-point Likert scale, the questionnaire assesses the intensity of fatigue and its impact on daily life over the past seven days.¹⁶ Examples of items included in the scale are “I feel fatigued,” “I feel tired,” and “I have to limit my social activity because I am tired.” After reverse scoring items seven (“I have energy”) and eight (“I am able to do my usual activities”), a global score ranging from zero to 52 is obtained. Higher scores indicate greater levels of fatigue. The FACIT-F is widely accepted as a measure of fatigue in cancer patients,²⁴ with high internal validity (Cronbach's α = 0.96)(1) and good test–retest reliability (r = 0.90).(1) Scores above 22 are considered as clinically significant fatigue.²⁵

Sleep

Sleep quality over the past month was measured using the Pittsburgh Sleep Quality Index (PSQI). The 19-question scale has seven dimensions: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. The individual dimensions can be evaluated separately, or combined to give a global score ranging from 0 to 21, with greater scores indicating poorer sleep quality. The PSQI was validated for cancer patients (Cronbach's α = 0.81)²⁶ and shows good reliability (r = 0.85).²⁶ The cutoff score is set at five, to identify cases with clinical sleep disorders.²⁷

HRQOL

HRQOL was measured with the EuroQoL-5, a valid (Cronbach's α = 0.71) and reliable (r > 0.7) measure of health status that is widely used in cancer research.²⁸ The five-item questionnaire assesses mobility, self-care, daily activities, discomfort/pain, and anxiety/depression at the day of survey on a five-point Likert scale.²⁸ Individual dimension scores are added to give a global score ranging from 5 to 25. Higher scores indicate poorer HRQOL.

Statistical analyses

Participants who started the survey but did not complete any items contained within either the HRQOL, sleep or fatigue measures were excluded from all analyses. Where participants completed outcome measures partially, missing data were imputed using expectation maximization algorithm.²⁹ Data were not imputed for any demographic variables or health characteristics, and pairwise deletion was applied to minimize loss of data.³⁰

Descriptive statistics were calculated for all variables. Following the advice of the TYA clinical team and after testing for an interaction by treatment status (B = 0.01, β = 0.62, 95% confidence intervals [CI] = 0.01–0.02, p < 0.001 for treatment status × fatigue interaction; B = 0.03, β = 0.46, 95% CI = 0.02–0.04, p < 0.001 for treatment status × sleep interaction) TYA survivors were stratified into those on and off treatment. In the United Kingdom, a TYA survivor is defined as any young person between the ages of 13 and 24 years living with or beyond cancer.³¹ Both groups are consequently widely referred to as TYA survivors, yet they differ in their needs.³² TYAs undergoing treatment struggle with hospitalization and treatment-related side effects such as nausea, while TYA survivors off treatment are faced with challenges regaining a sense of normalcy to their lives. TYAs who reported undergoing active treatment at survey were classified as TYA survivors on treatment. TYAs who reported not having started treatment or to have finished all active treatment were categorized as TYA survivors off treatment.

Before main analyses, associations between sleep and fatigue were explored. HRQOL was log transformed to account for the non-normality of data. Simple linear regressions were run to test for unadjusted associations between sleep and HRQOL, and fatigue and HRQOL with HRQOL as the dependent variable. Then models adjusting for covariates were run, with demographics and age at diagnosis entered as covariates, and sleep or fatigue as variables of main interest. Separate regressions were run for sleep and fatigue. To investigate whether sleep and fatigue were independently associated with HRQOL additional analyses were carried out that included sleep and fatigue in the same model. TYA survivors on and off treatment commonly reported to suffer from extreme fatigue and mental health problems, such as anxiety, in addition to their cancer. To avoid overlap with the measures included in this study, the presence of an additional health problem was not adjusted for. Other cancer-specific health characteristics such as cancer type were not controlled for, as no significant associations between these and any of the key variables were found in preliminary analyses.

All data were analyzed using IBM SPSS Version 24.0. The significance level was set at α = 0.05 for all analyses. A 95% CI, and standardized regression coefficients (β) as effect size estimates, were reported (with β < 0.2 = small, 0.2 < β < 0.5 = medium, β > 0.5 = strong).³³ Due to a lack of effect sizes reported in studies suggesting an association between fatigue and HRQOL among TYA cancer survivors, sample size calculations for the present study were based on a recent quantitative study which found a large significant correlation (r = −0.57) between sleep quality and HRQOL among TYA survivors in the first year post-treatment.¹⁸ Power calculations suggested that samples of minimum 55 participants were required to observe associations (linear regressions, large effect size, power of 80%, α = 0.05).

Results

Response rate

In total, 295 eligible TYA survivors began the survey, 85 of whom did not complete any items contained within either HRQOL, and sleep or fatigue measures. They were thus excluded from analyses. Sixty-seven TYAs reported to currently receive active cancer treatment, and 135 TYAs said to be off treatment. The remaining eight survivors did not indicate their treatment status.

Sample and health characteristics

Tables 1 and 2 provide an overview of the demographic information of the study population, and their health characteristics, respectively. The average age at survey for TYA survivors on treatment was 19.57 years (standard deviation [SD] = 3.14), and 20.17 years (SD = 2.86) for survivors off treatment. The majority of participants were female (64.18% for on treatment, 65.19% for off treatment) and White (85.07% for on treatment, 86.67% for off treatment).

Table 1.

Sociodemographic Information of the Study Population

	TYA survivors on treatment (n = 67)	TYA survivors off treatment (n = 135)	p
Age at survey, mean (SD)	19.57 (3.14)	20.17 (2.86)	0.174
13–18 years,% (n)	29.85 (20)	30.37 (41)
19–24 years,% (n)	70.15 (47)	69.63 (94)
Female,% (n)	64.18 (43)	65.19 (88)	0.888
Ethnicity,% (n)			0.980
White	85.07 (57)	86.67 (117)
Black	7.46 (5)	7.41 (10)
Asian	2.99 (2)	2.22 (3)
Mixed	4.48 (3)	3.70 (5)

TYA, teenage and young adult; SD, standard deviation.

Table 2.

Health Characteristics of the Study Population

	TYA survivors on treatment (n = 67)	TYA survivors off treatment (n = 135)	p
Age at diagnosis, mean (SD)	17.80 (3.25)	16.27 (4.31)	0.015
Health problem present,% (n)	67.16 (45)	60.74 (82)	0.791
Osteoporosis	1.49 (1)	4.44 (6)
Diabetes	7.46 (5)	1.48 (2)
Asthma	10.45 (7)	10.37 (14)
Irregular heart rhythm	7.46 (5)	5.19 (7)
Extreme fatigue	35.82 (24)	29.63 (40)
Mental health problems	16.42 (11)	20.00 (27)
Lung disease	0 (0)	0.74 (1)
Arthritis	1.49 (1)	2.96 (4)
Any other heart trouble	1.49 (1)	2.22 (3)
Another cancer	2.98 (2)	1.48 (1)
Sensory impairment	1.49 (1)	3.70 (5)
Other	19.40 (13)	19.25 (26)
Treatment type,% (n)			0.827
Chemotherapy or radiotherapy	95.52 (64)	94.81 (128)
No chemotherapy or radiotherapy	4.48 (3)	5.19 (7)
Cancer type,% (n)			0.015
Leukemia	32.84 (22)	24.44 (33)
Lymphoma	26.87 (18)	35.56 (48)
Carcinoma	0 (0)	4.44 (6)
Germ cell tumor	0 (0)	3.70 (5)
CNS tumor	0 (0)	2.22 (3)
Melanoma	1.49 (1)	0.74 (1)
Bone tumor	4.48 (3)	9.63 (13)
Soft tissue tumor	14.92 (10)	3.70 (5)
Other	17.91 (12)	14.07 (19)
Missing	1.49 (1)	1.48 (2)
Cancer stage at diagnosis,% (n)			0.222
0	0 (0)	0.74 (1)
I	11.94 (8)	6.67 (9)
II	11.94 (8)	20.00 (27)
III	11.94 (8)	16.30 (22)
IV	13.4 (9)	11.85 (16)
Do not know	47.76 (32)	40.74 (55)
Do not want to answer	0 (0)	0.74 (1)
Missing	2.99 (2)	2.96 (4)
Time since active treatment,% (n)
Less than 3 months		14.08 (19)
Between 4 and 11 months		20.00 (27)
Between 1 and 5 years		45.19 (61)
More than 5 years		3.70 (5)
On active surveillance		12.59 (17)
Missing		4.44 (6)

TYA survivors on treatment (mean age = 17.80 years, SD = 3.25) were significantly older at diagnosis compared with survivors off treatment (mean age = 16.27 years, SD = 4.31) (p = 0.015). The majority of TYAs on (67.16%) and off treatment (60.74%) reported the presence of an additional health problem. The two groups differed in cancer type (p = 0.015). Almost all TYAs on (95.52%) and off treatment (94.81%) reported to have received/receive chemotherapy and/or radiotherapy as cancer treatment. Most survivors on (47.76%) and off treatment (40.74%) were unsure about the stage of cancer they had been diagnosed with. The majority of TYAs off treatment (45.19%) had finished their treatment between 1 and 5 years before survey.

Table 3 lists the mean scores for sleep, fatigue, and HRQOL. Around 85.07% of TYAs on treatment and 62.96% of TYAs off treatment had PSQI sleep quality scores above five, suggesting possible clinically significant sleep disorders.²⁷ 56.72% of TYAs on treatment and 26.67% of TYAs off treatment had fatigue scores above 22 indicating clinically significant levels of fatigue. Significantly worse sleep quality (p = 0.007), fatigue (p < 0.001), and HR-QoL (p < 0.001) was observed among TYA cancer survivors on treatment compared to TYA cancer survivors off treatment. Sleep quality and fatigue were significantly associated among TYA survivors on (β = 0.41, 95% CI = 0.54–1.98, B = 1.26, p = 0.001) and off treatment (β = 0.54, 95% CI = 1.21–2.17, B = 1.69, p < 0.001).

Table 3.

Mean Scores of Sleep, Fatigue, and Health-Related Quality of Life of Teenage and Young Adult Survivors

	TYA survivors on treatment (n = 67)	TYA survivors off treatment (n = 135)
Sleep, mean (SD)	8.91 (3.36)	7.27 (3.55)
Fatigue, mean (SD)	23.20 (10.86)	15.56 (10.98)
HRQOL, mean (SD)	9.90 (3.68)	7.86 (2.76)

HRQOL, health-related quality of life.

Associations with HRQOL

Table 4 presents results of regression analyses among TYA survivors on treatment. In separate adjusted analyses sleep quality (β = 0.49, 95% CI = 0.03–0.07, B = 0.05, p < 0.001) and fatigue (β = 0.55, 95% CI = 0.01–0.03, B = 0.02, p < 0.001) were strongly associated with HRQOL. When entering sleep quality and fatigue into the same model both variables showed strong independent associations with HRQOL (β = 0.32, 95% CI = 0.01–0.06, B = 0.03, p = 0.009 for sleep quality, β = 0.41, 95% CI = 0.01–0.02, B = 0.01, p = 0.002 for fatigue).

Table 4.

Linear Regression Analyses of Teenage and Young Adult Survivors on Treatment

	Unadjusted	Adjusted ^a
Sleep quality
B	0.52	0.49
B (95% CI)	0.05 (0.03–0.07)	0.05 (0.03–0.07)
p	<0.001	<0.001
Fatigue
B	0.55	0.55
B (95% CI)	0.02 (0.01–0.03)	0.02 (0.01–0.03)
p	<0.001	<0.001
Sleep quality and Fatigue
Sleep quality
B	0.33	0.32
B (95% CI)	0.03 (0.01–0.06)	0.03 (0.01–0.06)
p-value	0.005	0.009
Fatigue
B	0.38	0.41
B (95% CI)	0.01 (0.01–0.02)	0.01 (0.01–0.02)
p	0.001	0.002

Regressions adjusted for age at survey, age at diagnosis, gender, and ethnicity (n = 61).

CI, confidence intervals.

Table 5 lists results of analyses, including TYA survivors off treatment. Moderate to strong associations were found between sleep quality and HRQOL (β = 0.43 95% CI = 0.02–0.05, B = 0.04, p < 0.001), and fatigue and HRQOL (β = 0.67, 95% CI = 0.01–0.02, B = 0.02, p < 0.001). After entering sleep quality and fatigue into the same model, fatigue was strongly associated with HRQOL (β = 0.63, 95% CI = 0.01–0.02, B = 0.02, p < 0.001), but no association was found between sleep quality and HRQOL (β = 0.08, 95% CI = −0.01 to 0.02, B = 0.01, p = 0.296).

Table 5.

Linear Regression Analyses of Teenage and Young Adult Survivors off Treatment

	Unadjusted	Adjusted ^a
Sleep quality
B	0.43	0.43
B (95% CI)	0.04 (0.02–0.05)	0.04 (0.02–0.05)
p	<0.001	<0.001
Fatigue
B	0.69	0.67
B (95% CI)	0.02 (0.01–0.02)	0.02 (0.01–0.02)
p	<0.001	<0.001
Sleep quality and Fatigue
Sleep quality
B	0.07	0.08
B (95% CI)	0.01 (−0.01 to 0.02)	0.01 (−0.01 to 0.02)
p	0.334	0.296
Fatigue
B	0.64	0.63
B (95% CI)	0.02 (0.01–0.02)	0.02 (0.01–0.02)
p	<0.001	<0.001

Regressions adjusted for age at survey, age at diagnosis, gender, and ethnicity (n = 131).

Discussion

A cross-sectional survey design was used to test for associations between fatigue and sleep quality, and HRQOL among TYA survivors. High prevalence of clinical sleep problems and fatigue were observed across the sample. After stratification by treatment status moderate to strong associations were observed between sleep quality and fatigue, and HRQOL among TYA survivors on and off treatment. While fatigue was found to be independently associated with HRQOL in both groups independent associations between sleep quality and HRQOL were found in TYA survivors on treatment, but not among survivors off treatment.

The high prevalence of sleep problems and fatigue observed among TYA survivors is in line with past research that found sleep onset latency suggestive of insomnia in 41% of TYA survivors in their first year post-treatment.¹⁸ Another study found increased fatigue among TYA survivors on treatment compared with general population TYAs.³ While poor sleep quality is common also among TYAs from the general population³⁴ the high percentage found in this study is particularly concerning as sleep disruption can cause circadian rhythm dysregulation, which is linked to poor health outcomes, including poorer cancer prognosis.^35,36 Additionally, fatigue hinders the development of adolescent key needs, including autonomy and close peer relationships.³⁷

The significant associations found between fatigue and HRQOL in TYAs on and off treatment are supported by findings of a review that suggests fatigue in TYA survivors was associated with increased levels of distress and reduced mobility.⁶ Using the MSAS, which allows comparisons of the level of distress caused by each symptom, fatigue was found in the top half in the majority of studies included in the review. Another review of mainly qualitative studies described the impact of fatigue on children and adolescents with cancer as an increased need to sleep and rest, and therefore to not being able to take part in regular activities.³⁸

The finding that sleep quality was strongly associated with HRQOL among TYA survivors is in line with past research involving TYA and adult cancer survivors. Associations between increased sleep–wake disturbances and impaired cancer-related quality of life were observed in a small sample of TYAs receiving chemotherapy.¹⁷ Another study found associations between poor sleep quality and impaired HRQOL among TYA survivors in the first year post-treatment. Moreover, diminished sleep quality was associated with impaired cognitive functioning and poorer functional status in 115 adult lung cancer patients undergoing chemotherapy.³⁹

Strong associations were found between sleep quality and fatigue both in TYA survivors on and off treatment. However, sleep quality among those on treatment is likely to be additionally impacted by treatment-specific factors, such as hospitalization.⁹ This may explain why sleep was found to be associated with HRQOL independent of fatigue in TYA survivors on treatment but not among those off treatment.

Several limitations need to be addressed when interpreting the findings of this study. First, as this study is a cross-sectional design, assumptions about causal relationships between sleep and fatigue and HRQOL cannot be made. Second, the study used self-report measures, thus introducing potential biases, including over- or underestimation of certain outcomes, such as sleep duration.⁴⁰ Inclusion of objective tools, such as actigraphy⁴¹ would have been valuable. Third, to reduce the burden related to study participation it was decided to include the EuroQoL-5 as a brief measure of HRQOL, yet a more detailed measure may have yielded in more insightful findings. Fourth, this study used a United Kingdom sample of TYA survivors between 13 and 24 years of age. Findings are therefore limited in generalizability to TYAs from countries that apply different age ranges to define TYA survivors.⁴² Despite aforementioned limitations, the present study had important strengths. Although a large number of TYA survivors, particularly those on treatment, appears to suffer from sleep disorders, and our findings suggest poor sleep quality to be strongly associated with impaired HRQOL in this group, only one study has to date investigated sleep quality among TYA survivors.¹⁸ Additionally, this study included exclusively TYA survivors in the first year after having finished treatment.¹⁸ The present study is thus the first sufficiently powered quantitative study to examine associations between sleep quality and HRQOL, and to describe the prevalence of sleep disorders among TYA survivors on treatment. Moreover, previous studies that examined associations between fatigue and HRQOL⁶ evaluated fatigue mainly as a subcomponent of more general measures.¹² The present study in contrast used a distinct and detailed measure of fatigue.⁴³ Furthermore, it was the first study to investigate whether sleep quality and fatigue are independently associated with HRQOL among TYA survivors on and off treatment.

Future research should aim to identify the direction of associations between sleep quality and fatigue and HRQOL. Equally, longitudinal repeated-measures study should identify the underlying mechanisms of poor sleep and HRQOL, and fatigue in TYA survivors on and off treatment. Once the direction of associations has been clarified studies, including large numbers of participants per cancer and treatment type, are required to investigate potential cancer/treatment- and demographic-related differences among TYA survivors to identify those who are in greatest need of potential interventions.

The present study suggests potentially high prevalence of sleep disorders and fatigue, and has identified probable associations between sleep and fatigue, and HRQOL among TYA survivors. Poor sleep quality and fatigue are suggested as potential modifiable factors associated with poor HRQOL among TYA survivors on and off treatment. Targeting sleep and fatigue in tailored interventions may therefore improve on and off treatment HRQOL outcomes. Furthermore, the finding that sleep quality was independently associated with HRQOL among TYA survivors on treatment but not among those off treatment suggests that interventions TYA survivors on and off treatment may benefit from different interventions. However, the causes of poor sleep and HRQOL, and fatigue among TYA survivors are complex and yet to be understood. Large-scale longitudinal studies using subjective and objective measures are needed to understand the exact mechanisms underlying fatigue and poor sleep, and HRQOL before starting the development of potential interventions.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

References

Stark

, Bowen

, Dunwoodie

, et al. Survival patterns in teenagers and young adults with cancer in the United Kingdom: comparisons with younger and older age groups. Eur J Cancer. 2015; 51(17):2643–54.

O'Hara

, Moran

, Whelan

, et al. Trends in survival for teenagers and young adults with cancer in the UK 1992–2006. Eur J Cancer. 2015; 51(14):2039–48.

Smith

, Bellizzi

, Keegan

, et al. Health-related quality of life of adolescent and young adult patients with cancer in the United States: the Adolescent and Young Adult Health Outcomes and Patient Experience study. J Clin Oncol. 2013; 31(17):2136–45.

, Robison

, Jenney

, et al. Assessment of health-related quality of life of adolescent cancer patients using the Minneapolis-Manchester Quality of Life Adolescent Questionnaire. Pediatr Blood Cancer. 2007; 48(7):678–86.

Lehmann

, Gronqvist

, Engvall

, et al. Negative and positive consequences of adolescent cancer 10 years after diagnosis: an interview-based longitudinal study in Sweden. Psychooncology. 2014; 23(11):1229–35.

Spathis

, Booth

, Grove

, et al. Teenage and young adult cancer-related fatigue is prevalent, distressing, and neglected: it is time to intervene. A systematic literature review and narrative synthesis. J Adolesc Young Adult Oncol., 2015; 4(1):3–17.

Ream

, Richardson

. Fatigue: a concept analysis. Int J Nurs Stud. 1996; 33(5):519–29.

Stasi

, Abriani

, Beccaglia

, et al. Cancer-related fatigue: evolving concepts in evaluation and treatment. Cancer. 2003; 98(9):1786–801.

Hinds

, Hockenberry

, Gattuso

, et al. Dexamethasone alters sleep and fatigue in pediatric patients with acute lymphoblastic leukemia. Cancer. 2007; 110(10):2321–30.

10.

Rosen

, Brand

. Sleep in children with cancer: case review of 70 children evaluated in a comprehensive pediatric sleep center. Support Care Cancer. 2011; 19(7):985–94.

11.

Curt

, Breitbart

, Cella

, et al. Impact of cancer-related fatigue on the lives of patients: new findings from the Fatigue Coalition. Oncologist. 2000; 5(5):353–60.

12.

Alexander

, Minton

, Andrews

, Stone

. A comparison of the characteristics of disease-free breast cancer survivors with or without cancer-related fatigue syndrome. Eur J Cancer. 2009; 45(3):384–92.

13.

Meeske

, Patel

, Palmer

, et al. Factors associated with health-related quality of life in pediatric cancer survivors. Pediatr Blood Cancer. 2007; 49(3):298–305.

14.

Gupta

, Lis

, Grutsch

. The relationship between cancer-related fatigue and patient satisfaction with quality of life in cancer. J Pain Symptom Manage. 2007; 34(1):40–7.

15.

Owens

, Group

ASW

. Insufficient sleep in adolescents and young adults: an update on causes and consequences. Pediatrics. 2014; 134(3):e921–32.

16.

Cella

, Lai

, Chang

, et al. Fatigue in cancer patients compared with fatigue in the general United States population. Cancer. 2002; 94(2):528–38.

17.

Erickson

, Beck

, Christian

, et al. Fatigue, sleep-wake disturbances, and quality of life in adolescents receiving chemotherapy. J Pediatr Hematol Oncol. 2011; 33(1):e17–25.

18.

Daniel

, Aggarwal

, Schwartz

. Sleep in adolescents and young adults in the year after cancer treatment. J Adolesc Young Adult Oncol. 2017; 6(4):560–567.

19.

Gordijn

, van Litsenburg

, Gemke

, et al. Sleep, fatigue, depression, and quality of life in survivors of childhood acute lymphoblastic leukemia. Pediatr Blood Cancer. 2013; 60(3):479–85.

20.

Walter

, Nixon

, Davey

, et al. Sleep and fatigue in pediatric oncology: a review of the literature. Sleep Med Rev. 2015; 24:71–82.

21.

Albritton

, Eden

. Access to care. Pediatr Blood Cancer. 2008; 50(5 Suppl):1094–8.

22.

Pugh

, Hough

, Gravestock

, et al. The health behavior information needs and preferences of teenage and young adult cancer survivors. J Adolesc Young Adult Oncol. 2017; 6(2):318–26.

23.

Hunter

, Pierscionek

. Children, Gillick competency and consent for involvement in research. J Med Ethics. 2007; 33(11):659–62.

24.

Webster

, Cella

, Yost

. The Functional Assessment of Chronic Illness Therapy (FACIT) measurement system: properties, applications, and interpretation. Health Qual Life Outcomes. 2003; 1:79.

25.

Reeves

, Lloyd

, Vernon

, et al. Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution. BMC Health Serv Res. 2003; 3(1):25.

26.

Beck

, Schwartz

, Towsley

, et al. Psychometric evaluation of the Pittsburgh Sleep Quality Index in cancer patients. J Pain Symptom Manage. 2004; 27(2):140–8.

27.

Buysse

, Hall

, Strollo

, et al. Relationships between the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and clinical/polysomnographic measures in a community sample. J Clin Sleep Med. 2008; 4(6):563.

28.

Noyes

, Edwards

. EQ-5D for the assessment of health-related quality of life and resource allocation in children: a systematic methodological review. Value Health. 2011; 14(8):1117–29.

29.

Allison

. Missing data: quantitative applications in the social sciences. Br J Math Stat Psychol. 2002; 55(1):193–6.

30.

Graham

. Missing data analysis: making it work in the real world. Annu Rev Psychol. 2009; 60:549–76.

31.

Lewis

. Patterns of care for teenagers and young adults with cancer: is there a single blueprint of care? In: Eden

TOB

, Barr

, Bleyer

, Whiteson

(Eds). Cancer and the Adolescent, 2nd Edition. Oxford: Blackwell Science Ltd; 2005; pp. 241–258.

32.

Zebrack

, Bleyer

, Albritton

, et al. Assessing the health care needs of adolescent and young adult cancer patients and survivors. Cancer. 2006; 107(12):2915–23.

33.

Crockett

, Schulenberg

, Petersen

. Congruence between objective and self-report data in a sample of young adolescents. J Adoles Res. 1987; 2(4):383–92.

34.

Meltzer

, Mindell

. Sleep and sleep disorders in children and adolescents. Psychiatr Clin. 2006; 29(4):1059–76.

35.

Irwin

, Fortner

, Clark

, et al. Reduction of natural killer cell activity in primary insomnia and in major depression. Sleep Res. 1995; 24:256.

36.

Sephton

, Spiegel

. Circadian disruption in cancer: a neuroendocrine-immune pathway from stress to disease?. Brain Behav Immun. 2003; 17(5):321–8.

37.

Erickson

, Beck

, Christian

, et al. Patterns of fatigue in adolescents receiving chemotherapy. Oncol Nurs Forum. 2010; 37(4):444–55.

38.

Tomlinson

, Zupanec

, Jones

, et al. The lived experience of fatigue in children and adolescents with cancer: a systematic review. Supportive Care in Cancer. 2016; 24(8):3623–31.

39.

Chen

M-L

, Yu

C-T

, Yang

C-H

. Sleep disturbances and quality of life in lung cancer patients undergoing chemotherapy. Lung Cancer. 2008; 62(3):391–400.

40.

Acock

. A gentle introduction to Stata. College Station, Texas: Stata press; 2008.

41.

Sadeh

. The role and validity of actigraphy in sleep medicine: an update. Sleep Med Rev. 2011; 15(4):259–67.

42.

Adolescent and Young Adult Oncology Progress Review Group. Closing the gap: research and cancer care imperatives for adolescents and young adults with cancer (NIH Publication No. 06-6067). Bethesda, MD: Department of Health and Human Services, National Institutes of Health, National Cancer Institute, and the LIVESTRONG Young Adult Alliance; August 2006. Accessed December 27, 2017 from: www.cancer.gov/types/aya/research/ayao-august-2006.pdf

43.

Tennant

. Assessment of fatigue in older adults: the FACIT Fatigue Scale (version 4). Psychosom Med. 2015; 65:771–7.