Time-restricted eating to address persistent cancer-related fatigue among cancer survivors: A randomized controlled trial

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Kleckner, Carin L. Clingan, Shari M. Youngblood, Ian R. Kleckner, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5530166/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Apr, 2025 Read the published version in Supportive Care in Cancer → Version 1 posted 7 You are reading this latest preprint version Abstract Purpose: Time-restricted eating (TRE) helps regulate rest-activity rhythms, blood glucose, and other diurnally regulated energetics processes, which may have implications for persistent fatigue. In a randomized controlled trial, we tested the effects of TRE vs. control on fatigue in cancer survivorship. Methods: Adult cancer survivors were recruited who were 2 months to 2 years post-treatment and reported moderate to severe fatigue. Participants were randomized 1:1, TRE:control and all received individualized nutrition counseling. The TRE group self-selected a 10-hour eating window for 12 weeks. At baseline, week 6, and week 12, participants were asked to log eating instances, complete the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire (FACIT-F, higher score=less fatigue), and wear an actigraph and continuous glucose monitor. Results: Thirty participants completed baseline assessments and were randomized (77% female, 53% Black/African American, 43% White, 7% Hispanic; 54.1±14.7 years old; 87% with blood cancer); 25 completed 12-week assessments. TRE led to a meaningful reduction in fatigue at week 12 controlling for baseline levels (change in FACIT-F fatigue subscale=0.0±5.4 for control, 4.1±5.7 for TRE, p =0.11, effect size [ES]=0.70; clinically meaningful threshold=3.0 points). Glucose parameters (e.g., average interstitial glucose, average fasting glucose) tended to be lower and rest-activity rhythms tended to indicate more regularity for those in the TRE vs. control group at weeks 6 and 12, though differences were not statistically significant ( p >0.19). Conclusions: A 12-week, nutritionist-led TRE program led to less fatigue than control. Continued study of TRE patterns are warranted to optimize this eating pattern and address persistent cancer-related fatigue. Clinicaltrials.gov identifier: NCT05256888, registered 02/2022 Figures Figure 1 Figure 2 Introduction Cancer-related fatigue is one of the most prevalent and distressing symptoms experienced by cancer patients, with approximately 42% of cancer survivors reporting persistent fatigue more than 3 months post-treatment [ 1 ]. Unlike the tiredness from typical daily activities, cancer-related fatigue is more severe, persists despite rest, and interferes with daily functioning and quality of life [ 3 ]. It can persist for months or even years after treatment, contributing to a diminished capacity for physical and cognitive activities, emotional distress, and reduced social interactions [ 4 ]. Given its substantial negative impact on the lives of cancer survivors, effective strategies to mitigate cancer-related fatigue are of critical importance [ 5 ]. The factors underlying cancer-related fatigue are multifactorial and complex [ 38 ], and nutritional interventions may be able to address upstream factors [ 15 ]. Specifically, circadian rhythms are sometimes disrupted in cancer patients [ 35 , 37 ] and may precipitate and/or perpetuate fatigue [ 14 , 39 ]. Time-restricted eating (TRE), also known as prolonged nighttime fasting, has recently garnered attention for its potential to entrain and sustain circadian rhythm [ 16 , 18 ]. TRE is a dietary strategy that involves consuming all meals within a specific time window of less than 12 hours per day. By aligning food intake with the body’s natural biological clock, TRE may enhance sleep efficiency at night, allow the body to more reliably and accurately predict energy availability and expenditure, and promote increased energy levels during the day [ 8 ]. Scientific literature to support TRE as a strategy to address cancer-related fatigue is emerging, as TRE can positively influence metabolic and circadian health [ 17 , 42 ]. Animal studies have demonstrated that TRE can improve circadian rhythm robustness, which is linked to better sleep and reduced fatigue [ 7 , 13 ]. Additionally, preliminary single-arm human studies suggest that TRE is feasible among cancer survivors and may help alleviate fatigue [ 17 , 19 , 20 , 30 ]. However, randomized controlled trials are needed to evaluate TRE vs. a control group to estimate the specific effects of TRE on cancer-related fatigue. Herein, we conducted a small randomized controlled trial to test the feasibility of a randomized TRE study as well as test the hypothesis that TRE vs. a time- and attention-matched control intervention (nutrition counseling without a time component) can reduce cancer-related fatigue. Methods 2.1 Study design The Fatigue REDuction After cancer (FREDA) trial was a pilot randomized controlled trial conducted through University of Maryland Medical System from January 2023 to June 2024 (NCT05256888, registered February 2022). The research protocol was reviewed and approved by the University of Maryland Institutional Review Board (IRB; HP-00099067) and conducted in accordance with the Declaration of Helsinki. The primary aims were feasibility and to test the effects of TRE vs. an unrestricted eating group on cancer-related fatigue. Secondary aims were to evaluate the effects of TRE on glucose regulation and rest-activity rhythm, as described below. We targeted enrollment survivors of hematological malignancies given the high prevalence of persistent fatigue (58% [1]) and high interference of fatigue with daily activities in this population [40, 41]. 2.2 Eligibility criteria Inclusion criteria (Participants must…): be 2 months to 2 years post-treatment with chemotherapy, surgery, and/or radiation for hematologic malignancies or solid tumors; have a baseline level of fatigue, as assessed by responding 4 or higher to the question, “In the last week, how bad was your worst fatigue on a scale from 0-10?”; be at least 18 years old; be able to communicate in English; and have access to a smartphone or mobile device. Exclusion criteria (Participants must not…): already eat all their food within a window that is 10 hours or shorter most (six of seven) days per week; have a body mass index ≤18.5 kg/m 2 ; have surgery planned during the study duration, and have any contraindications to the proposed intervention (e.g., insulin-dependent diabetes, enteral or parenteral nutrition, recent history of an eating disorder). Individuals were eligible if they were on maintenance therapy with non-conventional chemotherapy (e.g. targeted therapy). 2.3 Procedures Participants consented to the study either on paper or electronically via Research Electronic Data Capture (REDCap) tools hosted at University of Maryland Baltimore [12, 22]. After consent, participants were in the study for approximately 14 weeks. During the baseline week (7 days), participants were asked to log their food; wear an actigraphy watch (MotionWatch8, CamNTech, Boerne, TX, USA); wear a continuous glucose monitor (FreeStyle Libre, Abbott Nutrition, Chicago, IL, USA); and complete questionnaires (described below). After baseline assessments, participants were randomized 1:1 to the TRE group (intervention) or the unrestricted eating group (control). The randomization table was generated in block sizes of 2 and 4 by the statistician (SZ) and concealed from the other study team members using REDCap; there was no stratification. All participants met with a licensed dietitian nutritionist (SMY) for individualized nutrition counseling. Those assigned to the TRE group were asked to meet recommendations within a self-selected 10-hour eating window while those in the control group were not given temporal restrictions. Participants were asked to follow the recommendations for 12 weeks. A coordinator or the nutritionist checked in with each participant at least every 2 weeks. The same data collection protocol was conducted at week 6 and week 12. Data collection and meetings were conducted completely remotely, and equipment was mailed to and from participants’ homes. 2.4 The control arm Participants met with the nutritionist after randomization for individualized counseling. Meetings were via phone or Zoom and lasted approximately 30-60 minutes. Participants discussed eating habits and set goals based on their individual needs—macronutrients, food groups, maximum servings of nutrient-poor selections, food preferences, culinary self-efficacy, etc. Participants were not asked to change the timing of their food intake. 2.5 Time-restricted eating (TRE) intervention Those randomized to TRE selected a 10-hour eating window based on schedule and preferences. We encouraged the eating window to be during the day and end several hours before bedtime. Aside from water, which was always allowed, only unsweetened tea and black coffee were allowed before the eating window; calorie-free foods and beverages such as chewing gum and diet soda were not allowed outside the eating window. Participants met with the same nutritionist as those in the control group for individualized nutrition counseling, and goals discussed during the counseling session were asked to be met within the eating window. To match expectancy, both groups were told that nutritional programs can help with fatigue, and we are not sure the restricted eating window will help or not. 2.6 Outcomes 2.6.1 Adherence Participants were declared adherent to TRE if their average eating window was ≤10 hours. Eating windows were assessed using the myCircadianClock smartphone application [26]; paper-based logs were permittable as an alternative to the app. We calculated the eating window from the first and last calorie entered every day at baseline, week 6, and week 12, then averaged the eating window across the 7 days. If a participant logged only one eating instance within a day or if the eating window was <4 hours, we declared that day to have missing data. 2.6.2 Fatigue Questionnaires were administered at baseline, week 6, and week 12. Fatigue was assessed using the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) [6] and the Brief Fatigue Inventory (BFI) [28]. The FACIT-F is a 40-item, validated patient-reported fatigue measure that is comprised of five subscales: physical well-being, social well-being, emotional well-being, functional well-being, and fatigue [6]. Participants respond how true various statements were over the last seven days such as “I feel fatigued” and “I have to limit my social activities because I am tired” with five response choices ranging from 0, “Not at all,” to 4, “Very much.” Scoring, which involves reversing some items, yields five subscale scores and a total score. A higher score indicates higher well-being/quality of life or less fatigue. The BFI is a 10-item fatigue questionnaire that is also validated and commonly used in oncology [28]. It captures fatigue now as well as the usual and worst fatigue in the last 24 hours from 0, “No fatigue,” to 10, “As bad as you can imagine.” It also includes six single-item questions regarding how fatigue has interfered with general activity, mood, etc., from 0, “Does not interfere” to 10, “Completely interferes.” The average of all 10 items yields a global fatigue score with a higher score indicating worse fatigue. Cronbach alpha reliability ranges from 0.82 to 0.97 [28]. 2.6.3. Body weight Participants were given a scale (Weight Watchers, Conair Corp., Stamford, CT) and were asked to record body weight weekly, soon after waking with minimal clothing. 2.6.4 Glucose monitoring Participants were provided a continuous glucose monitor (Freestyle Libre) to wear on the back of their upper arm for 7 days at baseline, 6 weeks, and 12 weeks. Interstitial glucose was recorded every 15 minutes, and data were extracted using LibreView (Abbott). Data were manually checked for quality and any traces that showed a large (>50 mg/dl) stepwise shift in average values or unreasonable values (>350 mg/dl) were removed. Average, daily maximums and minimums, fasting glucose, and coefficient of variation were extracted from glucose traces by a researcher blinded to treatment groups (LQ) [27]. 2.6.5 Actigraphy Participants were asked to wear a MotionWatch8 (CamNTech) on their wrist of choice for 24 hours per day for 7 days at baseline, 6 weeks, and 12 weeks. The actigraphy watch measured triaxial activity “counts” in 15-second epochs. Using MotionWare software (CamNTech), periods during which the watch was worn were manually selected by an assessor blinded to treatment group (RDE); parametric measures (cosine peak, amplitude, midline estimating statistic of rhythm [MESOR]) and non-parametric measures (interdaily stability, intradaily variability, activity in the 5 consecutive hours with the least activity, activity in the 10 consecutive hours with the most activity, relative amplitude) of activity were extracted [34]. 2.7 Statistical analysis Differences between groups (randomized vs. not and TRE vs. control) at baseline were assessed using a t -test for continuous variables, a ­χ 2 test for categorical variables. Linear mixed models were used to assess the intervention effects on fatigue and all mechanistic measures. We stated a priori that we would use an analysis of covariance (ANCOVA) to assess the effects of group at week 6 and week 12 but, due to the large amount of missing data, we decided that a mixed model would be more appropriate. Thus, results of both models are reported for FACIT-F fatigue outcomes. Mixed effect models were constructed with group, time (continuous), and group×time as fixed effects and participant as a random effect. Effect sizes were calculated as Cohen’s d (Δ TRE –Δ Control )/SD pooled , where Δ is the change from baseline to week 6 or week 12 and SD pooled is the standard deviation from all participants at baseline [23]. A two-sided p <0.05 was used to assess between-group differences in demographics and clinical characteristics, and a probability of p <0.15 was declared a priori to be considered meaningful for informing future research in regard to effects of time and group on outcomes [36]. No interim analyses were planned or performed. Results Fifty participants were enrolled between January 2023 and February 2024 and 30 were randomized ( Fig. 1 ; Table 1 ). Those who withdrew or were lost to follow-up before randomization tended to be older ( p =0.0048) and have less education than those who completed the study ( p =0.0098). Those who withdrew vs. were retained had similar distributions for race, sex, living situation, employment, cancer type, comorbidity index, and baseline FACIT-F fatigue subscale scores ( p >0.05). Those randomized to the TRE vs. control group had similar demographics and clinical characteristics (all p >0.085). To monitor adherence, eating windows were calculated from food logs entered into myCircadianClock [26] ( n =21) or a paper-based log ( n =2). However, only 23/50 (46%) participants provided any data at baseline, 19/30 (63%) provided data at week 6, and 13/30 (43%) provided data at week 12 ( Suppl. Fig. 1 ). The average eating window reported at baseline was 10.5±1.8 hours. Of those who logged eating instances, 9/10 of respondents in the TRE group consumed food within an eating window ≤10 hours at week 6 (8.9±0.6 hours) and 4/4 at week 12 (8.6±0.9 hours, Suppl. Table 1 ). On average, fatigue improved over time as measured using the FACIT-F fatigue subscale (mixed model effect of time, β±SE=0.17±0.09, p =0.059; Table 2 ). Further, there was a between-group difference in FACIT-F fatigue scores favoring the TRE group (group×time β±SE= -0.17±0.09, p =0.069). At week 6, the magnitude of FACIT-F fatigue subscale scores was higher (less fatigue) in the TRE group controlling for baseline values, but the between-group difference did not meet statistical significance (ANCOVA, change from baseline to week 6=2.5±4.5 for the TRE group vs. 0.9±7.7 in the control group, p =0.83, effect size [ES]=0.27; Fig. 2 ). At week 12, differences between groups were larger (4.1±5.7 for TRE vs. 0.0±5.5, p =0.11, ES=0.70). The improvements in fatigue in the TRE group exceeded the minimal clinically important difference (3.0 points [29]). Trends were similar as measured by the global BFI score and other subscales of the FACIT-F and BFI in that fatigue improved slightly from baseline to week 12 and the TRE group experienced greater benefits with small-moderate effect sizes on average ( Table 2 ). Among those who provided body weight data ( n =15 in the control group and n =10 in the TRE group), those in the control group tended to lose a small but statistically significant amount of weight over time (β±SE= -0.024±0.009 pounds/day, p =0.013) and those in the TRE group gained a small but statistically significant amount of weight over time (β±SE=0.031±0.015 pounds/day, p =0.038). The between-group difference was statistically significant (β±SE= -0.027±0.008, p =0.002). The effects of TRE vs. control on glucose regulation were measured using continuous glucose monitoring ( Suppl. Fig. 2 ). Glucose monitoring was feasible for about half of our active participants. Glucose parameters tended to be lower at week 6 and week 12 for those in the TRE group, though no measures met statistical significance ( p >0.25; Suppl. Fig. 3 , Suppl. Table 2 ). For example, average daily minimum was lower for those in the TRE group compared to the control group at week 6 (change from baseline= 4.4±16.0 mg/dl in the control group and -13.0±11.6 in the TRE group) and at week 12 (change from baseline= 0.7±17.7 mg/dl in the control group and -6.3±18.1 mg/dl in the TRE group, mixed model group×time estimate ± SE = 0.29±0.25, p =0.258). We collected actigraphy data to quantify the strength of participants’ rest-activity rhythm, or a person’s regular daily 24-hour pattern of being active and resting. Stronger rest-activity rhythms are reflected by high activity during the day and low activity at night (i.e., high fitted cosine amplitude) and regular movement and rest patterns each day (i.e., interdaily stability; Table 3 ). Actigraphy data were available from 33 participants and 24 contributed data for at least two time points ( Suppl. Fig. 4 ). Three participants removed their actigraphs at night, precluding our ability to calculate parametric rest-activity measures. The estimate for group×time interaction in mixed models for all rest-activity parameters suggested that TRE led to higher regulation of rest-activity rhythms, though this term did not reach statistical significance for any model ( p >0.19 for all parameters that reflect the degree of rhythm entrainment, Table 3 , Suppl. Fig. 5 ). In regard to safety, there were two grade 4 adverse events and none of these adverse events were attributed to the intervention or study procedures. Two hospitalizations occurred in the control group—one for shortness of breath and one for pneumonia. There was one grade 3 adverse event: approximately 2 weeks of nausea and diarrhea that led to significant weight loss in the TRE group. Discussion This is one of the first randomized controlled trials to test the effects of TRE on cancer-related fatigue. Throughout the 12-week trial, fatigue tended to be stable in the control group and tended to gradually decrease in the TRE group to a clinically meaningful degree (> 3 points), yielding a moderate effect size of 0.70 at week 12 as measured using the FACIT-F fatigue subscale (Table 2 ). Collection of continuous glucose monitor data and actigraphy was feasible for more than half of our participants, though some could not apply the glucose monitor on their own, chose not to wear the device(s), or did not return the device(s) to our lab. While participants did not necessarily have impairments in glucose regulation, TRE led to slight decreases in average and fasting interstitial glucose concentrations, which tends to reflect healthier levels. Similarly, actigraphy data suggest that TRE may help increase the robustness of rest-activity rhythms, but this study was not powered adequately to resolve group-level differences. Throughout the course of the study, we increased our engagement strategies and only two of our last 14 consents withdrew before randomization. Thus, after troubleshooting our recruitment and retention strategies, recruitment to the TRE study was feasible and participants were retained. These data support continued investigation into TRE to better understand how to leverage dietary patterns to regulate circadian rhythms and energy metabolism to address fatigue. These results build on promising single-arm interventional trials that support the use of TRE to regulate circadian rhythms and address cancer-related fatigue [ 16 , 18 ]. For example, in a single-arm TRE study, a cohort of survivors of mixed cancer types ( n = 36) reported less fatigue after two weeks (mean pre-post improvement of 5.3 points on the FACIT-F fatigue subscale, effect size = 0.55) [ 20 ]. In addition, breast cancer survivors ( n = 40) saw a pre-post improvement in fatigue after 12 weeks of TRE (median change of 1.0 points on the FACIT-F fatigue subscale) [ 30 ]. In populations other than cancer populations, studies tend to report increased energy levels that are sustained for up to one year or no increases in fatigue (e.g., [ 11 , 24 , 31 , 33 ]). TRE has shown benefits to glucose metabolism in other populations, including those with metabolic syndrome and diabetes [ 18 , 31 , 32 ], but not yet in the cancer population because it has not yet been tested [ 17 ]. We saw small improvements (reductions) in several glucose parameters, but our study was not powered to see statistically significant group-level effects. While cancer and chemotherapy can sometimes cause dysregulation of glucose parameters [ 10 ], and diabetes specifically is associated with cancer-related fatigue [ 21 ], not all cancer survivors have dysregulated glucose metabolism. Based on studies among people with diabetes [ 32 ], TRE may be particularly beneficial for glucose parameters for those with dysregulated glucose metabolism at baseline. Actigraphy is a useful measure for circadian rest-activity rhythms in the cancer population, and parametric and non-parametric measures are complementary in describing the strength of the diurnal rhythm. For example, Liu et al. used wrist-worn actigraphs to show that people with breast cancer had disrupted rest-activity rhythms even before chemotherapy began, and that rhythms were less robust after chemotherapy [ 25 ]. Rhythms with less robusticity were associated with more fatigue [ 25 ]. Consistently, in this small study with considerable inter-individual variability, we saw that TRE led to trends towards higher cosinar and relative amplitudes and higher interdaily stability, though a larger study is necessary to achieve adequate power. This study sets the stage for follow-on projects to further optimize TRE to address fatigue. The importance of the start time of the eating window is unknown, i.e., in relation to either daylight or an individual’s sleep patterns. Cancer-related fatigue is a multifaceted condition, and future research is warranted to explore who in particular will benefit from TRE in regard to cancer type, treatment type, clinical characteristics, or behavioral habits. Future research should also explore whether TRE can be combined with other interventions that entrain circadian rhythms, for example bright light therapy, for additive or synergistic effects. This study has several strengths. Our population was diverse in regard to sex/gender, age, and race, increasing the generalizability to other cancer survivors. Also, we completed all study activities completely remotely, facilitating the ability to implement and disseminate a TRE program in clinical practices in the future. Our study was randomized with known potential confounding factors distributed fairly equally, and therefore any differences between groups can be attributed to TRE. Further, we had an active control condition to help control for time, attention, expectation of benefit, and potential improvements in the quality of diet, which may help discern the specific effects of the TRE eating pattern. However, this study was not without limitations. Our drop-out rate was high at the beginning of our study, especially before randomization; but we were able to reduce dropout by increasing engagement later in the study. In addition, we recruited a heterogeneous population in regard to cancer type and treatment history; while that may increase generalizability, it may reduce our ability to see benefits if TRE is only effective for a subset of the eligible participants. Conclusions There has been a recent explosion of exploration into “chrononutrition,” “chronochemotherapy,” and other “chronomedicine” approaches to understand how we can manipulate and harness circadian processes to prevent and treat chronic illnesses [ 9 , 16 ]. Herein, we provide promising results from a randomized controlled trial that TRE may be able to alleviate persistent cancer-related fatigue. Given the appeal of TRE in regard to accessibility, low cost, low risk, and potential benefits, the results herein support follow-on studies to continue to evaluate TRE to address fatigue and other supportive care outcomes, as well as understand the underlying mediators so that we can tailor behavioral interventions and facilitate survivors’ recovery to life “before cancer.” Declarations Author Contribution Conceptualization: AK; Methodology: AK, IRK, SZ; Study coordination, recruitment, intervention delivery, and data collection: CLC, SMY, AK; Clinical Oversight: AZB, AE; Data analysis: AK, IRK, SZ, LQ, RDE; Writing - original draft preparation: AK; Writing - review and editing: AK, CLC, SMY, IRK, LQ, RDE, SZ, ENCM, SP, AZB, AE; Funding acquisition: AK; Resources: AK, ENCM, SP; Supervision: AK. Acknowledgments We thank Maygan McMahon, Roland Park High School, for help with analyzing the adherence data and Sumedha Shastry, Centennial High School, for help analyzing the continuous glucose data. This project was supported by the Accelerated Translational Incubator Pilot (ATIP) Grant Program through the Institute for Clinical and Translational Research (ICTR; UL1TR003098 to Daniel Ford) as well as funds through the Maryland Department of Health's Cigarette Restitution Fund Program (no. CH-649-CRF). LQ was supported by the University of Maryland Medical System Foundation Nathan Schnaper Fund and the National Cancer Institute (R25CA186872 to Bret A. Hassel). 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Fatigue Inventory Cancer 85: 1186-1196 Nordin A, Taft C, Lundgren-Nilsson A, Dencker A (2016) Minimal important differences for fatigue patient reported outcome measures-a systematic review BMC Med Res Methodol 16: 62 O'Donnell E, Shapiro Y, Comander A, Isakoff S, Moy B, Spring L, Wander S, Kuter I, Shin J, Specht M, Kournioti C, Hu B, Sullivan C, Winters L, Horick N, Peppercorn J (2022) Pilot study to assess prolonged overnight fasting in breast cancer survivors (longfast) Breast Cancer Res Treat 193: 579-587 Parr EB, Devlin BL, Radford BE, Hawley JA (2020) A Delayed Morning and Earlier Evening Time-Restricted Feeding Protocol for Improving Glycemic Control and Dietary Adherence in Men with Overweight/Obesity: A Randomized Controlled Trial Nutrients 12 Parr EB, Radford BE, Hall RC, Steventon-Lorenzen N, Flint SA, Siviour Z, Plessas C, Halson SL, Brennan L, Kouw IWK, Johnston RD, Devlin BL, Hawley JA (2024) Comparing the effects of time-restricted eating on glycaemic control in people with type 2 diabetes with standard dietetic practice: A randomised controlled trial Diabetes Res Clin Pract 217: 111893 Ravussin E, Beyl RA, Poggiogalle E, Hsia DS, Peterson CM (2019) Early Time-Restricted Feeding Reduces Appetite and Increases Fat Oxidation But Does Not Affect Energy Expenditure in Humans Obesity (Silver Spring) 27: 1244-1254 Rogers VE, Zhu S, Mandrell BN, Ancoli-Israel S, Liu L, Hinds PS (2020) Relationship between circadian activity rhythms and fatigue in hospitalized children with CNS cancers receiving high-dose chemotherapy Support Care Cancer 28: 1459-1467 Roscoe JA, Morrow GR, Hickok JT, Bushunow P, Matteson S, Rakita D, Andrews PL (2002) Temporal interrelationships among fatigue, circadian rhythm and depression in breast cancer patients undergoing chemotherapy treatment Support Care Cancer 10: 329-336 Rubinstein LV, Korn EL, Freidlin B, Hunsberger S, Ivy SP, Smith MA (2005) Design issues of randomized phase II trials and a proposal for phase II screening trials J Clin Oncol 23: 7199-7206 Schmidt ME, Semik J, Habermann N, Wiskemann J, Ulrich CM, Steindorf K (2016) Cancer-related fatigue shows a stable association with diurnal cortisol dysregulation in breast cancer patients Brain Behav Immun 52: 98-105 Sleight AG, Crowder SL, Skarbinski J, Coen P, Parker NH, Hoogland AI, Gonzalez BD, Playdon MC, Cole S, Ose J, Murayama Y, Siegel EM, Figueiredo JC, Jim HSL (2022) A New Approach to Understanding Cancer-Related Fatigue: Leveraging the 3P Model to Facilitate Risk Prediction and Clinical Care Cancers (Basel) 14 Starreveld DEJ, Habers GEA, Valdimarsdottir HB, Kessels R, Daniels LA, van Leeuwen FE, Bleiker EMA (2021) Cancer-related Fatigue in Relation to Chronotype and Sleep Quality in (Non-)Hodgkin Lymphoma Survivors J Biol Rhythms 36: 71-83 Suzuki K, Kobayashi N, Ogasawara Y, Shimada T, Yahagi Y, Sugiyama K, Takahara S, Saito T, Minami J, Yokoyama H, Kamiyama Y, Katsube A, Kondo K, Yanagisawa H, Aiba K, Yano S (2018) Clinical significance of cancer-related fatigue in multiple myeloma patients Int J Hematol 108: 580-587 Wang XS (2002) Clinical Factors Associated With Cancer-Related Fatigue in Patients Being Treated for Leukemia and Non-Hodgkin's Lymphoma Journal of Clinical Oncology 20: 1319-1328 Wilkinson MJ, Manoogian ENC, Zadourian A, Lo H, Fakhouri S, Shoghi A, Wang X, Fleischer JG, Navlakha S, Panda S, Taub PR (2020) Ten-Hour Time-Restricted Eating Reduces Weight, Blood Pressure, and Atherogenic Lipids in Patients with Metabolic Syndrome Cell Metab 31: 1-13 Tables Table 1. Demographics, clinical characteristics, and lifestyle habits a Consented (n=50) Randomized (n=30) Control (n=15) Time-restricted eating (n=15) Characteristic Age (years) 58.2±13.7 54.1±14.7 b 53.7±16.8 54.6±12.7 Sex Female 36 (72.0%) 23 (76.7%) 10 (66.7%) 13 (86.7%) Male 14 (28.0%) 7 (23.3%) 5 (33.3%) 2 (13.3%) Race Black/African American 24 (48.0%) 16 (53.3%) 6 (40.0%) 10 (66.7%) White 24 (48.0%) 13 (43.3%) 8 (53.3%) 5 (33.3%) Other 1 (2.0%) 0 0 0 Mixed race 1 (2.0%) 1 (3.3%) 1 (6.7%) 0 Ethnicity Hispanic 2 (4.0%) 2 (6.7%) 0 2 (13.3%) Non-Hispanic 48 (96.0%) 28 (93.3%) 15 (100%) 13 (86.7%) Living situation b Married or in long-term committed relationship 23 (46.0%) 16 (53.3%) 6 (40.0%) 10 (66.7%) Single, divorced, or widowed 13 (26.0%) 10 (33.3%) 7 (46.7%) 3 (20.0%) Employment status Employed full-time (≥35 hours/week) 16 (32.0%) 12 (40.0%) 8 (53.3%) 4 (26.7%) Employed part-time (<35 hours/week) 5 (10.0%) 4 (13.3%) 3 (20.0%) 1 (6.7%) Employed, unknown hours/week 1 (2.0%) 1 (3.3%) 0 1 (6.7%) Home Maker 2 (4.0%) 2 (6.7%) 1 (6.7%) 1 (6.7%) Retired 8 (16.0%) 4 (13.3%) 0 4 (26.7%) Unemployed/on leave 4 (8.0%) 3 (10%) 1 (6.7%) 2 (13.3%) Education High school 7 (14.0%) 3 (10.0%) b 1 (6.7%) 2 (13.3%) Some college 7 (14.0%) 5 (16.7%) 3 (20.0%) 2 (13.3%) 4-Year college degree 8 (16.0%) 5 (16.7%) 4 (26.7%) 1 (6.7%) Graduate school 13 (26.0%) 13 (43.4%) 5 (33.3%) 8 (53.3%) Body mass index (kg/m 2 ) 30.4±5.9 29.8±5.8 28.7±4.3 30.9±7.0 Exercise habits Meets WHO c recommendations 24/36 (66.7%) 22 (73.3%) 11 (73.3%) 11 (73.3%) Does not meet WHO recommendations 12/36 (33.3%) 8 (26.7%) 4 (26.7%) 4 (26.7%) Cancer type Leukemia 8 (16.0%) 6 (20.0%) 4 (36.7%) 2 (13.3%) Lymphoma 9 (18.0%) 4 (13.3%) 1 (6.7%) 3 (20.0%) Multiple myeloma 27 (54.0%) 16 (53.3%) 8 (53.3%) 8 (53.3%) Solid tumor 6 (12.0%) 4 (13.3%) 2 (13.3%) 2 (13.3%) Treatment for cancer Surgery 8 (16.0%) 6 (20.0%) 4 (26.7%) 2 (13.3%) Chemotherapy 47 (94.0%) 28 (93.3%) 14 (93.3%) 14 (93.3%) Radiation 8 (16.0%) 7 (23.3%) 4 (26.7%) 3 (20.0%) Stem cell transplant 20 (40.0%) 11 (36.7%) 5 (33.3%) 6 (40.0%) CAR-T cell therapy 11 (22.0%) 5 (16.7%) 3 (20.0%) 2 (13.3%) Charlson Comorbidity Index 2.9±1.7 2.6±1.3 2.7±1.0 2.5±1.5 a Some missing data exist. b Differences were observed between those randomized and not randomized ( t -test or χ 2 likelihood ratio test, p <0.05). There were no statistically significant differences between time-restricted eating and control groups. c World Health Organization, a combination of moderate- and vigorous-intensity physical activity achieving at least 600 metabolic equivalent-minutes per week, as measuring using a self-administered Global Physical Activity Questionnaire [2]. Table 2. Fatigue over time by group Fatigue measure Directionality Group Baseline (Mean ± SD) Week 6 (Mean ± SD) Effect size of TRE vs. Control* at Week 6 Week 12 (Mean ± SD) Effect size of TRE vs. Control at Week 12 Control n 15 13 14 TRE n 15 12 11 FACIT-F Physical well-being Higher is better Control 22.0 ± 4.6 23.1 ± 2.8 0.33 22.9 ± 3.7 a,b** 0.45 TRE 18.5 ± 6.1 20.9 ± 4.1 21.7 ± 5.1 FACIT-F Social well-being Higher is better Control 22.9 ± 4.2 23.0 ± 3.6 -0.19 22.8 ± 5.1 -0.17 TRE 22.5 ± 4.8 21.1 ± 5.4 21.9 ± 4.0 FACIT-F Emotional well-being Higher is better Control 19.0 ± 3.1 20.5 ± 2.3 -0.06 20.5 ± 2.8 a 0.44 TRE 18.9 ± 3.5 18.9 ± 3.4 20.8 ± 2.6 FACIT-F Functional well-being Higher is better Control 18.8 ± 5.0 19.6 ± 4.7 0.03 20.2 ± 6.7 -0.33 TRE 18.5 ± 5.8 18.8 ± 5.0 18.7 ± 5.4 FACIT-F Fatigue-specific well-being Higher is better Control 36.7 ± 9.2 37.8 ± 8.6 0.25 37.2 ± 9.1 a,c 0.70 TRE 33.8 ± 11.4 35.2 ± 10.9 38.7 ± 9.2 FACIT-F Total score Higher is better Control 120.1 ± 21.3 123.9 ± 14.2 0.14 123.7 ± 22.6 0.30 TRE 112.1 ± 26.8 114.9 ± 20.4 121.8 ± 21.6 Brief Fatigue Inventory: Global score Lower is better Control 3.4 ± 1.8 2.6 ± 1.8 0.08 3.5 ± 2.8 c -0.53 TRE 3.9 ± 2.7 3.3 ± 2.5 2.8 ± 2.3 Brief Fatigue Inventory: Usual fatigue Lower is better Control 4.3 ± 2.4 3.4 ± 2.5 0.27 4.1 ± 2.6 a -0.45 TRE 4.4 ± 2.9 3.8 ± 2.6 2.8 ± 3.1 Brief Fatigue Inventory: Fatigue at its worst Lower is better Control 5.1 ± 2.7 3.2 ± 2.0* 0.71 2.8 ± 2.4 a** -0.37 TRE 5.1 ± 3.1 4.8 ± 3.2 2.6 ± 3.4 Brief Fatigue Inventory: Interference of fatigue with enjoyment of life Lower is better Control 3.1 ± 3.0 2.3 ± 2.2 0.07 2.9 ± 2.4 a -0.43 TRE 3.6 ± 3.6 3.4 ± 3.4 2.5 ± 2.8 *Effect size is calculated from the change scores from baseline to week 6 or baseline to week 12. a p <0.15 over time in a mixed model b p <0.15 by group in a mixed model c p <0.15 for group×time in a mixed model ** p <0.05 Table 3. Results of mixed model analyses evaluating the effects of TRE vs. control on rest-activity parameters ( n =67 observations for non-parametric measures and n =65 for parametric measures). Parameter Definition Interpretation Effect of group (TRE vs. Control, Estimate ± SE) p -value Effect of time (Estimate ± SE) p -value Effect of group (TRE vs. control)*Time (Estimate ± SE) p -value Interdaily stability The degree of regularity in the rest-activity pattern (range 0-1) Higher is better -0.016±0.020 0.421 0.002±0.003 0.5386 0.003±0.003 0.194 Intradaily variability The degree of fragmentation of rest-activity periods (range 0-2) Lower is better -0.028±0.042 0.505 0.005±0.006 0.3801 -0.001±0.006 0.857 Least 5 average The average activity level for the sequence of the least five active hours (from averaged 24-hour periods of an overlay of all days) Lower is better -114.5±132.1 0.394 -7.45±14.8 0.6168 -14.5±14.8 0.334 Least 5- Start hour The onset of the "Least 5" sequence [range (midnight) to 24 (midnight the following day)]* Descriptive -0.439±0.221 0.057 -0.004±0.028 0.8768 0.035±0.028 0.216 Most 10 average The average activity level for the sequence of the most 10 active hours (from averaged 24-hour periods of an overlay of all days) Higher is better 158.6±716.3 0.827 20.4±105.6 0.8478 68.4±105.6 0.521 Most 10- Start hour The temporal onset of the "Most 10" sequence [range 0 (midnight) to 24 (midnight the following day)] Descriptive -0.398±0.378 0.303 -0.030±0.037 0.4279 -0.004±0.037 0.903 Relative amplitude [(Most 10)-(Least 5)]/[(Most 10)+(Least 5)] The range is 0-1. Higher is better 0.023±0.018 0.217 0.000±0.002 0.9716 0.003±0.002 0.239 Fitted cosine Peak Where in the 24-hour period the peak is [range 0 (midnight) – 1 (midnight the next day)] Descriptive -0.013±0.012 0.285 0.001±0.001 0.464 0.001±0.001 0.432 Fitted cosine Amplitude Amplitude of fitted cosine curve (positive number, no defined range) Higher is better 0.187±1.849 0.920 0.173±0.263 0.5164 0.325±0.263 0.226 Fitted cosine MESOR Midline estimating statistic of rhythm from the cosine curve (positive number, no defined range) Neither -0.004±1.962 0.998 0.230±0.236 0.3366 0.174±0.236 0.467 *For individuals in which the L5 started before midnight, the time was converted to the hour(s) before midnight, for example “-1” for 11pm. Additional Declarations No competing interests reported. Supplementary Files suppl.docx Cite Share Download PDF Status: Published Journal Publication published 05 Apr, 2025 Read the published version in Supportive Care in Cancer → Version 1 posted Editorial decision: Revision requested 18 Feb, 2025 Reviews received at journal 15 Feb, 2025 Reviewers agreed at journal 17 Jan, 2025 Reviewers invited by journal 15 Jan, 2025 Editor assigned by journal 14 Jan, 2025 Submission checks completed at journal 02 Dec, 2024 First submitted to journal 26 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5530166","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":385407250,"identity":"da9014db-2673-4846-953a-1aac1cae2768","order_by":0,"name":"Amber S. 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P-values are a result of Analysis of Covariance (ANCOVA) models constructed at week 6 (effect size=0.27) and at week 12 (effect size=0.70) with baseline values as covariates.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5530166/v1/152781c714974b99aa7049f0.jpeg"},{"id":80082032,"identity":"9250ee7c-b0c2-483e-aca4-cfb37d7c2d2f","added_by":"auto","created_at":"2025-04-07 16:05:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1464677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5530166/v1/858feb6d-bd41-46c5-95ca-795fdd854138.pdf"},{"id":72300852,"identity":"ee5352c7-1f6b-490c-8e31-4fbaf127dade","added_by":"auto","created_at":"2024-12-25 01:24:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1368736,"visible":true,"origin":"","legend":"","description":"","filename":"suppl.docx","url":"https://assets-eu.researchsquare.com/files/rs-5530166/v1/3fa797fd62a47417d7e6f725.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Time-restricted eating to address persistent cancer-related fatigue among cancer survivors: A randomized controlled trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer-related fatigue is one of the most prevalent and distressing symptoms experienced by cancer patients, with approximately 42% of cancer survivors reporting persistent fatigue more than 3 months post-treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Unlike the tiredness from typical daily activities, cancer-related fatigue is more severe, persists despite rest, and interferes with daily functioning and quality of life [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It can persist for months or even years after treatment, contributing to a diminished capacity for physical and cognitive activities, emotional distress, and reduced social interactions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Given its substantial negative impact on the lives of cancer survivors, effective strategies to mitigate cancer-related fatigue are of critical importance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe factors underlying cancer-related fatigue are multifactorial and complex [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and nutritional interventions may be able to address upstream factors [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Specifically, circadian rhythms are sometimes disrupted in cancer patients [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and may precipitate and/or perpetuate fatigue [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Time-restricted eating (TRE), also known as prolonged nighttime fasting, has recently garnered attention for its potential to entrain and sustain circadian rhythm [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. TRE is a dietary strategy that involves consuming all meals within a specific time window of less than 12 hours per day. By aligning food intake with the body\u0026rsquo;s natural biological clock, TRE may enhance sleep efficiency at night, allow the body to more reliably and accurately predict energy availability and expenditure, and promote increased energy levels during the day [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eScientific literature to support TRE as a strategy to address cancer-related fatigue is emerging, as TRE can positively influence metabolic and circadian health [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Animal studies have demonstrated that TRE can improve circadian rhythm robustness, which is linked to better sleep and reduced fatigue [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, preliminary single-arm human studies suggest that TRE is feasible among cancer survivors and may help alleviate fatigue [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, randomized controlled trials are needed to evaluate TRE vs. a control group to estimate the specific effects of TRE on cancer-related fatigue.\u003c/p\u003e \u003cp\u003eHerein, we conducted a small randomized controlled trial to test the feasibility of a randomized TRE study as well as test the hypothesis that TRE vs. a time- and attention-matched control intervention (nutrition counseling without a time component) can reduce cancer-related fatigue.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003e2.1 Study design\u003c/h2\u003e\n\u003cp\u003eThe Fatigue REDuction After cancer (FREDA) trial was a pilot randomized controlled trial conducted through University of Maryland Medical System from January 2023 to June 2024 (NCT05256888, registered February 2022). The research protocol was reviewed and approved by the University of Maryland Institutional Review Board (IRB; HP-00099067) and conducted in accordance with the Declaration of Helsinki. The primary aims were feasibility and to test the effects of TRE vs. an unrestricted eating group on cancer-related fatigue. Secondary aims were to evaluate the effects of TRE on glucose regulation and rest-activity rhythm, as described below. We targeted enrollment survivors of hematological malignancies given the high prevalence of persistent fatigue (58% [1]) and high interference of fatigue with daily activities in this population [40, 41].\u003c/p\u003e\n\n\u003ch2\u003e2.2 Eligibility criteria\u003c/h2\u003e\n\u003cp\u003eInclusion criteria (Participants must\u0026hellip;): be 2 months to 2 years post-treatment with chemotherapy, surgery, and/or radiation for hematologic malignancies or solid tumors; have a baseline level of fatigue, as assessed by responding 4 or higher to the question, \u0026ldquo;In the last week, how bad was your worst fatigue on a scale from 0-10?\u0026rdquo;; be at least 18 years old; be able to communicate in English; and have access to a smartphone or mobile device. Exclusion criteria (Participants must not\u0026hellip;): already eat all their food within a window that is 10 hours or shorter most (six of seven) days per week; have a body mass index \u0026le;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e; have surgery planned during the study duration, and have any contraindications to the proposed intervention (e.g., insulin-dependent diabetes, enteral or parenteral nutrition, recent history of an eating disorder). Individuals were eligible if they were on maintenance therapy with non-conventional chemotherapy (e.g. targeted therapy).\u003c/p\u003e\n\n\u003ch2\u003e2.3 Procedures\u003c/h2\u003e\n\u003cp\u003eParticipants consented to the study either on paper or electronically via Research Electronic Data Capture (REDCap) tools hosted at University of Maryland Baltimore [12, 22]. After consent, participants were in the study for approximately 14 weeks. During the baseline week (7 days), participants were asked to log their food; wear an actigraphy watch (MotionWatch8, CamNTech, Boerne, TX, USA); wear a continuous glucose monitor (FreeStyle Libre, Abbott Nutrition, Chicago, IL, USA); and complete questionnaires (described below). After baseline assessments, participants were randomized 1:1 to the TRE group (intervention) or the unrestricted eating group (control). The randomization table was generated in block sizes of 2 and 4 by the statistician (SZ) and concealed from the other study team members using REDCap; there was no stratification. All participants met with a licensed dietitian nutritionist (SMY) for individualized nutrition counseling. Those assigned to the TRE group were asked to meet recommendations within a self-selected 10-hour eating window while those in the control group were not given temporal restrictions. Participants were asked to follow the recommendations for 12 weeks. A coordinator or the nutritionist checked in with each participant at least every 2 weeks. The same data collection protocol was conducted at week 6 and week 12. Data collection and meetings were conducted completely remotely, and equipment was mailed to and from participants\u0026rsquo; homes.\u003c/p\u003e\n\n\u003ch2\u003e2.4 The control arm\u003c/h2\u003e\n\u003cp\u003eParticipants met with the nutritionist after randomization for individualized counseling. Meetings were via phone or Zoom and lasted approximately 30-60 minutes. Participants discussed eating habits and set goals based on their individual needs\u0026mdash;macronutrients, food groups, maximum servings of nutrient-poor selections, food preferences, culinary self-efficacy, etc. Participants were not asked to change the timing of their food intake.\u003c/p\u003e\n\n\u003ch2\u003e2.5 Time-restricted eating (TRE) intervention\u003c/h2\u003e\n\u003cp\u003eThose randomized to TRE selected a 10-hour eating window based on schedule and preferences. We encouraged the eating window to be during the day and end several hours before bedtime. Aside from water, which was always allowed, only unsweetened tea and black coffee were allowed before the eating window; calorie-free foods and beverages such as chewing gum and diet soda were not allowed outside the eating window. Participants met with the same nutritionist as those in the control group for individualized nutrition counseling, and goals discussed during the counseling session were asked to be met within the eating window. To match expectancy, both groups were told that nutritional programs can help with fatigue, and we are not sure the restricted eating window will help or not.\u003c/p\u003e\n\n\u003ch2\u003e2.6 Outcomes\u003c/h2\u003e\n\u003ch3\u003e2.6.1 Adherence\u003c/h3\u003e\n\u003cp\u003eParticipants were declared adherent to TRE if their average eating window was \u0026le;10 hours. Eating windows were assessed using the myCircadianClock smartphone application [26]; paper-based logs were permittable as an alternative to the app. We calculated the eating window from the first and last calorie entered every day at baseline, week 6, and week 12, then averaged the eating window across the 7 days. If a participant logged only one eating instance within a day or if the eating window was \u0026lt;4 hours, we declared that day to have missing data.\u003c/p\u003e\n\n\u003ch3\u003e2.6.2 Fatigue\u003c/h3\u003e\n\u003cp\u003eQuestionnaires were administered at baseline, week 6, and week 12. Fatigue was assessed using the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) [6] and the Brief Fatigue Inventory (BFI) [28]. The FACIT-F is a 40-item, validated patient-reported fatigue measure that is comprised of five subscales: physical well-being, social well-being, emotional well-being, functional well-being, and fatigue [6]. Participants respond how true various statements were over the last seven days such as \u0026ldquo;I feel fatigued\u0026rdquo; and \u0026ldquo;I have to limit my social activities because I am tired\u0026rdquo; with five response choices ranging from 0, \u0026ldquo;Not at all,\u0026rdquo; to 4, \u0026ldquo;Very much.\u0026rdquo; Scoring, which involves reversing some items, yields five subscale scores and a total score. A higher score indicates higher well-being/quality of life or less fatigue. The BFI is a 10-item fatigue questionnaire that is also validated and commonly used in oncology [28]. It captures fatigue \u003cem\u003enow\u003c/em\u003e as well as the \u003cem\u003eusual\u003c/em\u003e and \u003cem\u003eworst\u003c/em\u003e fatigue in the last 24 hours from 0, \u0026ldquo;No fatigue,\u0026rdquo; to 10, \u0026ldquo;As bad as you can imagine.\u0026rdquo; It also includes six single-item questions regarding how fatigue has interfered with general activity, mood, etc., from 0, \u0026ldquo;Does not interfere\u0026rdquo; to 10, \u0026ldquo;Completely interferes.\u0026rdquo; The average of all 10 items yields a global fatigue score with a higher score indicating worse fatigue. Cronbach alpha reliability ranges from 0.82 to 0.97 [28].\u003c/p\u003e\n\n\u003ch3\u003e2.6.3. Body weight\u003c/h3\u003e\n\u003cp\u003eParticipants were given a scale (Weight Watchers, Conair Corp., Stamford, CT) and were asked to record body weight weekly, soon after waking with minimal clothing.\u003c/p\u003e\n\n\u003ch3\u003e2.6.4 Glucose monitoring\u003c/h3\u003e\n\u003cp\u003eParticipants were provided a continuous glucose monitor (Freestyle Libre) to wear on the back of their upper arm for 7 days at baseline, 6 weeks, and 12 weeks. Interstitial glucose was recorded every 15 minutes, and data were extracted using LibreView (Abbott). Data were manually checked for quality and any traces that showed a large (\u0026gt;50 mg/dl) stepwise shift in average values or unreasonable values (\u0026gt;350 mg/dl) were removed. Average, daily maximums and minimums, fasting glucose, and coefficient of variation were extracted from glucose traces by a researcher blinded to treatment groups (LQ) [27].\u003c/p\u003e\n\n\u003ch3\u003e2.6.5 Actigraphy\u003c/h3\u003e\n\u003cp\u003eParticipants were asked to wear a MotionWatch8 (CamNTech) on their wrist of choice for 24 hours per day for 7 days at baseline, 6 weeks, and 12 weeks. The actigraphy watch measured triaxial activity \u0026ldquo;counts\u0026rdquo; in 15-second epochs. Using MotionWare software (CamNTech), periods during which the watch was worn were manually selected by an assessor blinded to treatment group (RDE); parametric measures (cosine peak, amplitude, midline estimating statistic of rhythm [MESOR]) and non-parametric measures (interdaily stability, intradaily variability, activity in the 5 consecutive hours with the least activity, activity in the 10 consecutive hours with the most activity, relative amplitude) of activity were extracted [34].\u003c/p\u003e\n\n\u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e\n\u003cp\u003eDifferences between groups (randomized vs. not and TRE vs. control) at baseline were assessed using a \u003cem\u003et\u003c/em\u003e-test for continuous variables, a \u0026shy;\u0026chi;\u003csup\u003e2\u003c/sup\u003e test for categorical variables. Linear mixed models were used to assess the intervention effects on fatigue and all mechanistic measures. We stated \u003cem\u003ea priori \u003c/em\u003ethat we would use an analysis of covariance (ANCOVA) to assess the effects of group at week 6 and week 12 but, due to the large amount of missing data, we decided that a mixed model would be more appropriate. Thus, results of both models are reported for FACIT-F fatigue outcomes. Mixed effect models were constructed with group, time (continuous), and group\u0026times;time as fixed effects and participant as a random effect. Effect sizes were calculated as Cohen\u0026rsquo;s d (\u0026Delta;\u003csub\u003eTRE\u003c/sub\u003e \u0026ndash;\u0026Delta;\u003csub\u003eControl\u003c/sub\u003e)/SD\u003csub\u003epooled\u003c/sub\u003e, where \u0026Delta; is the change from baseline to week 6 or week 12 and SD\u003csub\u003epooled\u003c/sub\u003e is the standard deviation from all participants at baseline [23]. A two-sided \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 was used to assess between-group differences in demographics and clinical characteristics, and a probability of \u003cem\u003ep\u003c/em\u003e\u0026lt;0.15 was declared \u003cem\u003ea priori\u003c/em\u003e to be considered meaningful for informing future research in regard to effects of time and group on outcomes [36]. No interim analyses were planned or performed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFifty participants were enrolled between January 2023 and February 2024 and 30 were randomized (\u003cstrong\u003eFig. 1\u003c/strong\u003e; \u003cstrong\u003eTable 1\u003c/strong\u003e). Those who withdrew or were lost to follow-up before randomization tended to be older (\u003cem\u003ep\u003c/em\u003e=0.0048) and have less education than those who completed the study (\u003cem\u003ep\u003c/em\u003e=0.0098). Those who withdrew vs. were retained had similar distributions for race, sex, living situation, employment, cancer type, comorbidity index, and baseline FACIT-F fatigue subscale scores (\u003cem\u003ep\u003c/em\u003e\u0026gt;0.05). Those randomized to the TRE vs. control group had similar demographics and clinical characteristics (all \u003cem\u003ep\u003c/em\u003e\u0026gt;0.085).\u003c/p\u003e\n\u003cp\u003eTo monitor adherence, eating windows were calculated from food logs entered into myCircadianClock [26] (\u003cem\u003en\u003c/em\u003e=21) or a paper-based log (\u003cem\u003en\u003c/em\u003e=2). However, only 23/50 (46%) participants provided any data at baseline, 19/30 (63%) provided data at week 6, and 13/30 (43%) provided data at week 12 (\u003cstrong\u003eSuppl. Fig. 1\u003c/strong\u003e). The average eating window reported at baseline was 10.5\u0026plusmn;1.8 hours. Of those who logged eating instances, 9/10 of respondents in the TRE group consumed food within an eating window \u0026le;10 hours at week 6 (8.9\u0026plusmn;0.6 hours) and 4/4 at week 12 (8.6\u0026plusmn;0.9 hours, \u003cstrong\u003eSuppl. Table 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eOn average, fatigue improved over time as measured using the FACIT-F fatigue subscale (mixed model effect of time, \u0026beta;\u0026plusmn;SE=0.17\u0026plusmn;0.09, \u003cem\u003ep\u003c/em\u003e=0.059; \u003cstrong\u003eTable 2\u003c/strong\u003e). Further, there was a between-group difference in FACIT-F fatigue scores favoring the TRE group (group\u0026times;time \u0026beta;\u0026plusmn;SE= -0.17\u0026plusmn;0.09, \u003cem\u003ep\u003c/em\u003e=0.069). At week 6, the magnitude of FACIT-F fatigue subscale scores was higher (less fatigue) in the TRE group controlling for baseline values, but the between-group difference did not meet statistical significance (ANCOVA, change from baseline to week 6=2.5\u0026plusmn;4.5 for the TRE group vs. 0.9\u0026plusmn;7.7 in the control group, \u003cem\u003ep\u003c/em\u003e=0.83, effect size [ES]=0.27; \u003cstrong\u003eFig. 2\u003c/strong\u003e). At week 12, differences between groups were larger (4.1\u0026plusmn;5.7 for TRE vs. 0.0\u0026plusmn;5.5, \u003cem\u003ep\u003c/em\u003e=0.11, ES=0.70). The improvements in fatigue in the TRE group exceeded the minimal clinically important difference (3.0 points [29]). Trends were similar as measured by the global BFI score and other subscales of the FACIT-F and BFI in that fatigue improved slightly from baseline to week 12 and the TRE group experienced greater benefits with small-moderate effect sizes on average (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eAmong those who provided body weight data (\u003cem\u003en\u003c/em\u003e=15 in the control group and \u003cem\u003en\u003c/em\u003e=10 in the TRE group), those in the control group tended to lose a small but statistically significant amount of weight over time (\u0026beta;\u0026plusmn;SE= -0.024\u0026plusmn;0.009 pounds/day, \u003cem\u003ep\u003c/em\u003e=0.013) and those in the TRE group gained a small but statistically significant amount of weight over time (\u0026beta;\u0026plusmn;SE=0.031\u0026plusmn;0.015 pounds/day, \u003cem\u003ep\u003c/em\u003e=0.038). The between-group difference was statistically significant (\u0026beta;\u0026plusmn;SE= -0.027\u0026plusmn;0.008, \u003cem\u003ep\u003c/em\u003e=0.002).\u003c/p\u003e\n\u003cp\u003eThe effects of TRE vs. control on glucose regulation were measured using continuous glucose monitoring (\u003cstrong\u003eSuppl. Fig. 2\u003c/strong\u003e). Glucose monitoring was feasible for about half of our active participants. Glucose parameters tended to be lower at week 6 and week 12 for those in the TRE group, though no measures met statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026gt;0.25; \u003cstrong\u003eSuppl. Fig. 3\u003c/strong\u003e, \u003cstrong\u003eSuppl. Table\u003c/strong\u003e \u003cstrong\u003e2\u003c/strong\u003e). For example, average daily minimum was lower for those in the TRE group compared to the control group at week 6 (change from baseline= 4.4\u0026plusmn;16.0 mg/dl in the control group and -13.0\u0026plusmn;11.6 in the TRE group) and at week 12 (change from baseline= 0.7\u0026plusmn;17.7 mg/dl in the control group and -6.3\u0026plusmn;18.1 mg/dl in the TRE group, mixed model group\u0026times;time estimate \u0026plusmn; SE = 0.29\u0026plusmn;0.25, \u003cem\u003ep\u003c/em\u003e=0.258).\u003c/p\u003e\n\u003cp\u003eWe collected actigraphy data to quantify the strength of participants\u0026rsquo; rest-activity rhythm, or a person\u0026rsquo;s regular daily 24-hour pattern of being active and resting. Stronger rest-activity rhythms are reflected by high activity during the day and low activity at night (i.e., high fitted cosine amplitude) and regular movement and rest patterns each day (i.e., interdaily stability; \u003cstrong\u003eTable 3\u003c/strong\u003e). Actigraphy data were available from 33 participants and 24 contributed data for at least two time points (\u003cstrong\u003eSuppl. Fig. 4\u003c/strong\u003e). Three participants removed their actigraphs at night, precluding our ability to calculate parametric rest-activity measures. The estimate for group\u0026times;time interaction in mixed models for all rest-activity parameters suggested that TRE led to higher regulation of rest-activity rhythms, though this term did not reach statistical significance for any model (\u003cem\u003ep\u003c/em\u003e\u0026gt;0.19 for all parameters that reflect the degree of rhythm entrainment, \u003cstrong\u003eTable 3\u003c/strong\u003e, \u003cstrong\u003eSuppl. Fig. 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eIn regard to safety, there were two grade 4 adverse events and none of these adverse events were attributed to the intervention or study procedures. Two hospitalizations occurred in the control group\u0026mdash;one for shortness of breath and one for pneumonia. There was one grade 3 adverse event: approximately 2 weeks of nausea and diarrhea that led to significant weight loss in the TRE group.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is one of the first randomized controlled trials to test the effects of TRE on cancer-related fatigue. Throughout the 12-week trial, fatigue tended to be stable in the control group and tended to gradually decrease in the TRE group to a clinically meaningful degree (\u0026gt;\u0026thinsp;3 points), yielding a moderate effect size of 0.70 at week 12 as measured using the FACIT-F fatigue subscale (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Collection of continuous glucose monitor data and actigraphy was feasible for more than half of our participants, though some could not apply the glucose monitor on their own, chose not to wear the device(s), or did not return the device(s) to our lab. While participants did not necessarily have impairments in glucose regulation, TRE led to slight decreases in average and fasting interstitial glucose concentrations, which tends to reflect healthier levels. Similarly, actigraphy data suggest that TRE may help increase the robustness of rest-activity rhythms, but this study was not powered adequately to resolve group-level differences. Throughout the course of the study, we increased our engagement strategies and only two of our last 14 consents withdrew before randomization. Thus, after troubleshooting our recruitment and retention strategies, recruitment to the TRE study was feasible and participants were retained. These data support continued investigation into TRE to better understand how to leverage dietary patterns to regulate circadian rhythms and energy metabolism to address fatigue.\u003c/p\u003e \u003cp\u003eThese results build on promising single-arm interventional trials that support the use of TRE to regulate circadian rhythms and address cancer-related fatigue [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. For example, in a single-arm TRE study, a cohort of survivors of mixed cancer types (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;36) reported less fatigue after two weeks (mean pre-post improvement of 5.3 points on the FACIT-F fatigue subscale, effect size\u0026thinsp;=\u0026thinsp;0.55) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, breast cancer survivors (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;40) saw a pre-post improvement in fatigue after 12 weeks of TRE (median change of 1.0 points on the FACIT-F fatigue subscale) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In populations other than cancer populations, studies tend to report increased energy levels that are sustained for up to one year or no increases in fatigue (e.g., [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]).\u003c/p\u003e \u003cp\u003eTRE has shown benefits to glucose metabolism in other populations, including those with metabolic syndrome and diabetes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], but not yet in the cancer population because it has not yet been tested [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. We saw small improvements (reductions) in several glucose parameters, but our study was not powered to see statistically significant group-level effects. While cancer and chemotherapy can sometimes cause dysregulation of glucose parameters [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and diabetes specifically is associated with cancer-related fatigue [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], not all cancer survivors have dysregulated glucose metabolism. Based on studies among people with diabetes [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], TRE may be particularly beneficial for glucose parameters for those with dysregulated glucose metabolism at baseline.\u003c/p\u003e \u003cp\u003eActigraphy is a useful measure for circadian rest-activity rhythms in the cancer population, and parametric and non-parametric measures are complementary in describing the strength of the diurnal rhythm. For example, Liu \u003cem\u003eet al.\u003c/em\u003e used wrist-worn actigraphs to show that people with breast cancer had disrupted rest-activity rhythms even before chemotherapy began, and that rhythms were less robust after chemotherapy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Rhythms with less robusticity were associated with more fatigue [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Consistently, in this small study with considerable inter-individual variability, we saw that TRE led to trends towards higher cosinar and relative amplitudes and higher interdaily stability, though a larger study is necessary to achieve adequate power.\u003c/p\u003e \u003cp\u003eThis study sets the stage for follow-on projects to further optimize TRE to address fatigue. The importance of the start time of the eating window is unknown, i.e., in relation to either daylight or an individual\u0026rsquo;s sleep patterns. Cancer-related fatigue is a multifaceted condition, and future research is warranted to explore who in particular will benefit from TRE in regard to cancer type, treatment type, clinical characteristics, or behavioral habits. Future research should also explore whether TRE can be combined with other interventions that entrain circadian rhythms, for example bright light therapy, for additive or synergistic effects.\u003c/p\u003e \u003cp\u003eThis study has several strengths. Our population was diverse in regard to sex/gender, age, and race, increasing the generalizability to other cancer survivors. Also, we completed all study activities completely remotely, facilitating the ability to implement and disseminate a TRE program in clinical practices in the future. Our study was randomized with known potential confounding factors distributed fairly equally, and therefore any differences between groups can be attributed to TRE. Further, we had an active control condition to help control for time, attention, expectation of benefit, and potential improvements in the \u003cem\u003equality\u003c/em\u003e of diet, which may help discern the specific effects of the TRE eating pattern.\u003c/p\u003e \u003cp\u003eHowever, this study was not without limitations. Our drop-out rate was high at the beginning of our study, especially before randomization; but we were able to reduce dropout by increasing engagement later in the study. In addition, we recruited a heterogeneous population in regard to cancer type and treatment history; while that may increase generalizability, it may reduce our ability to see benefits if TRE is only effective for a subset of the eligible participants.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThere has been a recent explosion of exploration into \u0026ldquo;chrononutrition,\u0026rdquo; \u0026ldquo;chronochemotherapy,\u0026rdquo; and other \u0026ldquo;chronomedicine\u0026rdquo; approaches to understand how we can manipulate and harness circadian processes to prevent and treat chronic illnesses [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Herein, we provide promising results from a randomized controlled trial that TRE may be able to alleviate persistent cancer-related fatigue. Given the appeal of TRE in regard to accessibility, low cost, low risk, and potential benefits, the results herein support follow-on studies to continue to evaluate TRE to address fatigue and other supportive care outcomes, as well as understand the underlying mediators so that we can tailor behavioral interventions and facilitate survivors\u0026rsquo; recovery to life \u0026ldquo;before cancer.\u0026rdquo;\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: AK; Methodology: AK, IRK, SZ; Study coordination, recruitment, intervention delivery, and data collection: CLC, SMY, AK; Clinical Oversight: AZB, AE; Data analysis: AK, IRK, SZ, LQ, RDE; Writing - original draft preparation: AK; Writing - review and editing: AK, CLC, SMY, IRK, LQ, RDE, SZ, ENCM, SP, AZB, AE; Funding acquisition: AK; Resources: AK, ENCM, SP; Supervision: AK.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eWe thank Maygan McMahon, Roland Park High School, for help with analyzing the adherence data and Sumedha Shastry, Centennial High School, for help analyzing the continuous glucose data. This project was supported by the Accelerated Translational Incubator Pilot (ATIP) Grant Program through the Institute for Clinical and Translational Research (ICTR; UL1TR003098 to Daniel Ford) as well as funds through the Maryland Department of Health\u0026apos;s Cigarette Restitution Fund Program (no. CH-649-CRF). LQ was supported by the University of Maryland Medical System Foundation Nathan Schnaper Fund and the National Cancer Institute (R25CA186872 to Bret A. Hassel).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl Maqbali M, Al Sinani M, Al Naamani Z, Al Badi K, Tanash MI (2020) Prevalence of Fatigue in Patients with Cancer: A Systematic Review and Meta-Analysis J Pain Symptom Manage\u003c/li\u003e\n\u003cli\u003eArmstrong T, Bull F (2006) Development of the World Health Organization Global Physical Activity Questionnaire (GPAQ) Journal of Public Health 14: 66-70\u003c/li\u003e\n\u003cli\u003eBerger AM, Mooney K, Alvarez-Perez A, Breitbart WS, Carpenter KM, Cella D, Cleeland C, Dotan E, Eisenberger MA, Escalante CP, Jacobsen PB, Jankowski C, LeBlanc T, Ligibel JA, Loggers ET, Mandrell B, Murphy BA, Palesh O, Pirl W, Plaxe SC, Riba MB, Rugo HS, Salvador C, Wagner LI, Wagner-Johnston ND, Zachariah FJ, Bergman MA, Smith C (2015) Cancer-Related Fatigue, Version 2.2015, Clinical Practice Guidelines in Oncology Nat Comp Cancer Netw 13: 1012-1039\u003c/li\u003e\n\u003cli\u003eBower JE (2014) Cancer-related fatigue\u0026mdash;mechanisms, risk factors, and treatments Nature Reviews Clinical Oncology 11: 597-609\u003c/li\u003e\n\u003cli\u003eBower JE, Lacchetti C, Alici Y, Barton DL, Bruner D, Canin BE, Escalante CP, Ganz PA, Garland SN, Gupta S, Jim H, Ligibel JA, Loh KP, Peppone L, Tripathy D, Yennu S, Zick S, Mustian K (2024) Management of Fatigue in Adult Survivors of Cancer: ASCO-Society for Integrative Oncology Guideline Update J Clin Oncol: JCO2400541\u003c/li\u003e\n\u003cli\u003eCella D (1997) The Functional Assessment of Cancer Therapy-Anemia (FACT-An) Scale: a new tool for the assessment of outcomes in cancer anemia and fatigue. Semin Hematol 34: 13-19\u003c/li\u003e\n\u003cli\u003eChaix A, Lin T, Le HD, Chang MW, Panda S (2019) Time-Restricted Feeding Prevents Obesity and Metabolic Syndrome in Mice Lacking a Circadian Clock Cell Metab 29: 303-319 e304\u003c/li\u003e\n\u003cli\u003eChristensen RAG, Kirkham AA (2021) Time-Restricted Eating: A Novel and Simple Dietary Intervention for Primary and Secondary Prevention of Breast Cancer and Cardiovascular Disease Nutrients 13\u003c/li\u003e\n\u003cli\u003eDamato AR, Herzog ED (2022) Circadian clock synchrony and chronotherapy opportunities in cancer treatment Semin Cell Dev Biol 126: 27-36\u003c/li\u003e\n\u003cli\u003eDieli-Conwright CM, Wong L, Waliany S, Bernstein L, Salehian B, Mortimer JE (2016) An observational study to examine changes in metabolic syndrome components in patients with breast cancer receiving neoadjuvant or adjuvant chemotherapy Cancer 122: 2646-2653\u003c/li\u003e\n\u003cli\u003eGill S, Panda S (2015) A Smartphone App Reveals Erratic Diurnal 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e437-e445\u003c/li\u003e\n\u003cli\u003eInglis JE, Lin PJ, Kerns SL, Kleckner IR, Kleckner AS, Castillo DA, Mustian KM, Peppone LJ (2019) Nutritional Interventions for Treating Cancer-Related Fatigue: A Qualitative Review Nutr Cancer 71: 21-40\u003c/li\u003e\n\u003cli\u003eKalam F, James D, Li YR, Coleman MF, Kiesel VA, Cespedes Feliciano EM, Hursting SD, Sears DD, Kleckner AS (2023) Intermittent fasting interventions to leverage chrononutrition and metabolic mechanisms for cancer treatment and supportive care outcomes JNCI Monographs 61: 84-103\u003c/li\u003e\n\u003cli\u003eKirkham AA, Ford KL, Ramos Da Silva B, Topolnyski J, Prado CM, Joy AA, Paterson DI, Boule N, Pituskin E, Haykowsky MJ, Thompson RB (2023) Implementation of weekday time-restricted eating to improve metabolic health in breast cancer survivors with overweight/obesity Obesity (Silver Spring) 31 Suppl 1: 150-160\u003c/li\u003e\n\u003cli\u003eKirkham AA, Parr EB, Kleckner AS (2022) Cardiometabolic health impacts of time-restricted eating: Implications for type 2 diabetes, cancer, and cardiovascular diseases Current Opinion in Clinical Nutrition and Metabolic Care 25: 378-387\u003c/li\u003e\n\u003cli\u003eKirkham AA, Pituskin E, Mackey JR, Grenier JG, Ian Paterson D, Haykowsky MJ, Thompson RB (2022) Longitudinal Changes in Skeletal Muscle Metabolism, Oxygen Uptake, and Myosteatosis During Cardiotoxic Treatment for Early-Stage Breast Cancer Oncologist 27: e748-e754\u003c/li\u003e\n\u003cli\u003eKleckner AS, Altman BJ, Reschke JE, Kleckner IR, Culakova E, Dunne RF, Mustian KM, Peppone LJ (2022) Time-restricted eating to address cancer-related fatigue among cancer survivors: A single-arm pilot study Journal of Integrative Oncology 11\u003c/li\u003e\n\u003cli\u003eKleckner AS, Kleckner IR, Culakova E, Shayne M, Belcher EK, Gudina AT, Williams AM, Onitilo AA, Hopkins JO, Gross H, Mustian KM, Peppone LJ, Janelsins MC (2022) The association between cancer-related fatigue and diabetes from pre-chemotherapy to 6 months post-chemotherapy Support Care Cancer\u003c/li\u003e\n\u003cli\u003eLawrence CE, Dunkel L, McEver M, Israel T, Taylor R, Chiriboga G, Goins KV, Rahn EJ, Mudano AS, Roberson ED, Chambless C, Wadley VG, Danila MI, Fischer MA, Joosten Y, Saag KG, Allison JJ, Lemon SC, Harris PA (2020) A REDCap-based model for electronic consent (eConsent): Moving toward a more personalized consent J Clin Transl Sci 4: 345-353\u003c/li\u003e\n\u003cli\u003eLee DK (2016) Alternatives to P value: confidence interval and effect size Korean J Anesthesiol 69: 555-562\u003c/li\u003e\n\u003cli\u003eLee SA, Sypniewski C, Bensadon BA, McLaren C, Donahoo WT, Sibille KT, Anton S (2020) Determinants of Adherence in Time-Restricted Feeding in Older Adults: Lessons from a Pilot Study Nutrients 12\u003c/li\u003e\n\u003cli\u003eLiu L, Rissling M, Neikrug A, Fiorentino L, Natarajan L, Faierman M, Sadler GR, Dimsdale JE, Mills PJ, Parker BA, Ancoli-Israel S (2013) Fatigue and circadian activity rhythms in breast cancer patients before and after chemotherapy: A controlled study Fatigue 1: 12-26\u003c/li\u003e\n\u003cli\u003eManoogian ENC, Wei-Shatzel J, Panda S (2022) Assessing temporal eating pattern in free living humans through the myCircadianClock app Int J Obes (Lond)\u003c/li\u003e\n\u003cli\u003eMartinez M, Santamarina J, Pavesi A, Musso C, Umpierrez GE (2021) Glycemic variability and cardiovascular disease in patients with type 2 diabetes BMJ Open Diabetes Res Care 9\u003c/li\u003e\n\u003cli\u003eMendoza TR, Wang XS, Cleeland CS, Morrissey M, Johnson BA, Wendt JK, Huber SL (1999) The Rapid Assessment of Fatigue Severity in Cancer Patients: Use of the Brief Fatigue Inventory Cancer 85: 1186-1196\u003c/li\u003e\n\u003cli\u003eNordin A, Taft C, Lundgren-Nilsson A, Dencker A (2016) Minimal important differences for fatigue patient reported outcome measures-a systematic review BMC Med Res Methodol 16: 62\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Donnell E, Shapiro Y, Comander A, Isakoff S, Moy B, Spring L, Wander S, Kuter I, Shin J, Specht M, Kournioti C, Hu B, Sullivan C, Winters L, Horick N, Peppercorn J (2022) Pilot study to assess prolonged overnight fasting in breast cancer survivors (longfast) Breast Cancer Res Treat 193: 579-587\u003c/li\u003e\n\u003cli\u003eParr EB, Devlin BL, Radford BE, Hawley JA (2020) A Delayed Morning and Earlier Evening Time-Restricted Feeding Protocol for Improving Glycemic Control and Dietary Adherence in Men with Overweight/Obesity: A Randomized Controlled Trial Nutrients 12\u003c/li\u003e\n\u003cli\u003eParr EB, Radford BE, Hall RC, Steventon-Lorenzen N, Flint SA, Siviour Z, Plessas C, Halson SL, Brennan L, Kouw IWK, Johnston RD, Devlin BL, Hawley JA (2024) Comparing the effects of time-restricted eating on glycaemic control in people with type 2 diabetes with standard dietetic practice: A randomised controlled trial Diabetes Res Clin Pract 217: 111893\u003c/li\u003e\n\u003cli\u003eRavussin E, Beyl RA, Poggiogalle E, Hsia DS, Peterson CM (2019) Early Time-Restricted Feeding Reduces Appetite and Increases Fat Oxidation But Does Not Affect Energy Expenditure in Humans Obesity (Silver Spring) 27: 1244-1254\u003c/li\u003e\n\u003cli\u003eRogers VE, Zhu S, Mandrell BN, Ancoli-Israel S, Liu L, Hinds PS (2020) Relationship between circadian activity rhythms and fatigue in hospitalized children with CNS cancers receiving high-dose chemotherapy Support Care Cancer 28: 1459-1467\u003c/li\u003e\n\u003cli\u003eRoscoe JA, Morrow GR, Hickok JT, Bushunow P, Matteson S, Rakita D, Andrews PL (2002) Temporal interrelationships among fatigue, circadian rhythm and depression in breast cancer patients undergoing chemotherapy treatment Support Care Cancer 10: 329-336\u003c/li\u003e\n\u003cli\u003eRubinstein LV, Korn EL, Freidlin B, Hunsberger S, Ivy SP, Smith MA (2005) Design issues of randomized phase II trials and a proposal for phase II screening trials J Clin Oncol 23: 7199-7206\u003c/li\u003e\n\u003cli\u003eSchmidt ME, Semik J, Habermann N, Wiskemann J, Ulrich CM, Steindorf K (2016) Cancer-related fatigue shows a stable association with diurnal cortisol dysregulation in breast cancer patients Brain Behav Immun 52: 98-105\u003c/li\u003e\n\u003cli\u003eSleight AG, Crowder SL, Skarbinski J, Coen P, Parker NH, Hoogland AI, Gonzalez BD, Playdon MC, Cole S, Ose J, Murayama Y, Siegel EM, Figueiredo JC, Jim HSL (2022) A New Approach to Understanding Cancer-Related Fatigue: Leveraging the 3P Model to Facilitate Risk Prediction and Clinical Care Cancers (Basel) 14\u003c/li\u003e\n\u003cli\u003eStarreveld DEJ, Habers GEA, Valdimarsdottir HB, Kessels R, Daniels LA, van Leeuwen FE, Bleiker EMA (2021) Cancer-related Fatigue in Relation to Chronotype and Sleep Quality in (Non-)Hodgkin Lymphoma Survivors J Biol Rhythms 36: 71-83\u003c/li\u003e\n\u003cli\u003eSuzuki K, Kobayashi N, Ogasawara Y, Shimada T, Yahagi Y, Sugiyama K, Takahara S, Saito T, Minami J, Yokoyama H, Kamiyama Y, Katsube A, Kondo K, Yanagisawa H, Aiba K, Yano S (2018) Clinical significance of cancer-related fatigue in multiple myeloma patients Int J Hematol 108: 580-587\u003c/li\u003e\n\u003cli\u003eWang XS (2002) Clinical Factors Associated With Cancer-Related Fatigue in Patients Being Treated for Leukemia and Non-Hodgkin\u0026apos;s Lymphoma Journal of Clinical Oncology 20: 1319-1328\u003c/li\u003e\n\u003cli\u003eWilkinson MJ, Manoogian ENC, Zadourian A, Lo H, Fakhouri S, Shoghi A, Wang X, Fleischer JG, Navlakha S, Panda S, Taub PR (2020) Ten-Hour Time-Restricted Eating Reduces Weight, Blood Pressure, and Atherogenic Lipids in Patients with Metabolic Syndrome Cell Metab 31: 1-13\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographics, clinical characteristics, and lifestyle habits\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsented (n=50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRandomized (n=30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl (n=15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime-restricted eating (n=15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e58.2\u0026plusmn;13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e54.1\u0026plusmn;14.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e53.7\u0026plusmn;16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e54.6\u0026plusmn;12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e36 (72.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e23 (76.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13 (86.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e14 (28.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e7 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Black/African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e24 (48.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e16 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e24 (48.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13 (43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Mixed race\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Non-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e48 (96.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e28 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e15 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13 (86.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiving situation\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Married or in long-term committed relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e23 (46.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e16 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Single, divorced, or widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e13 (26.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e10 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e7 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Employed full-time (\u0026ge;35 hours/week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e16 (32.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e12 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Employed part-time (\u0026lt;35 hours/week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e5 (10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Employed, unknown hours/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Home Maker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Retired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Unemployed/on leave\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e7 (14.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (10.0%)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Some college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e7 (14.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; 4-Year college degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Graduate school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e13 (26.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13 (43.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e30.4\u0026plusmn;5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e29.8\u0026plusmn;5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e28.7\u0026plusmn;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e30.9\u0026plusmn;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExercise habits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Meets WHO\u003csup\u003ec\u003c/sup\u003e recommendations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e24/36 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e22 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e11 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e11 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Does not meet WHO recommendations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e12/36 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e8 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Leukemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e6 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Lymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e9 (18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Multiple myeloma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e27 (54.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e16 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Solid tumor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e6 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment for cancer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e6 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e47 (94.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e28 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e14 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e14 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Radiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e7 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; Stem cell transplant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e20 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e11 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp; CAR-T cell therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e11 (22.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Comorbidity Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.6\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.5\u0026plusmn;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003ea\u003c/sup\u003eSome missing data exist.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eDifferences were observed between those randomized and not randomized (\u003cem\u003et\u003c/em\u003e-test or \u0026chi;\u003csup\u003e2\u003c/sup\u003e likelihood ratio test, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). There were no statistically significant differences between time-restricted eating and control groups.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eWorld Health Organization, a combination of moderate- and vigorous-intensity physical activity achieving at least 600 metabolic equivalent-minutes per week, as measuring using a self-administered Global Physical Activity Questionnaire [2].\u003c/p\u003e\n\u003cp\u003eTable 2. Fatigue over time by group\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"720\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFatigue measure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDirectionality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek 6 (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect size of TRE vs. Control* at Week 6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeek 12 (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect size of TRE vs. Control at Week 12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eControl \u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eTRE \u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFACIT-F Physical well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e22.0 \u0026plusmn; 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e23.1 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e22.9 \u0026plusmn; 3.7\u003csup\u003ea,b**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e18.5 \u0026plusmn; 6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e20.9 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e21.7 \u0026plusmn; 5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFACIT-F Social well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e22.9 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e23.0 \u0026plusmn; 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e22.8 \u0026plusmn; 5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e22.5 \u0026plusmn; 4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e21.1 \u0026plusmn; 5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e21.9 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFACIT-F Emotional well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e19.0 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e20.5 \u0026plusmn; 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e20.5 \u0026plusmn; 2.8\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e18.9 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e18.9 \u0026plusmn; 3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e20.8 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFACIT-F Functional well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e18.8 \u0026plusmn; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e19.6 \u0026plusmn; 4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e20.2 \u0026plusmn; 6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e18.5 \u0026plusmn; 5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e18.8 \u0026plusmn; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e18.7 \u0026plusmn; 5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFACIT-F Fatigue-specific well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e36.7 \u0026plusmn; 9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e37.8 \u0026plusmn; 8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e37.2 \u0026plusmn; 9.1\u003csup\u003ea,c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e33.8 \u0026plusmn; 11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e35.2 \u0026plusmn; 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e38.7 \u0026plusmn; 9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFACIT-F Total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e120.1 \u0026plusmn; 21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e123.9 \u0026plusmn; 14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e123.7 \u0026plusmn; 22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e112.1 \u0026plusmn; 26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e114.9 \u0026plusmn; 20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e121.8 \u0026plusmn; 21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eBrief Fatigue Inventory: Global score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eLower is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.4 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e3.5 \u0026plusmn; 2.8\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.9 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.3 \u0026plusmn; 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.8 \u0026plusmn; 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eBrief Fatigue Inventory: Usual fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eLower is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.3 \u0026plusmn; 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.4 \u0026plusmn; 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e4.1 \u0026plusmn; 2.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e4.4 \u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.8 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.8 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eBrief Fatigue Inventory: Fatigue at its worst\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eLower is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.1 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.2 \u0026plusmn; 2.0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.8 \u0026plusmn; 2.4\u003csup\u003ea**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.1 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.8 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.6 \u0026plusmn; 3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eBrief Fatigue Inventory: Interference of fatigue with enjoyment of life\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eLower is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.1 \u0026plusmn; 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.3 \u0026plusmn; 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.9 \u0026plusmn; 2.4\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003eTRE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.6 \u0026plusmn; 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.4 \u0026plusmn; 3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003e2.5 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Effect size is calculated from the change scores from baseline to week 6 or baseline to week 12.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.15 over time in a mixed model\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.15 by group in a mixed model\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.15 for group\u0026times;time in a mixed model\u003c/p\u003e\n\u003cp\u003e**\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Results of mixed model analyses evaluating the effects of TRE vs. control on rest-activity parameters (\u003cem\u003en\u003c/em\u003e=67 observations for non-parametric measures and \u003cem\u003en\u003c/em\u003e=65 for parametric measures).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"937\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDefinition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of group (TRE vs. Control, Estimate \u0026plusmn; SE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of time (Estimate \u0026plusmn; SE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of group (TRE vs. control)*Time (Estimate \u0026plusmn; SE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eInterdaily stability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThe degree of regularity in the rest-activity pattern (range 0-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-0.016\u0026plusmn;0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.002\u0026plusmn;0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.5386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.003\u0026plusmn;0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eIntradaily variability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThe degree of fragmentation of rest-activity periods (range 0-2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eLower is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-0.028\u0026plusmn;0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.005\u0026plusmn;0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.3801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.001\u0026plusmn;0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eLeast 5 average\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThe average activity level for the sequence of the least five active hours (from averaged 24-hour periods of an overlay of all days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eLower is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-114.5\u0026plusmn;132.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e-7.45\u0026plusmn;14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.6168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-14.5\u0026plusmn;14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eLeast 5- Start hour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThe onset of the \u0026quot;Least 5\u0026quot; sequence [range (midnight) to 24 (midnight the following day)]*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDescriptive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-0.439\u0026plusmn;0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e-0.004\u0026plusmn;0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.8768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.035\u0026plusmn;0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eMost 10 average\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThe average activity level for the sequence of the most 10 active hours (from averaged 24-hour periods of an overlay of all days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e158.6\u0026plusmn;716.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e20.4\u0026plusmn;105.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.8478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e68.4\u0026plusmn;105.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eMost 10- Start hour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eThe temporal onset of the \u0026quot;Most 10\u0026quot; sequence [range 0 (midnight) to 24 (midnight the following day)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDescriptive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-0.398\u0026plusmn;0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e-0.030\u0026plusmn;0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.4279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.004\u0026plusmn;0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eRelative amplitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003e[(Most 10)-(Least 5)]/[(Most 10)+(Least 5)] The range is 0-1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.023\u0026plusmn;0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.000\u0026plusmn;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.9716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.003\u0026plusmn;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eFitted cosine Peak\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eWhere in the 24-hour period the peak is [range 0 (midnight) \u0026ndash; 1 (midnight the next day)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eDescriptive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-0.013\u0026plusmn;0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.001\u0026plusmn;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.001\u0026plusmn;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eFitted cosine Amplitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eAmplitude of fitted cosine curve (positive number, no defined range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eHigher is better\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.187\u0026plusmn;1.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.173\u0026plusmn;0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.5164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.325\u0026plusmn;0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 126px;\"\u003e\n \u003cp\u003eFitted cosine MESOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 245px;\"\u003e\n \u003cp\u003eMidline estimating statistic of rhythm from the cosine curve (positive number, no defined range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 104px;\"\u003e\n \u003cp\u003eNeither\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 101px;\"\u003e\n \u003cp\u003e-0.004\u0026plusmn;1.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.230\u0026plusmn;0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.3366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.174\u0026plusmn;0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*For individuals in which the L5 started before midnight, the time was converted to the hour(s) before midnight, for example \u0026ldquo;-1\u0026rdquo; for 11pm.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5530166/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5530166/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose:\u003c/strong\u003e Time-restricted eating (TRE) helps regulate rest-activity rhythms, blood glucose, and other diurnally regulated energetics processes, which may have implications for persistent fatigue. In a randomized controlled trial, we tested the effects of TRE vs. control on fatigue in cancer survivorship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Adult cancer survivors were recruited who were 2 months to 2 years post-treatment and reported moderate to severe fatigue. Participants were randomized 1:1, TRE:control and all received individualized nutrition counseling. The TRE group self-selected a 10-hour eating window for 12 weeks. At baseline, week 6, and week 12, participants were asked to log eating instances, complete the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire (FACIT-F, higher score=less fatigue), and wear an actigraph and continuous glucose monitor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Thirty participants completed baseline assessments and were randomized (77% female, 53% Black/African American, 43% White, 7% Hispanic; 54.1±14.7 years old; 87% with blood cancer); 25 completed 12-week assessments. TRE led to a meaningful reduction in fatigue at week 12 controlling for baseline levels (change in FACIT-F fatigue subscale=0.0±5.4 for control, 4.1±5.7 for TRE, \u003cem\u003ep\u003c/em\u003e=0.11, effect size [ES]=0.70; clinically meaningful threshold=3.0 points). Glucose parameters (e.g., average interstitial glucose, average fasting glucose) tended to be lower and rest-activity rhythms tended to indicate more regularity for those in the TRE vs. control group at weeks 6 and 12, though differences were not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026gt;0.19).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eA 12-week, nutritionist-led TRE program led to less fatigue than control. Continued study of TRE patterns are warranted to optimize this eating pattern and address persistent cancer-related fatigue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinicaltrials.gov identifier:\u003c/strong\u003e NCT05256888, registered 02/2022\u003c/p\u003e","manuscriptTitle":"Time-restricted eating to address persistent cancer-related fatigue among cancer survivors: A randomized controlled trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-25 01:24:38","doi":"10.21203/rs.3.rs-5530166/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-18T14:53:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-15T14:05:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235890638683587853736735679454065603083","date":"2025-01-17T22:44:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-15T08:36:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-15T02:21:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-12-03T01:16:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2024-11-26T18:38:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3e0fdd48-19b2-4f61-9914-fbf728037ef6","owner":[],"postedDate":"December 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-07T16:00:22+00:00","versionOfRecord":{"articleIdentity":"rs-5530166","link":"https://doi.org/10.1007/s00520-025-09394-w","journal":{"identity":"supportive-care-in-cancer","isVorOnly":false,"title":"Supportive Care in Cancer"},"publishedOn":"2025-04-05 15:57:22","publishedOnDateReadable":"April 5th, 2025"},"versionCreatedAt":"2024-12-25 01:24:38","video":"","vorDoi":"10.1007/s00520-025-09394-w","vorDoiUrl":"https://doi.org/10.1007/s00520-025-09394-w","workflowStages":[]},"version":"v1","identity":"rs-5530166","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5530166","identity":"rs-5530166","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}