Longitudinal assessment of the impact of higher body mass index on cancer-related fatigue in patients with breast cancer receiving chemotherapy

The interplay between sleep and cancer-related fatigue in breast cancer: A casual and computer-simulated network analysis

Objective

Sleep problems and cancer-related fatigue are common symptoms in women for breast cancer, during and after treatment. Identifying key intervention targets for this symptom cluster may improve patient reported outcomes. This study aimed to explore the relationship between sleep and cancer-related fatigue to identify optimal intervention targets.

Methods

In the "Be Resilient to Breast Cancer" program, self report data were collected on sleep and cancer-related fatigue the Multidimensional Fatigue Symptom Inventory-Short Form and the Pittsburgh Sleep Quality Index. Gaussian network analysis was employed to identify central symptoms and nodes, while a Bayesian network explored their causal relationships. Computer-simulated interventions were used to identify core symptoms as targets for intervention.

Results

General fatigue (Str ​= ​0.95, Bet ​= ​7, Clo ​= ​0.007) was considered the node with the strongest centrality. The daytime dysfunction item on the Pittsburgh sleep quality index had the strongest bridge strength. Core symptoms were identified as targets for intervention by the computer-simulated analysis.

Conclusions

Sleep quality is the strongest predictor of cancer-related fatigue from a casual networking perspective. Sleep latency and daytime dysfunction should be targeted to break the chained symptom interaction between sleep and cancer-related fatigue.

Could nutrition status predict fatigue one week before in patients with nasopharynx cancer undergoing radiotherapy?

BACKGROUND

Patients with nasopharyngeal carcinoma (NPC) undergoing radiotherapy experience significant fatigue, which is frequently underestimated due to the lack of objective indicators for its evaluation. This study aimed to explore the longitudinal association between fatigue and nutrition status 1 week in advance.

METHODS

From January 2021 to June 2022, a total of 105 NPC patients who received intensity-modulated radiation therapy were enrolled in the observational longitudinal study. The significant outcomes, including the Piper Fatigue Scale-12 (PFS-12), the Scored Patient-Generated Subjective Global Assessment (PG-SGA), four body composition indices, and the Hospital Anxiety and Depression Scale (HADS), were assessed weekly from pre-treatment until the completion of radiotherapy (T0-T7) to explore their relationship.

RESULTS

The trajectories of PFS-12 and all dimensions for 105 participants reached a peak during the fifth week. Sensory fatigue consistently received the highest scores (T0 = 1.60 ± 2.20, T5 = 6.15 ± 1.57), whereas behavior fatigue exhibited the fastest increase over time (T0 = 1.11 ± 1.86, T5 = 5.47 ± 1.70). Higher PG-SGA scores were found to be weakly explainable for aggravating fatigue (β = 0.02 ~ 0.04). Unlike generalized additive mixed models, marginal structural models (MSM) produced larger effect values (β = 0.12 ~ 0.21). Additionally, body composition indices showed weakly negative relationships with fatigue in MSMs one week in advance.

CONCLUSIONS

The PG-SGA may be a more accurate predictor of future-week fatigue than individual body composition indicators, particularly when HADS is controlled for as a time-dependent confounder.

New Horizons: Epidemiology of Obesity, Diabetes Mellitus, and Cancer Prognosis

The global prevalence of obesity and diabetes mellitus has increased in parallel with increasing cancer incidence, due to environmental and lifestyle factors and population aging. Metabolic diseases are associated with increased cancer risk, so a growing number of patients with cancer have coexistent obesity and/or diabetes mellitus. In this narrative review, we highlight recent evidence on the clinical impact of obesity and diabetes mellitus on the prognosis of prostate, breast, and colorectal cancer, and provide an overview of the underlying mechanisms. There is evidence that obesity is associated with increased risk of recurrence, and all-cause and cancer-specific mortality among adults with prostate, breast, and colorectal cancer. Diabetes mellitus is associated with increased all-cause and cancer-specific mortality for these 3 cancers, beyond any impact of obesity. Evidence also suggests increased risk of colorectal cancer recurrence in patients with diabetes mellitus. The underlying mechanisms are multifactorial and likely include hormonal imbalances and chronic inflammation that promote cancer cell growth. Obesity and diabetes mellitus are associated with increased risk of complications and side effects of cancer treatment. Associated comorbidities such as impaired kidney function, cardiovascular disease, and neuropathies may preclude the use of guideline cancer treatment and are competing causes of death. Cancer patients with metabolic diseases require a designated clinical program and a multidisciplinary approach involving oncologists, endocrinologists, surgeons, nutritionists, and physiotherapists, to ensure coordinated and optimized patient care.

Metabolic underpinnings of cancer-related fatigue

Cancer-related fatigue (CRF) is one of the most prevalent and detrimental complications of cancer. Emerging evidence suggests that obesity and insulin resistance are associated with CRF occurrence and severity in cancer patients and survivors. In this narrative review, we analyzed recent studies including both preclinical and clinical research on the relationship between obesity and/or insulin resistance and CRF. We also describe potential mechanisms for these relationships, though with the caveat that because the mechanisms underlying CRF are incompletely understood, the mechanisms mediating the association between obesity/insulin resistance and CRF are similarly incompletely delineated. The data suggest that, in addition to their effects to worsen CRF by directly promoting tumor growth and metastasis, obesity and insulin resistance may also contribute to CRF by inducing chronic inflammation, neuroendocrinological disturbance, and metabolic alterations. Furthermore, studies suggest that patients with obesity and insulin resistance experience more cancer-induced pain and are at more risk of emotional and behavioral disruptions correlated with CRF. However, other studies implied a potentially paradoxical impact of obesity and insulin resistance to reduce CRF symptoms. Despite the need for further investigation utilizing interventions to directly elucidate the mechanisms of cancer-related fatigue, current evidence demonstrates a correlation between obesity and/or insulin resistance and CRF, and suggests potential therapeutics for CRF by targeting obesity and/or obesity-related mediators.

Obesity and Cancer Rehabilitation for Functional Recovery and Quality of Life in Breast Cancer Survivors: A Comprehensive Review

Obesity is a global health challenge with increasing prevalence, and its intricate relationship with cancer has become a critical concern in cancer care. As a result, understanding the multifactorial connections between obesity and breast cancer is imperative for risk stratification, tailored screening, and rehabilitation treatment planning to address long-term survivorship issues. The review follows the SANRA quality criteria and includes an extensive literature search conducted in PubMed/Medline, Web of Science, and Scopus. The biological basis linking obesity and cancer involves complex interactions in adipose tissue and the tumor microenvironment. Various mechanisms, such as hormonal alterations, chronic inflammation, immune system modulation, and mitochondrial dysfunction, contribute to cancer development. The review underlines the importance of comprehensive oncologic rehabilitation, including physical, psychological, and nutritional aspects. Cancer rehabilitation plays a crucial role in managing obesity-related symptoms, offering interventions for physical impairments, pain management, and lymphatic disorders, and improving both physical and psychological well-being. Personalized and technology-driven approaches hold promise for optimizing rehabilitation effectiveness and improving long-term outcomes for obese cancer patients. The comprehensive insights provided in this review contribute to the evolving landscape of cancer care, emphasizing the importance of tailored rehabilitation in optimizing the well-being of obese cancer patients.

Breast cancer survivors with pain: an examination of the relationships between body mass index, physical activity, and symptom burden

PURPOSE

Overweight and obesity are common for breast cancer survivors and associated with high symptom burden (i.e., pain, fatigue, depressive symptoms). Physical activity may protect breast cancer survivors with higher body mass indexes (BMI) from increased symptoms. However, the role of physical activity in buffering the relationship between higher BMI and greater symptoms is unclear.

METHODS

Baseline data from a randomized trial investigating Pain Coping Skills Training among breast cancer survivors (N = 327) with pain were used to examine the relationship between self-reported BMI (kg/m2) and physical activity level (Rapid Assessment of Physical Activity; suboptimal vs. optimal) with pain (Brief Pain Inventory; severity and interference), fatigue (PROMIS-Fatigue short form), and depressive symptoms (Center for Epidemiological Studies Depression Scale). Analyses were conducted in SPSS. Hayes PROCESS macro (Model 1) assessed whether physical activity moderated the relationship between BMI and symptoms.

RESULTS

Lower BMI (B = .06, p < .01) and optimal physical activity (B =  - .69, p < .01) were independently associated with lower pain interference. Lower BMI was also associated with lower pain severity (B = .04, p < .001). Neither BMI nor physical activity was associated with fatigue or depressive symptoms. Physical activity did not moderate the relationship between BMI and symptoms.

CONCLUSIONS

Among breast cancer survivors experiencing pain, higher BMI and being less physically active were related to greater pain (i.e., severity and/or interference). Physical activity did not buffer the relationships between BMI and pain, fatigue, and depressive symptoms, suggesting that physical activity alone may not be sufficient to influence the strength of the relationships between BMI and symptoms.

The association between cancer-related fatigue and diabetes from pre-chemotherapy to 6 months post-chemotherapy

PURPOSE

To quantify the relationship between diabetes and fatigue from pre-chemotherapy to 6 months post-chemotherapy for women with breast cancer compared to women without a history of cancer (controls).

METHODS

This was a secondary analysis from a nationwide prospective longitudinal study of female patients with breast cancer undergoing chemotherapy and controls. Diabetes diagnosis (yes/no) was obtained at baseline, and cancer-related fatigue was measured using the Multidimensional Fatigue Symptom Inventory (MFSI) pre-, post-, and 6 months post-chemotherapy in patients; controls were assessed at equivalent time points. Repeated measures mixed effects models estimated the association between fatigue and diabetes controlling for cancer (yes/no), body mass index, exercise and smoking habits, baseline anxiety and depressive symptoms, menopausal status, marital status, race, and education.

RESULTS

Among 439 patients and 235 controls (52.8 ± 10.5 years old), diabetes was twice as prevalent among patients as controls (11.6% vs. 6.8%). At baseline, diabetes was associated with worse fatigue (4.1 ± 1.7 points, p = 0.017). Also, diabetes was associated with clinically meaningful worse fatigue throughout the study period among all participants (5.2 ± 1.9 points, p = 0.008) and patients alone (4.5 ± 2.0, p = 0.023). For the MFSI subdomains among patients, diabetes was associated with worse general (p = 0.005) and mental fatigue (p = 0.026).

CONCLUSIONS

Diabetes was twice as prevalent in women with breast cancer compared to controls, and diabetes was associated with more severe cancer-related fatigue in patients before and after chemotherapy and at 6 months post-chemotherapy. Interventions that address diabetes management may also help address cancer-related fatigue during chemotherapy treatment.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01382082, first posted June 27, 2011.

Impact of community-based exercise on fatigue in early breast cancer survivors: identifying potential determinants of change

BACKGROUND

Exercise has been shown to reduce fatigue in early breast cancer survivors (EBCS), though it is unclear if these results translate to community-based exercise settings. Mechanisms that influence changes in fatigue seen after exercise are also poorly understood. This study sought to evaluate the impact of community-based exercise and identify associations of fatigue in EBCS.

METHODS

Twenty-nine EBCS and 13 non-cancer controls (CON) enrolled. Pre/post-intervention measurements included measures of fitness/function, balance, and adherence/compliance as well as self-reported measures of fatigue, health-related quality of life (HRQOL), well-being, self-efficacy, and physical activity. Both groups participated in a supervised 16-week aerobic + resistance exercise intervention. A mixed model ANOVA and Cohen's D effect size assessed fatigue changes, and univariable linear regressions identified fatigue associations.

RESULTS

Fatigue improved for EBCS (- 2.6, Cohen's D = 0.51) but not CON (0.0, Cohen's D = 0.02); no interaction effect was observed. Post-intervention fatigue in EBCS was associated with better QOL (R² = 0.387; p < 0.01), depression (R² = 0.251; p < 0.01), self-efficacy, (R² = 0.453; p < 0.01), outcome expectations from exercise (R² = 0.254; p < 0.01), balance (R² = 0.167; p < 0.05), and the 6-minute walk test (R² = 0.193; p < 0.05). EBCS improvements in fatigue were associated with improvements in self-reported physical health (R² = 0.425; p < 0.01), depression (R² = 0.233; p < 0.01), pain (R² = 0.157; p < 0.05), outcome expectations from exercise (R² = 0.420; p < 0.01), and the 6-minute walk test (R² = 0.172; p < 0.05). Less fatigue in the CON group was shown be associated with better sleep quality (R² = 0.309; p < 0.05) and pain (R² = 0.259; p < 0.05).

CONCLUSION

Community-based exercise appears beneficial for alleviating fatigue in EBCS. These improvements may be driven by parallel improvements in psychosocial outcomes and objectively measured functional outcomes.

A phase III randomized trial of weight loss to reduce cancer-related fatigue among overweight and obese breast cancer patients: MEDEA Study design

Background

Elevated body mass index (BMI) represents a risk factor for cancer-related fatigue (CRF). Weight loss interventions are feasible and safe in cancer survivors, leading to improved cardio-metabolic and quality of life (QOL) outcomes and modulating inflammatory biomarkers. Randomized data are lacking showing that a lifestyle intervention aimed at weight loss, combining improved diet, exercise, and motivational counseling, reduces CRF. Motivating to Exercise and Diet, and Educating to healthy behaviors After breast cancer (MEDEA) is a multi-center, randomized controlled trial evaluating the impact of weight loss on CRF in overweight or obese survivors of breast cancer. Herein, we described the MEDEA methodology.

Methods

Patients (N = 220) with stage I–III breast cancer and BMI ≥ 25 kg/m², within 12 months of primary treatment, and able to walk ≥ 400 m are eligible to enroll. Participants are randomized 1:1 to health education alone vs. a personalized telephone-based weight loss intervention plus health education. Both arms receive a health education program focusing on healthy living. Patients in the intervention arm are paired with an individual lifestyle coach, who delivers the intervention through 24 semi-structured telephone calls over 1 year. Intervention goals include weight loss ≥ 10% of baseline, caloric restriction of 500–1000 Kcal/day, and increased physical activity (PA) to 150 (initial phase) and 225–300 min/week (maintenance phase). The intervention is based on the social cognitive theory and is adapted from the Breast Cancer Weight Loss trial (BWEL, A011401). The primary endpoint is the difference in self-reported CRF (EORTC QLQ-C30) between arms. Secondary endpoints include the following: QOL (EORTC QLQ-C30, -BR45, -FA12), anxiety, and depression (HADS); weight and BMI, dietary habits and quality, PA, and sleep; health care costs (hospital-admissions, all-drug consumption, sick leaves) and cost-effectiveness (cost per quality-adjusted life-year); and patient motivation and satisfaction. The primary analysis of MEDEA will compare self-reported CRF at 12 months post-randomization between arms, with 80.0% power (two-sided α = 0.05) to detect a standardized effect size of 0.40.

Discussion

MEDEA will test the impact of a weight loss intervention on CRF among overweight or obese BC survivors, potentially providing additional management strategies and contributing to establish weight loss support as a new standard of clinical care.

Trial registration

ClinicalTrials.govNCT04304924

Serum carotenoids and cancer-related fatigue: An analysis of the 2005-2006 National Health and Nutrition Examination Survey

Cancer-related fatigue is a prevalent, debilitating condition, and preliminary evidence suggests a relationship between higher diet quality and lower fatigue. Serum-based carotenoids, Vitamin A, and Vitamin E are biomarkers of fruit and vegetable intake and therefore diet quality. To further elucidate the link between diet quality and cancer-related fatigue, associations were assessed between these serum-based nutrients and fatigue among American adults with special attention to cancer history. Data were analyzed from the United States 2005-2006 National Health and Nutrition Examination Survey (NHANES) dataset. Ten carotenoids, vitamin A, vitamin E, and γ-tocopherol were measured from fasting blood samples and fatigue was patient-reported. Associations between carotenoid concentration and fatigue were estimated using ordinal logistic regression models. Adjusted models included a diagnosis of cancer (with the exception on non-melanoma skin cancer, yes/no), age, body mass index, race/ethnicity, education, and exercise habits as covariates, and additional models included a cancer×nutrient interaction. Of 4091 participants, 272 (8.0%) reported a history of cancer. Greater fatigue was associated with lower serum trans-lycopene, retinyl palmitate, and retinyl stearate (all p<0.05) in separate models adjusting for potential confounders. For these nutrients, a one-standard deviation increase in nutrient was associated with a 6.8-9.9% lower risk of greater fatigue. Among cancer survivors only (n=272), statistically significant associations were not observed between any of the nutrients and fatigue. In conclusion, greater serum concentrations of carotenoid biomarkers were associated with less fatigue. These results support further exploration into relationships between carotenoid intake, diet quality, and persistent fatigue.

The Relationship Between Muscle Strength and Body Composition Measures and Cancer-Related Fatigue: A Systematic Review and Meta-Analysis

PROBLEM IDENTIFICATION

Cancer-related fatigue (CRF) substantially affects daily living and quality of life, but objective CRF measures remain limited. This review aimed to identify the correlation between muscle strength and body composition measures and CRF, as well as potential objective indicators for assessing CRF.

LITERATURE SEARCH

PubMed®, MEDLINE®, CINAHL®/PsycINFO®, and Embase® were searched for studies published from January 2000 to January 2021.

DATA EVALUATION

Study selection and quality assessment were conducted using the Critical Appraisals Skills Programme checklist and the Strengthening the Reporting of Observational Studies in Epidemiology statement. Comprehensive Meta-Analysis software was used to perform meta-analysis.

SYNTHESIS

25 studies were selected, and 19 measures were analyzed. CRF negatively correlated with hand grip strength, knee extensor strength, and the sit-to-stand test. No significant correlation was found between body composition measures and CRF.

IMPLICATIONS FOR NURSING

The evidence suggests that muscle strength measures may be potential indicators for CRF assessment. Combining objective and subjective CRF assessments could assist clinicians in evaluating the effectiveness of CRF interventions more accurately.

Obesity and Poststroke Fatigue: A 2-Year Longitudinal Study

Introduction

Obesity is associated with fatigue in many diseases, but the correlation between obesity and poststroke fatigue (PSF) is unclear. The study aimed to investigate the relationship between body mass index (BMI) and the occurrence of and recovery from PSF.

Methods

Within 3 days of the onset of ischemic stroke, patients were consecutively recruited. We assessed PSF at admission and at 6, 12, and 24 months with the Fatigue Severity Scale (FSS). Multivariable logistic regression and restricted cubic spline function were used to explore the relationships between baseline BMI and the risk of PSF at different time points. The correlation between baseline BMI and the dynamic changes in the natural logarithm transformation of the FSS (lnFSS) score during the follow-up period was analyzed by the piecewise linear mixed-effects model.

Results

A total of 1026 stroke patients were included. Multivariable analyses indicated that obesity was associated with a decreased risk of early PSF (fatigue diagnosed at baseline) [odds ratio (OR) 0.61, 95% confidence interval (CI) 0.41–0.93] but an increased risk of late PSF (fatigue diagnosed 6 months after the index stroke) (OR 1.63, 95% CI 1.06–2.50 for 6 months; OR 1.87, 95% CI 1.18–2.96 for 12 months; OR 2.11, 95% CI 1.28–3.49 for 24 months). Longitudinal analyses indicated that in the late stage of fatigue, the higher the BMI category, the slower the rate of decrease was for the FSS score.

Conclusion

Obese patients are less likely to develop fatigue in the acute stage of ischemic stroke. However, they are more prone to late fatigue and exhibit a slower decline in the FSS score in the long term.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-021-00276-x.

Current Landscape: The Mechanism and Therapeutic Impact of Obesity for Breast Cancer

Obesity is defined as a chronic disease induced by an imbalance of energy homeostasis. Obesity is a widespread health problem with increasing prevalence worldwide. Breast cancer (BC) has already been the most common cancer and one of the leading causes of cancer death in women worldwide. Nowadays, the impact of the rising prevalence of obesity has been recognized as a nonnegligible issue for BC development, outcome, and management. Adipokines, insulin and insulin-like growth factor, sex hormone and the chronic inflammation state play critical roles in the vicious crosstalk between obesity and BC. Furthermore, obesity can affect the efficacy and side effects of multiple therapies such as surgery, radiotherapy, chemotherapy, endocrine therapy, immunotherapy and weight management of BC. In this review, we focus on the current landscape of the mechanisms of obesity in fueling BC and the impact of obesity on diverse therapeutic interventions. An in-depth exploration of the underlying mechanisms linking obesity and BC will improve the efficiency of the existing treatments and even provide novel treatment strategies for BC treatment.

Impact of fatigue on quality of life among breast cancer patients receiving chemotherapy

Objectives

Fatigue is the most frequently reported symptom experienced by cancer patients and has a profound effect on their quality of life (QOL). The study aimed to determine the impact of fatigue on QOL among breast cancer patients receiving chemotherapy and to identify the risk factors associated with severe fatigue incidence.

Methods

This was an observational prospective study carried out at multiple centers. In total, 172 breast cancer patients were included. The Functional Assessment of Chronic Illness Therapy-Fatigue Questionnaire was used to measure QOL, while the Brief Fatigue Inventory (BFI) was used to assess the severity of fatigue.

Results

The total average mean and standard deviation of QOL were 84.58±18.07 and 4.65±1.14 for BFI scores, respectively. A significant association between fatigue and QOL was found in linear and multiple regression analyses. The relationships between fatigue severity and cancer stage, chemotherapy dose delay, dose reduction, chemotherapy regimen, and ethnicity were determined using binary logistic regression analysis.

Conclusion

The findings of this study are believed to be useful for helping oncologists effectively evaluate, monitor, and treat fatigue related to QOL changes.

Fatigue, anxiety, and quality of life in breast cancer patients compared to non-cancer controls: a nationwide longitudinal analysis

PURPOSE

Fatigue and anxiety are common and significant symptoms reported by cancer patients. Few studies have examined the trajectory of multidimensional fatigue and anxiety, the relationships between them and with quality of life.

METHODS

Breast cancer patients (n = 580) from community oncology clinics and age-matched controls (n = 364) completed fatigue and anxiety questionnaires prior to chemotherapy (A1), at chemotherapy completion (A2), and six months post-chemotherapy (A3). Linear mixed models (LMM) compared trajectories of fatigue /anxiety over time in patients and controls and estimated their relationship with quality of life. Models adjusted for age, education, race, BMI, marital status, menopausal status, and sleep symptoms.

RESULTS

Patients reported greater fatigue and anxiety compared to controls at all time points (p's < 0.001, 35% clinically meaningful anxiety at baseline). From A1 to A2 patients experienced a significant increase in fatigue (β = 8.3 95%CI 6.6,10.0) which returned to A1 values at A3 but remained greater than controls' (p < 0.001). General, mental, and physical fatigue subscales increased from A1 to A2 remaining significantly higher than A1 at A3 (p < 0.001). Anxiety improved over time (A1 to A3 β =  - 4.3 95%CI -2.6,-3.3) but remained higher than controls at A3 (p < 0.001). Among patients, fatigue and anxiety significantly predicted one another and quality of life. Menopausal status, higher BMI, mastectomy, and sleep problems also significantly predicted change in fatigue.

CONCLUSION

Breast cancer patients experience significant fatigue and anxiety up to six months post-chemotherapy that is associated with worse quality of life. Future interventions should simultaneously address anxiety and fatigue, focusing on mental and physical fatigue subdomains.

Excess Body Weight and Cancer-Related Fatigue, Systemic Inflammation, and Serum Lipids in Breast Cancer Survivors

BACKGROUND

Cancer-related fatigue (CRF) is a common side effect impacting breast cancer survivors. Research points to a relationship between obesity and CRF in breast cancer survivors related to elevated systemic inflammation and metabolic alterations.

METHODS

This cross-sectional study examined the relationship of obesity to CRF, inflammatory markers and serum lipids through a secondary analysis of a nationwide randomized controlled trial. Breast cancer survivors with CRF were categorized based on BMI category. Symptoms of CRF, inflammatory markers and serum fatty acids were assessed among groups.

RESULTS

There were 105 breast cancer survivors in the analysis. BMI was positively associated with CRF based on MFSI General (p = 0.020; 95% C.I. 0.024, 0.273) and MFSI Physical (p = 0.013; 95% C.I. 0.035, 0.298) subscales. TNF-α (p = 0.007; 95% C.I. 0.007, 0.044), and IL-6 (p = 0.020; 95% C.I. 0.006, 0.073) were elevated in the obese. Monounsaturated fatty acid levels (p = 0.047; 95% C.I. 0.000, 0.053) and the omega-6 to omega-3 fatty acid ratio were associated with obesity (p = 0.047; 95% C.I. 0.002, 0.322).

CONCLUSIONS

Obese breast cancer survivors had greater levels of CRF, inflammatory markers and certain fatty acids. Inflammatory markers and fatty acids were not found to have any mediating or positive association with CRF variables in this analysis. NCT02352779.