Abstract
Background
We sought to assess the influences of sleep duration, sleep adequacy, and daytime sleepiness on survival outcomes among Stage III colon cancer patients.
Methods
We conducted a prospective observational study of 1175 Stage III colon cancer patients enrolled in the CALGB/SWOG 80702 randomised adjuvant chemotherapy trial who completed a self-reported questionnaire on dietary and lifestyle habits 14–16 months post-randomisation. The primary endpoint was disease-free survival (DFS), and secondary was overall survival (OS). Multivariate analyses were adjusted for baseline sociodemographic, clinical, dietary and lifestyle factors.
Results
Patients sleeping ≥9 h—relative to 7 h—experienced a worse hazard ratio (HR) of 1.62 (95% confidence interval (CI), 1.01–2.58) for DFS. In addition, those sleeping the least (≤5 h) or the most (≥ 9 h) experienced worse HRs for OS of 2.14 (95% CI, 1.14–4.03) and 2.34 (95% CI, 1.26–4.33), respectively. Self-reported sleep adequacy and daytime sleepiness showed no significant correlations with outcomes.
Conclusions
Among resected Stage III colon cancer patients who received uniform treatment and follow-up within a nationwide randomised clinical trial, very long and very short sleep durations were significantly associated with increased mortality. Interventions targeting optimising sleep health among indicated colon cancer patients may be an important method by which more comprehensive care can be delivered.
Trial registration
ClinicalTrials.gov Identifier: NCT01150045.
Subject terms: Colon cancer, Outcomes research, Chemotherapy
Introduction
A wealth of emerging evidence suggests an association between sleep and cancer incidence and survival, although the literature remains conflicted with different studies reporting significant [1–5] or non-significant [6–10] associations. It is generally thought, however, that there may be a curvilinear relationship between sleep duration and mortality among cancer patients [11], as exists in the general population [12, 13].
Colorectal cancer (CRC) remains the fourth most common cancer and second leading cause of cancer-related deaths in the United States (U.S.), despite sustained improvements in CRC incidence, survival, and mortality over the past several decades [14]. While prior studies investigating sleep in the context of CRC support an increased risk associated with longer [15–18] or both longer and shorter [1] sleep durations—as well as with sleeping disorders [19] and with more frequent and longer daytime naps [16]—little is known about the influence of sleep on CRC outcomes. Only a handful of studies have evaluated the relationship between sleep and CRC survival; [20–22] of the two that have assessed the role of sleep duration, one reported post-diagnostic nighttime sleep duration to have no association with survival [22], while the other found pre-diagnostic shorter sleep duration correlated with increased all-cause and CRC-specific mortality [20].
We therefore sought to evaluate the hypothesis that patient self-reported dysregulated sleep duration, sleep inadequacy, and increased daytime sleepiness is associated with worse survival outcomes within a prospective cohort study nested in a randomised clinical trial (RCT) of adjuvant chemotherapy for Stage III colon cancer. To our knowledge, this is the first investigation into the associations of sleep duration adequacy with colon cancer survival outcomes. We additionally accounted for dietary and lifestyle factors—notably including physical activity, caffeine intake, alcohol consumption, and use of pain relief medications—beyond other clinical and sociodemographic variables, thereby conferring a more robust multivariable analysis. Careful and comprehensive documentation during the trial of patient performance status, pathologic stage, postoperative treatment, and dietary and lifestyle habits allowed concurrent effects of patient, disease and treatment characteristics to be examined.
Methods
Study population
Patients in this prospective cohort study were recruited from the U.S. and Canada as participants in the National Cancer Institute (NCI)-sponsored Cancer and Leukemia Group B (CALGB; now part of Alliance for Clinical Trials in Oncology)/Southwest Oncology Group (SWOG) 80702 phase III blinded adjuvant therapy trial for Stage III colon cancer (ClinicalTrials.gov identifier NCT01150045). The trial used a 2 × 2 factorial design to test the primary hypothesis of the superiority of celecoxib compared with placebo and the secondary hypothesis of noninferiority of three months compared with six months of chemotherapy as part of an international pooling project [23]. The results of the primary and secondary hypotheses have been reported [23–25]. Participants separately consented to a self-administered questionnaire collecting dietary and lifestyle behaviours, including physical activity, twice: once within 6 weeks of randomisation (Questionnaire 1), and again 14–16 months following randomisation (Questionnaire 2).
Eligibility required patients to have had a histologically documented, margin-negative resected colon adenocarcinoma, with tumours having had either at least one pathologically confirmed positive lymph node or an N1C designation, as defined in the 7th edition of the American Joint Committee on Cancer staging manual [26]. Participants had normal hepatic, renal, and haematologic laboratory values; an Eastern Cooperative Oncology Group performance status of 0–2; and no evidence of metastatic disease. Figure 1 describes the derivation of the final sample sizes of 1175, 1133 and 1165 patients included in this study for sleep duration, sleep adequacy and daytime sleepiness analyses, respectively.
Fig. 1. Derivation of the study cohort.
CONSORT diagram for CALGB 80702 and sleep substudy.
Assessment of sleep duration, sleep adequacy and daytime sleepiness
All exposures related to sleep were self-reported by participants through Questionnaire 2, reflecting sleep duration, sleep adequacy and daytime sleepiness as experienced in the time period surrounding questionnaire completion. Average sleep duration over a 24-h period was reported as ≤5, 6, 7, 8 or ≥ 9 h [9, 27, 28]. The Spearman correlation of the sleep duration question has previously been demonstrated to be 0.79 (P < 0.0001) [13]. Sleep adequacy was reported as adequate or inadequate. Daytime sleepiness was assessed via the frequency with which daily activities were affected by drowsiness, with response options including almost every day, ≥1 day a week, rarely or never [29].
Endpoints
The primary endpoint for this study was disease-free survival (DFS), defined as the time from completion of Questionnaire 2 to tumour recurrence, occurrence of a new primary colon cancer, or death consequent of any cause. Overall survival (OS) was defined as the time from completion of Questionnaire 2 to death due to any cause. Both endpoints were censored at 6 years.
Statistical analysis
Findings from the CALGB 80702 trial regarding the primary endpoint of DFS have been previously reported [23]. As the two chemotherapy treatment arms demonstrated similar results (non-significant interaction effects), patient data were combined from both treatment arms and analysed for this study according to categories of sleep duration, sleep adequacy, and daytime sleepiness. Baseline characteristics were compared between patients on the basis of sleep duration (≤5, 6, 7, 8 or ≥9 h).
Multivariate Cox proportional hazards regression was used to determine the survival hazards ratios (HRs) by sleep duration, sleep adequacy, or daytime sleepiness, controlling for potential confounders. Three models were built to incrementally examine the association between sleep and the study endpoints. Model 1 was adjusted for age and caffeine intake; model 2 for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status, and alcohol consumption; and model 3 for all covariates in model 2 in addition to physical activity, body mass index (BMI), smoking status, any neuropathy or grade 3+ toxicities during follow-up, and relative dose intensities of fluorouracil and oxaliplatin. Model 3 in the analysis of sleep adequacy was also adjusted for the use of pain relief medications—which included low-dose aspirin, other aspirin or aspirin-containing medications, acetaminophen, and non-steroidal anti-inflammatory drugs—and treatment arm (celecoxib versus placebo). Missing values for covariates were imputed via the following methods: (1) if the missing % was less than 5%, the missing values were recoded into the majority category (T-stage, tumour location, smoking status) or median values (physical activity) when used as covariates in the Cox model; (2) if the missing % was more than 5%, the missing values were recoded as a separate indicator when used as a covariate (BMI).
All statistical tests were two-sided, and P values equal to or less than 0.05 were considered statistically significant. All analyses were conducted using SAS software (version 9.4; SAS Institute, Cary, NC).
Patient registration and clinical data collection were managed, and their analyses were performed by the Alliance Statistics and Data Management Center. Statistical analyses were based on the study database frozen on August 10, 2020. Data quality was ensured by a review of the data by the Alliance Statistics and Data Management Center and the study chairperson following Alliance policies.
All patients signed study-specific informed consent, which was approved by the NCI Cancer Treatment Evaluation Program and each participating site’s institutional review board.
Results
Baseline characteristics by sleep duration
Within our cohort of 1175 patients with sleep variables data, 11.0%, 19.7%, 35.0%, 24.8% and 9.6% self-reported as sleeping ≤5, 6, 7, 8 or ≥9 average hours in a 24-h period, respectively. Table 1 summarises baseline clinical and sociodemographic characteristics of the study cohort according to sleep duration. Females and Blacks were more likely to sleep less relative to males and Whites or Asians, respectively. Compared to patients with an ECOG status of 0, those of statuses 1–2 were more likely to sleep fewer than 5 or more than 9 h. Patients classified as being high-risk (T4 or N2) tended to sleep more than those identified as low-risk (T1-3 or N1). Engagement in physical activity post-diagnosis, post-resection, and while on treatment or in survivorship was lowest among those at either extreme of sleep duration, and caffeine intake was highest among those sleeping more than 9 h.
Table 1.
Baseline characteristics of 1175 Stage III colon cancer patients by sleep duration in a 24-h period.
| Overall (N = 1175) | Average sleep duration (hours) | |||||
|---|---|---|---|---|---|---|
| Factor | Statistics | ≤5 (N = 129) | 6 (N = 231) | 7 (N = 411) | 8 (N = 291) | ≥9 (N = 113) |
| Age, years, mean (SD) | 61.1 (10.1) | 59.8 (9.3) | 59.0 (9.6) | 61.1 (10.0) | 61.8 (10.2) | 65.3 (10.2) |
| Female sex, no. (%) | 535 (45.5) | 73 (56.6) | 113 (48.9) | 174 (42.3) | 119 (40.9) | 56 (49.6) |
| Race, no. (%) | ||||||
| White | 972 (82.7) | 92 (71.3) | 183 (79.2) | 346 (84.2) | 251 (86.3) | 100 (88.5) |
| Black | 129 (11.0) | 30 (23.3) | 31 (13.4) | 34 (8.3) | 24 (8.2) | 10 (8.8) |
| Asian | 38 (3.2) | 2 (1.6) | 11 (4.8) | 14 (3.4) | 9 (3.1) | 2 (1.8) |
| Others | 36 (3.1) | 5 (3.9) | 6 (2.6) | 17 (4.1) | 7 (2.4) | 1 (0.88) |
| Hispanic ethnicity, no. (%) | 54 (4.6) | 4 (3.1) | 13 (5.6) | 23 (5.6) | 12 (4.1) | 2 (1.8) |
| BMI, kg/m2, mean (SD) | 30.2 (6.6) | 30.5 (6.6) | 29.9 (5.9) | 30.4 (6.5) | 29.7 (6.7) | 31.3 (7.7) |
| Missing | 104 | 14 | 18 | 31 | 30 | 11 |
| Treatment assigned, no. (%) | ||||||
| 6 Cycles + Celecoxib | 308 (26.2) | 34 (26.4) | 75 (32.5) | 105 (25.5) | 76 (26.1) | 18 (15.9) |
| 6 Cycles + Placebo | 302 (25.7) | 34 (26.4) | 55 (23.8) | 111 (27.0) | 69 (23.7) | 33 (29.2) |
| 12 Cycles + Celecoxib | 286 (24.3) | 27 (20.9) | 51 (22.1) | 95 (23.1) | 78 (26.8) | 35 (31.0) |
| 12 Cycles + Placebo | 279 (23.7) | 34 (26.4) | 50 (21.6) | 100 (24.3) | 68 (23.4) | 27 (23.9) |
| Prior cancer diagnosed, no. (%) | 89 (7.7) | 6 (4.7) | 17 (7.6) | 31 (7.6) | 25 (8.7) | 10 (9.0) |
| Missing | 20 | 1 | 7 | 5 | 5 | 2 |
| Performance status, no. (%)a | ||||||
| ECOG 0 | 854 (72.7) | 85 (65.9) | 165 (71.4) | 317 (77.1) | 216 (74.2) | 71 (62.8) |
| ECOG 1–2 | 321 (27.3) | 44 (34.1) | 66 (28.6) | 94 (22.9) | 75 (25.8) | 42 (37.2) |
| Aspirin use, no. (%) | 278 (23.7) | 26 (20.2) | 53 (22.9) | 92 (22.4) | 74 (25.4) | 33 (29.2) |
| T-stage, no. (%) | ||||||
| 1–2 | 229 (19.5) | 25 (19.4) | 39 (16.9) | 96 (23.4) | 53 (18.2) | 16 (14.2) |
| 3 | 791 (68.0) | 87 (68.0) | 158 (69.3) | 267 (65.4) | 200 (69.2) | 79 (71.2) |
| 4 | 144 (12.3) | 16 (12.4) | 31 (13.4) | 45 (10.9) | 36 (12.4) | 16 (14.2) |
| Missing | 11 | 1 | 3 | 3 | 2 | 2 |
| N-stage, no. (%) | ||||||
| N1 | 897 (76.3) | 98 (76.0) | 172 (74.5) | 321 (78.1) | 228 (78.4) | 78 (69.0) |
| N2 | 278 (23.7) | 31 (24.0) | 59 (25.5) | 90 (21.9) | 63 (21.6) | 35 (31.0) |
| Tumour location, no. (%) | ||||||
| Left | 549 (46.7) | 58 (45.0) | 105 (45.5) | 219 (53.3) | 120 (41.2) | 47 (41.6) |
| Right/transverse | 621 (52.9) | 71 (55.0) | 125 (54.1) | 189 (46.0) | 170 (58.4) | 66 (58.4) |
| Multiple | 5 (0.43) | 0 (0.0) | 1 (0.43) | 3 (0.73) | 1 (0.34) | 0 (0.0) |
| Missing | 12 | 1 | 3 | 4 | 2 | 2 |
| Risk group, no. (%) | ||||||
| Low (T1, T2, T3, or N1) | 784 (67.4) | 87 (68.0) | 146 (64.0) | 286 (70.1) | 200 (69.2) | 65 (58.6) |
| High (T4, N2, or both) | 380 (32.6) | 41 (32.0) | 82 (36.0) | 122 (29.9) | 89 (30.8) | 46 (41.4) |
| Missing | 11 | 1 | 3 | 3 | 2 | 2 |
| Physical activity, total MET-hours/week, median [IQR] | 10 [2.5, 28] | 5.5 [1.2, 16] | 14 [3.1, 35] | 12 [2.7, 30] | 11 [3.1, 26] | 4.9 [0.60, 15] |
| Caffeine intake, mg, median [IQR] | 119 [51, 247] | 112 [41, 258] | 119 [52, 249] | 120 [55, 246] | 117 [40, 245] | 215 [97, 260] |
| Alcohol consumption, gram, median [IQR] | 1.1 [0,7.8] | 0.61 [0, 5.7] | 0.90 [0, 6.0] | 1.5 [0, 8.9] | 1.1 [0, 9.3] | 0.30 [0, 4.7] |
| Diabetes mellitus, no. (%) | 203 (17.1) | 24 (18.6) | 36 (15.6) | 59 (14.4) | 54 (18.6) | 27 (23.9) |
| Missing | 14 | 1 | 4 | 4 | 4 | 1 |
SD standard deviation, BMI body mass index, ECOG Eastern Cooperative Oncology Group, MET metabolic equivalent of task, IQR interquartile range.
aBaseline performance status: Performance status 0 = fully active; Performance status 1 = restricted in physically strenuous activity but ambulatory and able to carry out light work; performance status 2 = ambulatory and capable of all self-care but unable to carry out any work activities, up and about more than 50% of waking hours.
Association between sleep duration and cancer recurrence or mortality
Over a median follow-up of 4.5 years (interquartile range: 3.7–4.8) following completion of Q2, there were 193 and 95 events for DFS and OS analyses, respectively. In multivariate Cox regression analyses, patients sleeping ≥ 9 h a day—relative to those sleeping 7 h—experienced a worse HR of 1.62 (95% confidence interval (CI), 1.01–2.58) for DFS (Table 2). Figure 2 illustrates the U-shape trend in DFS by sleep duration. In addition, those sleeping the least (≤5 h) and the most (≥9 h) experienced worse HRs for OS of 2.14 (95% CI, 1.14–4.03) and 2.34 (95% CI, 1.26–4.33), respectively, as well as for CRC-specific mortality of 3.65 (95% CI, 1.58–8.43) and 2.79 (95% CI, 1.17–6.62) (Supplemental Table 1). The cumulative incidence functions for CRC- and non-CRC-specific mortality by sleep duration is presented in Supplemental Fig. 1.
Table 2.
Sleep duration, colon cancer recurrence and mortality.
| Average sleep duration (hours) | ||||||
|---|---|---|---|---|---|---|
| ≤ 5 | 6 | 7 | 8 | ≥9 | *Pnon-linear | |
| Disease-free survival | ||||||
| # Event/at risk | 24/129 | 36/231 | 61/411 | 44/291 | 28/113 | |
| Age- and caffeine intake-adjusted only, HR (95% CI) | 1.23 (0.77–1.98) | 1.03 (0.68–1.56) | Ref | 0.98 (0.67–1.45) | 1.70 (1.08–2.68) | 0.03 |
| Multivariable-adjusted, HR (95% CI)a | 1.33 (0.83–2.15) | 1.01 (0.67–1.53) | Ref | 0.96 (0.65–1.41) | 1.66 (1.05–2.63) | 0.02 |
| Multivariable-adjusted, HR (95% CI)b | 1.35 (0.83–2.20) | 1.07 (0.70–1.63) | Ref | 0.96 (0.65–1.43) | 1.62 (1.01–2.58) | 0.03 |
| Overall survival | ||||||
| # Event/at risk | 17/129 | 12/231 | 26/411 | 20/291 | 20/113 | |
| Age- and caffeine intake-adjusted only, HR (95% CI) | 2.13 (1.15–3.93) | 0.87 (0.44–1.73) | Ref | 1.03 (0.58–1.85) | 2.63 (1.45–4.77) | <0.001 |
| Multivariable-adjusted, HR (95% CI)a | 2.26 (1.22–4.20) | 0.83 (0.42–1.66) | Ref | 0.99 (0.55–1.79) | 2.45 (1.34–4.49) | <0.001 |
| Multivariable-adjusted, HR (95% CI)b | 2.14 (1.14–4.03) | 0.87 (0.44–1.74) | Ref | 0.97 (0.53–1.75) | 2.34 (1.26–4.33) | <0.001 |
*P value for non-linear trend was estimated by including a quadratic term for sleep duration variable.
aMultivariable-adjusted model adjusted for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status and alcohol consumption.
bMultivariable-adjusted model adjusted for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status, alcohol consumption, physical activity, BMI, smoking status, any neuropathy or grade 3+ toxicities during follow-up, and relative dose intensities of fluorouracil and oxaliplatin.
Fig. 2. Spline curve of disease-free survival and sleep duration.
Spline curve illustrating the U-shape trend in disease-free survival according to sleep duration.
Association between sleep adequacy and cancer recurrence or mortality
Among 1133 participants with sleep adequacy data, there were 181 and 89 events for DFS and OS analyses, respectively. We observed no significant differences in cancer mortality by self-reported sleep adequacy in either age- and caffeine intake-adjusted or multivariate analyses. As shown in Table 3, when compared to patients reporting adequate sleep duration, the fully adjusted HRs for those reporting inadequate sleep duration were 1.27 (95% CI, 0.92–1.76) for DFS and 1.46 (95% CI, 0.92–2.31) for OS.
Table 3.
Sleep adequacy, colon cancer recurrence, and mortality.
| Sleep duration adequacy | |||
|---|---|---|---|
| Adequate | Not adequate | P value | |
| Disease-free survival | |||
| # Event/at risk | 121/765 | 60/368 | |
| Age- and caffeine intake-adjusted only, HR (95% CI) | Ref | 1.14 (0.84–1.57) | 0.40 |
| Multivariable-adjusted, HR (95% CI)a | Ref | 1.26 (0.91–1.73) | 0.16 |
| Multivariable-adjusted, HR (95% CI)b | Ref | 1.27 (0.92–1.76) | 0.15 |
| Overall survival | |||
| # Event/at risk | 59/765 | 30/368 | |
| Age- and caffeine intake-adjusted only, HR (95% CI) | Ref | 1.33 (0.85–2.08) | 0.22 |
| Multivariable-adjusted, HR (95% CI)a | Ref | 1.45 (0.92–2.29) | 0.11 |
| Multivariable-adjusted, HR (95% CI)b | Ref | 1.46 (0.92–2.31) | 0.11 |
aMultivariable-adjusted model adjusted for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status, and alcohol consumption.
bMultivariable-adjusted model adjusted for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status, alcohol consumption, physical activity, BMI, smoking status, any neuropathy or grade 3+ toxicities during follow-up, relative dose intensities of fluorouracil and oxaliplatin, treatment arm, and use of pain relief medications.
Association between daytime sleepiness and cancer recurrence or mortality
Among 1165 patients with daytime sleepiness data, there were 191 and 93 events for DFS and OS analyses, respectively. In multivariate Cox regression analyses, patients reporting daily activities being affected to any degree by daytime sleepiness experienced similar survival relative to those reporting daily activities never being affected by daytime sleepiness. The fully adjusted HRs for patients reporting being impacted almost every day were 1.39 (95% CI, 0.79–2.46) for DFS and 1.52 (95% CI, 0.70–3.30) for OS (Table 4). However, patients reporting being affected almost every day experienced greater CRC-specific mortality relative to those never being affected (HR, 2.97; 95% CI, 1.22–7.21) (Supplemental Table 2). The cumulative incidence functions for CRC- and non-CRC-specific mortality by daytime sleepiness is presented in Supplemental Fig. 2.
Table 4.
Daytime sleepiness, colon cancer recurrence, and mortality.
| Daily activities affected by daytime sleepiness | |||||
|---|---|---|---|---|---|
| Almost every day | ≥1 Day/week | Rarely | Never | *Plinear | |
| Disease-free survival | |||||
| # Event/at risk | 18/79 | 32/209 | 92/578 | 49/299 | |
| Age- and caffeine intake-adjusted only, HR (95% CI) | 1.42 (0.83–2.45) | 0.96 (0.62–1.50) | 0.94 (0.66–1.33) | Ref | 0.19 |
| Multivariable-adjusted, HR (95% CI)a | 1.59 (0.92–2.76) | 1.09 (0.69–1.70) | 0.99 (0.70–1.40) | Ref | 0.09 |
| Multivariable-adjusted, HR (95% CI)b | 1.39 (0.79–2.46) | 1.11 (0.70–1.75) | 1.01 (0.71–1.43) | Ref | 0.23 |
| Overall survival | |||||
| # Event/at risk | 10/79 | 22/209 | 38/578 | 23/299 | |
| Age- and caffeine intake-adjusted only, HR (95% CI) | 1.75 (0.83–3.68) | 1.65 (0.92–2.97) | 0.84 (0.50–1.41) | Ref | 0.08 |
| Multivariable-adjusted, HR (95% CI)a | 1.84 (0.86–3.92) | 1.91 (1.05–3.46) | 0.85 (0.51–1.44) | Ref | 0.06 |
| Multivariable-adjusted, HR (95% CI)b | 1.52 (0.70–3.30) | 1.93 (1.05–3.55) | 0.87 (0.51–1.47) | Ref | 0.19 |
*P value for linear trend was tested by assigning each subject the median value of the category and modelled as a continuous variable.
aMultivariable-adjusted model adjusted for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status, and alcohol consumption.
bMultivariable-adjusted model adjusted for age, caffeine intake, sex, T-stage, N-stage, ECOG performance status, alcohol consumption, physical activity, BMI, smoking status, any neuropathy or grade 3+ toxicities during follow-up, and relative dose intensities of fluorouracil and oxaliplatin.
Sensitivity analyses
To account for the potential of reverse causality, we performed sensitivity analyses further excluding patients who experienced recurrence or mortality within 90 days and 180 days of Q2 completion. In these analyses, no appreciable differences in outcomes were observed (data not shown).
Discussion
In this prospective cohort of resected Stage III colon cancer patients enrolled in a postoperative adjuvant chemotherapy clinical trial, we found patients reporting sleeping ≥9 h a day experienced significantly worse DFS relative to those sleeping 7 h, and patients sleeping the most or the least experienced significantly decreased OS and increased CRC-specific mortality. Patients reporting daytime sleepiness impacting their daily activities almost every day experienced only worse CRC-specific mortality relative to those never being affected. The inferior patient outcomes associated with very long and very short sleep durations and with nearly daily impact from daytime sleepiness remained consistent after adjusting for multiple predictors of patient outcome. Patients reporting inadequate sleep experienced similar survival compared to those reporting adequate sleep. Our study confers greater insight into the highly limited and conflicted literature on the association between sleep duration and colon cancer mortality, and is, to our knowledge, the first investigation into the influence of sleep adequacy on colon cancer survival outcomes.
Although sleep disturbances have been reported to affect almost 60% of CRC survivors [30], very few studies have previously examined the role of sleep in CRC mortality and have produced conflicting findings. In an analysis of pre-diagnosis sleep duration, a greater than 50% increase in CRC-specific mortality was observed among those reporting the shortest sleep duration (subdistribution HR, 1.53; 95% CI, 1.10–2.12), in addition to an increase in all-cause mortality associated with any amount of daytime napping [20]. A study on post-diagnosis sleep duration, however, found daytime napping of 2 or more hours—but not nighttime sleep duration—more than doubles the risk of all-cause mortality (HR, 2.22; 95% CI, 1.43–3.44) [22]. A recent meta-analysis including four studies of CRC patients also found no relationship between sleep duration and all-cause or CRC-specific mortality [31]. In contrast to much of the prior literature, we found very long and very short sleep durations post-diagnosis are significantly associated with worse mortality among CRC patients. In addition, although we did not directly measure daytime napping, we propose that daytime sleepiness may serve as a proxy measure. In our study, we found no significant correlation between daytime sleepiness and survival outcomes.
Our overall findings lend support for the general hypothesis that good sleep health may be associated with improved outcomes among colon cancer patients. Although disturbances in the circadian rest–activity rhythm have been correlated with worse CRC survival [32–35], the mechanism underlying the association between sleep and CRC is unknown. Sleep dysfunction may indirectly promote CRC risk via its associations with a variety of known CRC risk factors [36], including diabetes [37] and insulin resistance [38], obesity [39], and weight gain [39, 40]. Proinflammatory cytokines have been shown to be upregulated in the setting of sleep dysregulation [41, 42], potentially resulting in an environment more conducive to the development and progression of CRC. In addition, circadian rhythm-associated molecules have been shown to have overlapping functions in cell cycle and DNA damage checkpoints [43] and immune system functioning [44, 45]; and thus, sleep dysfunction may lead to both an increased risk for and decreased survival with CRC. Poor sleep quality and daytime sleepiness may also be markers of underlying health conditions and deteriorating overall health.
Assessing sleep and colon cancer patient outcomes through an RCT confers several strengths. By studying patients enrolled in a clinical trial, we potentially reduced the biases introduced by differences in access to healthcare resources unavoidable in population-based cancer registries. Moreover, as all patients in this study met the same enrollment criteria and received adjuvant 5-FU-based chemotherapy, confounding by patient or treatment characteristics was minimised. Finally, all patients had Stage III colon cancer, minimising the effect of disease stage heterogeneity on outcomes.
Our study is not without limitations. Patients who choose to enroll in clinical trials may differ from the general population: they must meet specific eligibility criteria, be chosen as appropriate candidates, and have the motivation to participate. However, CALGB 80702 enrolled patients from both community and academic centres across North America, thereby lowering the likelihood of biased sampling. Exposure misclassification may have confounded results: self-reported and objectively measured sleep durations have previously been shown to only be moderately correlated, with individuals who sleep less tending to overestimate their sleep duration relative to those who sleep more [46]. Some factors that may be contributory to baseline sleep issues, such as obstructive sleep apnoea and pain, were not directly assessed; however, potential proxies for such variables—including BMI and use of pain medications—were adjusted for in the multivariate analyses. In addition, patients reporting the furthest extremes of sleep duration (≤5 or ≥9 h per night) engaged in comparatively less physical activity and had a lower performance status. Although physical activity is independently associated with colon cancer survival [47] and performance status can serve as a surrogate of general health, our findings remained consistent even after adjusting for these characteristics. As the exposures were assessed only through Q2, any changes in sleep health during the follow-up period would not have been captured. It is important to note that factors relating to mental health and quality of life have been demonstrated to correlate with sleep health [48, 49]. The presence of other residual confounding attributable to such factors, which our study instruments did not measure, cannot be excluded. Nevertheless, our findings remained consistent even after controlling for a variety of known and suspected patient outcome predictors. Moreover, only 7% of participants had reported being impacted almost every day by daytime sleepiness, and our analyses may thus have been underpowered to identify statistical significance within this subset of patients. Finally, we were not able to perform an internal cross-validation of our findings due to the lack of an additional dataset.
In conclusion, we found both very long and very short sleep durations as well as nearly daily impact from daytime sleepiness were significantly associated with increased mortality in this cohort of Stage III colon cancer patients treated within an RCT. A recent survey of 25 U.S. NCI-designated comprehensive cancer centres enrolled in the National Comprehensive Cancer Network found that about half of the institutions screened less than 25% of cancer survivors for sleep disorders and did not have access to a provider who could perform a complete sleep assessment [50]. Indeed, cancer survivors have reported significant impairments in quality of life from insomnia, citing lack of focus on sleep health and inaccessibility of evidence-based insomnia interventions as substantial gaps in cancer care [51]. Our study highlights the need to more effectively integrate sleep health as an important component of cancer care. Interventions targeting optimising sleep health among indicated colon cancer patients may be an important method by which more comprehensive care can be delivered.
Supplementary information
Author contributions
Conceptualisation: JAM and SL; data curation: JAM and CM; formal analysis: JAM and CM; funding acquisition: JAM; investigation: JAM and SL; methodology: JAM; validation: QS and JM; visualisation: SL and CM; writing and original draft: JAM and SL; writing, review and editing: SL, CM, QS, JM, PK, FC, PK, SK, DL, BT, EMO, AFS and JAM.
Funding
Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Numbers U10CA180821 and U10CA180882 (to the Alliance for Clinical Trials in Oncology.) https://acknowledgments.alliancefound.org. UG1CA233163, UG1CA233180, UG1CA233253, UG1CA233290, UG1CA233320, UG1CA233337, UG1CA233339, UG1CA189954, and U10CA180863 to the Canadian Cancer Trials Group; UG1CA233234; and U10CA180820 to the ECOG–ACRIN Cancer Research Group; U10CA180868 to NRG Oncology; and U10CA180888 to the SWOG Cancer Research Network from the National Cancer Institute of the National Institutes of Health. Dr. Meyerhardt is supported by the Douglas Gray Woodruff Chair Fund, the Guo Shu Shi Fund, Anonymous Family Fund for Innovations in Colorectal Cancer, and the George Stone Family Foundation. The National Cancer Institute was involved in the design of the study and review of the manuscript. Pfizer participated in initial protocol development and review and approval of the final manuscript. Pfizer provided celecoxib and placebo tablets. Pfizer was not involved in the collection, management, analysis, or interpretation of the data. Neither Pfizer nor the National Cancer Institute had the right to veto publication or control the decision to which journal the article was submitted. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Data availability
Data are from the Alliance for Clinical Trials in Oncology. Investigators may request access to this data per Alliance protocol as outlined below and as detailed at https://www.allianceforclinicaltrialsinoncology.org/main/public/standard.xhtml?path=%2FPublic%2FDatasharing. Per NCI National Clinical Trials Network (NCTN) guidelines, any investigator may submit a request for data from published Alliance or legacy ACOSOG, CALGB, or NCCTG trials. To submit a data request, the investigator should complete an Alliance Data Sharing Request Form and send it by e-mail to gro. NTCNecnailla@stpecnoc. Once received, the request will be forwarded to the Alliance Statistics and Data Center (SDC). The SDC will confirm the availability of the data. Once the SDC confirms availability, the investigator will be asked to provide documentation of Institutional Review Board (IRB) approval or exemption from their institution, as well as to submit an Alliance data release agreement. Once the IRB documentation and the data release agreement are received from the requesting investigator, the SDC will be notified that the requested data may be released. Questions about the process may be directed to gro. NTCNecnailla@stpecnoc.
Competing interests
Dr. Shi reported receiving institutional grant support from Celgene–Bristol Myers Squibb and Roche/Genentech; serving as a consultant to Yiviva Inc and Boehringer Ingelheim Pharmaceuticals; and owning stock in Johnson & Johnson, Merck, and Amgen. Dr. Kuebler reported receiving grants from the Columbus National Community Oncology Research Program and the National Institutes of Cancer. Dr. O’Reilly reported receiving institutional grants from Genentech/Roche, Celgene/Bristol Myers Squibb, BioNTech, AstraZeneca, and Arcus; receiving personal fees from CytomX Therapeutics, Rafael Therapeutics, Sobi Consulting, and Synthorx Inc; nonfinancial support from Silenseed Consulting, consulting fees from Boehringer Ingelheim, BioNTech, Ipsen, and Merck; and his spouse receives consulting fees from Bayer, Genentech/Roche, Celgene/Bristol Myers Squibb, Eisai, and Polaris; and personal fees from Molecular Templates Consulting. Dr. Shields reported receiving grants from National Cancer Institute. Dr. Meyerhardt reported receiving grants from National Cancer Institute and personal fees for serving on the advisory boards of COTA Healthcare and Merck, and institutional support from Boston Biomedical for a clinical trial outside the submitted work. The remaining authors declare no competing interests.
Ethics approval and consent to participate
All patients signed study-specific informed consent, which was approved by the NCI Cancer Treatment Evaluation Program and each participating site’s institutional review board. The study was performed in accordance with the Declaration of Helsinki.
Consent for publication
Not applicable.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
The online version contains supplementary material available at 10.1038/s41416-023-02290-2.
References
- 1.Jiao L, Duan Z, Sangi-Haghpeykar H, Hale L, White DL, El-Serag HB. Sleep duration and incidence of colorectal cancer in postmenopausal women. Br J Cancer. 2013;108:213–21. doi: 10.1038/bjc.2012.561. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Luojus MK, Lehto SM, Tolmunen T, Erkkilä AT, Kauhanen J. Sleep duration and incidence of lung cancer in ageing men. BMC Public Health. 2014;14:295. doi: 10.1186/1471-2458-14-295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Xiao Q, Signorello LB, Brinton LA, Cohen SS, Blot WJ, Matthews CE. Sleep duration and breast cancer risk among black and white women. Sleep Med. 2016;20:25–9. doi: 10.1016/j.sleep.2015.11.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Trudel-Fitzgerald C, Zhou ES, Poole EM, Zhang X, Michels KB, Eliassen AH, et al. Sleep and survival among women with breast cancer: 30 years of follow-up within the Nurses’ Health Study. Br J Cancer. 2017;116:1239–46. doi: 10.1038/bjc.2017.85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Palesh O, Aldridge-Gerry A, Zeitzer JM, Koopman C, Neri E, Giese-Davis J, et al. Actigraphy-measured sleep disruption as a predictor of survival among women with advanced breast cancer. Sleep. 2014;37:837–42. doi: 10.5665/sleep.3642. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Sturgeon SR, Luisi N, Balasubramanian R, Reeves KW. Sleep duration and endometrial cancer risk. Cancer Causes Control: Ccc. 2012;23:547–53. doi: 10.1007/s10552-012-9912-2. [DOI] [PubMed] [Google Scholar]
- 7.Girschik J, Heyworth J, Fritschi L. Self-reported sleep duration, sleep quality, and breast cancer risk in a population-based case-control study. Am J Epidemiol. 2013;177:316–27. doi: 10.1093/aje/kws422. [DOI] [PubMed] [Google Scholar]
- 8.Vogtmann E, Levitan EB, Hale L, Shikany JM, Shah NA, Endeshaw Y, et al. Association between sleep and breast cancer incidence among postmenopausal women in the Women’s Health Initiative. Sleep. 2013;36:1437–44. doi: 10.5665/sleep.3032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Pinheiro SP, Schernhammer ES, Tworoger SS, Michels KB. A prospective study on habitual duration of sleep and incidence of breast cancer in a large cohort of women. Cancer Res. 2006;66:5521–5. doi: 10.1158/0008-5472.CAN-05-4652. [DOI] [PubMed] [Google Scholar]
- 10.Wong ATY, Heath AK, Tong TYN, Reeves GK, Floud S, Beral V, et al. Sleep duration and breast cancer incidence: results from the Million Women Study and meta-analysis of published prospective studies. Sleep. 2020;44:zsaa166. doi: 10.1093/sleep/zsaa166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Collins KP, Geller DA, Antoni M, Donnell DM, Tsung A, Marsh JW, et al. Sleep duration is associated with survival in advanced cancer patients. Sleep Med. 2017;32:208–12. doi: 10.1016/j.sleep.2016.06.041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Cappuccio FP, D’Elia L, Strazzullo P, Miller MA. Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep. 2010;33:585–92. doi: 10.1093/sleep/33.5.585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Patel SR, Ayas NT, Malhotra MR, White DP, Schernhammer ES, Speizer FE, et al. A prospective study of sleep duration and mortality risk in women. Sleep. 2004;27:440–4. doi: 10.1093/sleep/27.3.440. [DOI] [PubMed] [Google Scholar]
- 14.Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA: A Cancer J Clin. 2021;71:7–33. doi: 10.3322/caac.21654. [DOI] [PubMed] [Google Scholar]
- 15.Lin Y, Peng Y, Liang B, Zhu S, Li L, Jang F, et al. Associations of dinner-to-bed time, post-dinner walk and sleep duration with colorectal cancer: a case-control study. Medicine. 2018;97:e12038. doi: 10.1097/MD.0000000000012038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Papantoniou K, Castaño-Vinyals G, Espinosa A, Turner MC, Martín-Sánchez V, Casabonne D, et al. Sleep duration and napping in relation to colorectal and gastric cancer in the MCC-Spain study. Sci Rep. 2021;11:11822. doi: 10.1038/s41598-021-91275-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Lu Y, Tian N, Yin J, Shi Y, Huang Z. Association between sleep duration and cancer risk: a meta-analysis of prospective cohort studies. PLoS ONE. 2013;8:e74723. doi: 10.1371/journal.pone.0074723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Zhang X, Giovannucci EL, Wu K, Gao X, Hu F, Ogino S, et al. Associations of self-reported sleep duration and snoring with colorectal cancer risk in men and women. Sleep. 2013;36:681–8. doi: 10.5665/sleep.2626. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Lin CL, Liu TC, Wang YN, Chung CH, Chien WC. The association between sleep disorders and the risk of colorectal cancer in patients: a population-based nested case-control study. In Vivo. 2019;33:573–9. doi: 10.21873/invivo.11513. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Xiao Q, Arem H, Pfeiffer R, Matthews C. Prediagnosis sleep duration, napping, and mortality among colorectal cancer survivors in a large US cohort. Sleep. 2017;40:zsx010. doi: 10.1093/sleep/zsx010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Innominato PF, Spiegel D, Ulusakarya A, Giacchetti S, Bjarnason GA, Lévi F, et al. Subjective sleep and overall survival in chemotherapy-naïve patients with metastatic colorectal cancer. Sleep Med. 2015;16:391–8. doi: 10.1016/j.sleep.2014.10.022. [DOI] [PubMed] [Google Scholar]
- 22.Ratjen I, Schafmayer C, di Giuseppe R, Waniek S, Plachta-Danielzik S, Koch M, et al. Postdiagnostic physical activity, sleep duration, and TV watching and all-cause mortality among long-term colorectal cancer survivors: a prospective cohort study. BMC Cancer. 2017;17:701. doi: 10.1186/s12885-017-3697-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Meyerhardt JA, Shi Q, Fuchs CS, Meyer J, Niedzwiecki D, Zemla T, et al. Effect of celecoxib vs placebo added to standard adjuvant therapy on disease-free survival among patients with stage III Colon cancer: the CALGB/SWOG 80702 (alliance) randomized clinical trial. J Am Med Assoc. 2021;325:1277–86. doi: 10.1001/jama.2021.2454. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Grothey A, Sobrero AF, Shields AF, Yoshino T, Paul J, Taieb J, et al. Duration of adjuvant chemotherapy for stage III colon cancer. N Engl J Med. 2018;378:1177–88. doi: 10.1056/NEJMoa1713709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.André T, Meyerhardt J, Iveson T, Sobrero A, Yoshino T, Souglakos I, et al. Effect of duration of adjuvant chemotherapy for patients with stage III colon cancer (IDEA collaboration): final results from a prospective, pooled analysis of six randomised, phase 3 trials. Lancet Oncol. 2020;21:1620–9. doi: 10.1016/S1470-2045(20)30527-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17:1471–4. doi: 10.1245/s10434-010-0985-4. [DOI] [PubMed] [Google Scholar]
- 27.Gangwisch JE, Feskanich D, Malaspina D, Shen S, Forman JP. Sleep duration and risk for hypertension in women: results from the nurses’ health study. Am J Hypertens. 2013;26:903–11. doi: 10.1093/ajh/hpt044. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ayas NT, White DP, Manson JE, Stampfer MJ, Speizer FE, Malhotra A, et al. A prospective study of sleep duration and coronary heart disease in women. Arch Intern Med. 2003;163:205–9. doi: 10.1001/archinte.163.2.205. [DOI] [PubMed] [Google Scholar]
- 29.Gangwisch JE, Rexrode K, Forman JP, Mukamal K, Malaspina D, Feskanich D. Daytime sleepiness and risk of coronary heart disease and stroke: results from the Nurses’ Health Study II. Sleep Med. 2014;15:782–8. doi: 10.1016/j.sleep.2014.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Drury A, Payne S, Brady AM. Prevalence vs impact: a mixed methods study of survivorship issues in colorectal cancer. Qual Life Res. 2022;31:1117–34. [DOI] [PMC free article] [PubMed]
- 31.Stone CR, Haig TR, Fiest KM, McNeil J, Brenner DR, Friedenreich CM. The association between sleep duration and cancer-specific mortality: a systematic review and meta-analysis. Cancer Causes Control: CCC. 2019;30:501–25. doi: 10.1007/s10552-019-01156-4. [DOI] [PubMed] [Google Scholar]
- 32.Mormont M-C, Waterhouse J, Bleuzen P, Giacchetti S, Jami A, Bogdan A, et al. Marked 24-h rest/activity rhythms are associated with better quality of life, better response, and longer survival in patients with metastatic colorectal cancer and good performance status. Clin Cancer Res. 2000;6:3038. [PubMed] [Google Scholar]
- 33.Innominato PF, Focan C, Gorlia T, Moreau T, Garufi C, Waterhouse J, et al. Circadian rhythm in rest and activity: a biological correlate of quality of life and a predictor of survival in patients with metastatic colorectal cancer. Cancer Res. 2009;69:4700. doi: 10.1158/0008-5472.CAN-08-4747. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Innominato PF, Giacchetti S, Bjarnason GA, Focan C, Garufi C, Coudert B, et al. Prediction of overall survival through circadian rest-activity monitoring during chemotherapy for metastatic colorectal cancer. Int J Cancer. 2012;131:2684–92. doi: 10.1002/ijc.27574. [DOI] [PubMed] [Google Scholar]
- 35.Lévi F, Dugué PA, Innominato P, Karaboué A, Dispersyn G, Parganiha A, et al. Wrist actimetry circadian rhythm as a robust predictor of colorectal cancer patients survival. Chronobiol Int. 2014;31:891–900. doi: 10.3109/07420528.2014.924523. [DOI] [PubMed] [Google Scholar]
- 36.Giovannucci E. Metabolic syndrome, hyperinsulinemia, and colon cancer: a review. Am J Clin Nutr. 2007;86:s836–42. doi: 10.1093/ajcn/86.3.836S. [DOI] [PubMed] [Google Scholar]
- 37.Ayas NT, White DP, Al-Delaimy WK, Manson JE, Stampfer MJ, Speizer FE, et al. A prospective study of self-reported sleep duration and incident diabetes in women. Diabetes Care. 2003;26:380–4. doi: 10.2337/diacare.26.2.380. [DOI] [PubMed] [Google Scholar]
- 38.Nock NL, Li L, Larkin EK, Patel SR, Redline S. Empirical evidence for “syndrome Z”: a hierarchical 5-factor model of the metabolic syndrome incorporating sleep disturbance measures. Sleep. 2009;32:615–22. doi: 10.1093/sleep/32.5.615. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Patel SR, Malhotra A, White DP, Gottlieb DJ, Hu FB. Association between reduced sleep and weight gain in women. Am J Epidemiol. 2006;164:947–54. doi: 10.1093/aje/kwj280. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Patel SR, Hu FB. Short sleep duration and weight gain: a systematic review. Obesity. 2008;16:643–53. [DOI] [PMC free article] [PubMed]
- 41.Patel SR, Zhu X, Storfer-Isser A, Mehra R, Jenny NS, Tracy R, et al. Sleep duration and biomarkers of inflammation. Sleep. 2009;32:200–4. doi: 10.1093/sleep/32.2.200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Williams CJ, Hu FB, Patel SR, Mantzoros CS. Sleep duration and snoring in relation to biomarkers of cardiovascular disease risk among women with type 2 diabetes. Diabetes Care. 2007;30:1233–40. doi: 10.2337/dc06-2107. [DOI] [PubMed] [Google Scholar]
- 43.Collis SJ, Boulton SJ. Emerging links between the biological clock and the DNA damage response. Chromosoma. 2007;116:331–9. doi: 10.1007/s00412-007-0108-6. [DOI] [PubMed] [Google Scholar]
- 44.Irwin MR. Why sleep is important for health: a psychoneuroimmunology perspective. Annu Rev Psychol. 2015;66:143–72. doi: 10.1146/annurev-psych-010213-115205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Blask DE. Melatonin, sleep disturbance and cancer risk. Sleep Med Rev. 2009;13:257–64. doi: 10.1016/j.smrv.2008.07.007. [DOI] [PubMed] [Google Scholar]
- 46.Lauderdale DS, Knutson KL, Yan LL, Liu K, Rathouz PJ. Self-reported and measured sleep duration: how similar are they? Epidemiology. 2008;19:838–45. doi: 10.1097/EDE.0b013e318187a7b0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Lee S, Meyerhardt JA. Impact of diet and exercise on colorectal cancer. Hematol Oncol Clin North Am. 2022;36:471–89. doi: 10.1016/j.hoc.2022.02.004. [DOI] [PubMed] [Google Scholar]
- 48.Cho OH, Hwang KH. Association between sleep quality, anxiety and depression among Korean breast cancer survivors. Nurs Open. 2021;8:1030–7. doi: 10.1002/nop2.710. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Fortner BV, Stepanski EJ, Wang SC, Kasprowicz S, Durrence HH. Sleep and quality of life in breast cancer patients. J Pain Symptom Manag. 2022;24:471–80. doi: 10.1016/S0885-3924(02)00500-6. [DOI] [PubMed] [Google Scholar]
- 50.Zhou ES, Partridge AH, Syrjala KL, Michaud AL, Recklitis CJ. Evaluation and treatment of insomnia in adult cancer survivorship programs. J Cancer Surviv. 2017;11:74–9. doi: 10.1007/s11764-016-0564-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Reynolds-Cowie P, Fleming L. Living with persistent insomnia after cancer: a qualitative analysis of impact and management. Br J Health Psychol. 2021;26:33–49. doi: 10.1111/bjhp.12446. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data are from the Alliance for Clinical Trials in Oncology. Investigators may request access to this data per Alliance protocol as outlined below and as detailed at https://www.allianceforclinicaltrialsinoncology.org/main/public/standard.xhtml?path=%2FPublic%2FDatasharing. Per NCI National Clinical Trials Network (NCTN) guidelines, any investigator may submit a request for data from published Alliance or legacy ACOSOG, CALGB, or NCCTG trials. To submit a data request, the investigator should complete an Alliance Data Sharing Request Form and send it by e-mail to gro. NTCNecnailla@stpecnoc. Once received, the request will be forwarded to the Alliance Statistics and Data Center (SDC). The SDC will confirm the availability of the data. Once the SDC confirms availability, the investigator will be asked to provide documentation of Institutional Review Board (IRB) approval or exemption from their institution, as well as to submit an Alliance data release agreement. Once the IRB documentation and the data release agreement are received from the requesting investigator, the SDC will be notified that the requested data may be released. Questions about the process may be directed to gro. NTCNecnailla@stpecnoc.