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Background: There is emerging evidence that cancer and its treatments may accelerate the normal aging process, increasing the magnitude and rate of decline in functional capacity. This accelerated aging process is hypothesized to hasten the occurrence of common adverse age-related outcomes in cancer survivors, including loss of muscle mass and decrease in physical function. However, there is no data describing age-related loss of muscle mass and its relation to physical function in the long-term in cancer survivors., Methods: This study protocol describes the use of a novel method of muscle mass measurement, D3-creatine dilution method (D3Cr), in a large sample (n~6000) of community dwelling postmenopausal women from the Women's Health Initiative (WHI). D3Cr will be used to obtain a direct measure of muscle mass remotely. Participants will be drawn from two sub-cohorts embedded within the WHI that have recently completed an in-home visit. Cancer survivors will be drawn from the Life and Longevity After Cancer (LILAC) cohort, and cancer-free controls will be drawn from the WHI Long Life Study 2. The overall objective of this study is to examine the antecedents and consequences of low muscle mass in cancer survivors. The study aims are to: 1) create age-standardized muscle mass percentile curves and z-scores to characterize the distribution of D3- muscle mass in cancer survivors and non-cancer controls, 2) compare muscle mass, physical function, and functional decline in cancer survivors and non- cancer controls, and 3) use machine learning approaches to generate multivariate risk-prediction algorithms to detect low muscle mass., Discussion: The D3Cr method will transform our ability to measure muscle mass in large-scale epidemiologic research. This study is an opportunity to advance our understanding of a key source of morbidity among older and long-term female cancer survivors. This project will fill knowledge gaps, including the antecedents and consequences of low muscle mass, and use innovative methods to overcome common sources of bias in cancer research. The results of this study will be used to develop interventions to mitigate the harmful effects of low muscle mass in older adults and promote healthy survivorship in cancer survivors in the old (>65) and oldest-old (>85) age groups., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Banack et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: This study evaluated the role of the Pediatric Sleep Questionnaire (PSQ) and associated subscales in predicting the severity of obstructive sleep apnea (OSA) in children referred for attended polysomnography (PSG)., Methods: This is a retrospective study of children (0-18 years) who completed PSQs the night of their initial diagnostic PSG (2019-2020). We excluded children with previous PSG, positive airway pressure titrations, or underlying genetic or craniofacial syndromes. Area under the receiver operating characteristic curve (AUC [95%CIs]) were estimated for prediction of varying severities of obstructive apnea-hypopnea index (oAHI > 2, 5, 10, and 25/h) by the PSQ's sleep-related breathing disorders (SRBD) scale and subscales., Results: Of 477 children, median (IQR) age at PSG was 5.7 (4.3); 60% of children were male, 21% were obese, and 4% had oAHI > 25/h. SRBD score did not improve discrimination of OSA cases at any oAHI threshold, with AUC CI that crossed 50% at all severities. Snoring subscale scores were predictive at oAHI > 2/h (AUC = 64.5% [59.5-69.5%]), oAHI > 5/h (AUC = 64.3% [59.6-69.0%]), and oAHI > 10 (AUC = 67.2% [62.0-72.4%]) thresholds, but were not predictive at oAHI > 25/h. The addition of demographic data (age and gender) improved the classification of the SRBD scale., Conclusions: When utilized in children referred for attended PSG due to concerns for an underlying sleep disorder, the PSQ snoring subscale was more predictive of OSA at varying thresholds than the SRBD scale. While the original intent of the PSQ was not for the purpose of predicting severity in children referred for PSG, future directions include augmenting the questionnaire with additional clinical variables., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Epidemiological evidence suggests that inadequate sleep duration and insomnia may be associated with increased risk of metabolic syndrome (MetS). However, longitudinal data with repeated measures of sleep duration and insomnia and of MetS are limited. We examined the association of sleep duration and insomnia with MetS and its components using longitudinal data from the Women's Health Initiative (WHI)., Methods: The study included postmenopausal women (ages 50-79 years) diabetes-free at enrollment in the WHI, with baseline data on sleep duration (n = 5,159), insomnia (n = 5,063), MetS, and its components. Repeated measures of self-reported sleep duration and insomnia were available from years 1 or 3 of follow-up and of the MetS components from years 3, 6 and 9. Associations were assessed using logistic regression and generalized estimating equations models, and odds ratios and 95% confidence intervals (CI) adjusted for major risk factors were calculated., Results: In cross-sectional analysis, baseline sleep duration ≥ 9 h was positively associated with MetS (OR = 1.51; 95%CI 1.12-2.04), while sleep duration of 8- < 9 h was associated with waist circumference > 88 cm and triglycerides ≥ 150 mg/dL (OR = 1.18; 95%CI 1.01-1.40 and OR = 1.23; 95%CI 1.05-1.46, respectively). Insomnia had a borderline positive association with MetS (OR = 1.14; 95%CI 0.99-1.31), and significant positive associations with waist circumference > 88 cm and glucose ≥ 100 mg/dL (OR = 1.18; 95%CI 1.03-1.34 and OR = 1.17; 95%CI 1.02-1.35, respectively). In the longitudinal analysis, change from restful sleep to insomnia over time was associated with increased odds of developing MetS (OR = 1.40; 95%CI 1.01-1.94), and of a triglyceride level ≥ 150 mg/dL (OR = 1.48; 95%CI 1.08-2.03)., Conclusions: Among postmenopausal women in the WHI, sleep duration and insomnia were associated with current and future risk of MetS and some of its components., (© 2022. The Author(s).)

Purpose: Aging associated with progressive declines in physical function is well-known; however, it is unclear how breast cancer diagnosis affects the trajectories of physical function over a long period of time. The current study examined the trajectories in objective measures of physical function over 20 years for women with breast cancer and matched controls., Methods: 2712 community-dwelling women (452 breast cancer cases and 1:5 matched cancer-free controls) aged 65 years or older at baseline (1986-1988) within the Study of Osteoporotic Fractures were followed for 20 years. Objective physical function was assessed up to 9 times, including hand grip strength, timed chair stand, gait speed and quadriceps strength. Linear mixed models were used to model physical function changes in terms of secular time trend, group (cases or controls), period (pre-and post-diagnosis status), and their interaction terms., Results: We observed all measures of physical function declined over time. While no differences in trends between cases and controls during the pre-diagnosis period were observed, after cancer diagnosis, grip strength and gait speed declined significantly faster in cases than controls. Quadriceps strength significantly decreased ~ 7 pounds shortly after breast cancer diagnosis, and then improved over time., Conclusion: Our study revealed that older breast cancer survivors relative to older women without cancer had significantly worse declines in grip strength and gait speed. Breast cancer survivors also had a sharp, short-term drop followed by gradual improvement over time in quadriceps strength. These findings suggest exercise training targeting muscle strength and mobility would be beneficial among older breast cancer survivors., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Adipose tissue radiodensity may have prognostic importance for colorectal cancer (CRC) survival. Lower radiodensity is indicative of larger adipocytes, while higher radiodensity may represent adipocyte atrophy, inflammation, or edema., Objectives: We investigated associations of adipose tissue radiodensity and longitudinal changes in adipose tissue radiodensity with mortality among patients with nonmetastatic CRC., Methods: In 3023 patients with stage I-III CRC, radiodensities of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were quantified from diagnostic computed tomography (CT) images. There were 1775 patients with follow-up images available. Cox proportional hazards models and restricted cubic splines were used to examine associations of at-diagnosis values and of longitudinal changes in VAT and SAT radiodensities with risks of death after adjusting for potential confounders, including body size and comorbidities., Results: VAT and SAT radiodensities were linearly associated with all-cause mortality: the HRs for death per SD increase were 1.21 (95% CI, 1.11-1.32) for VAT radiodensity and 1.18 (95% CI, 1.11-1.26) for SAT radiodensity. Changes in adipose tissue radiodensity had curvilinear associations with risks of death. The HR for an increase in VAT radiodensity of at least 1 SD was 1.53 (95% CI, 1.23-1.90), while the HR for a decrease of at least 1 SD was nonsignificant at 1.11 (95% CI, 0.84-1.47) compared with maintaining radiodensity within 1 SD of baseline. Similarly, increases (HR, 1.88; 95% CI, 1.48-2.40) but not decreases (HR, 1.20; 95% CI, 0.94-1.54) in SAT radiodensity significantly increased the risk of death compared with no change in radiodensity., Conclusions: In patients with nonmetastatic CRC, adipose tissue radiodensity is a novel risk factor for total mortality that is independent of BMI and changes in body weight., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Computed Tomography (CT) imaging is widely used for studying body composition, i.e., the proportion of muscle and fat tissues with applications in areas such as nutrition or chemotherapy dose design. In particular, axial CT slices from the 3rd lumbar (L3) vertebral location are commonly used for body composition analysis. However, selection of the third lumbar vertebral slice and the segmentation of muscle/fat in the slice is a tedious operation if performed manually. The objective of this study is to automatically find the middle axial slice at L3 level from a full or partial body CT scan volume and segment the skeletal muscle (SM), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT) and intermuscular adipose tissue (IMAT) on that slice. The proposed algorithm includes an L3 axial slice localization network followed by a muscle-fat segmentation network. The localization network is a fully convolutional classifier trained on more than 12,000 images. The segmentation network is a convolutional neural network with an encoder-decoder architecture. Three datasets with CT images taken for patients with different types of cancers are used for training and validation of the networks. The mean slice error of 0.87±2.54 was achieved for L3 slice localization on 1748 CT scan volumes. The performance of five class tissue segmentation network evaluated on two datasets with 1327 and 1202 test samples. The mean Jaccard score of 97% was achieved for SM and VAT tissue segmentation on 1327 images. The mean Jaccard scores of 98% and 83% are corresponding to SAT and IMAT tissue segmentation on the same dataset. The localization and segmentation network performance indicates the potential for fully automated body composition analysis with high accuracy., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Breast cancer survivors frequently report sleep problems, but little research has studied sleep patterns longitudinally. We examined trends in sleep quality and duration up to 15 years before and 20 years after a diagnosis of breast cancer, over time among postmenopausal women participating in the Women's Health Initiative (WHI). We included 12,098 participants who developed invasive breast cancer after study enrollment. A linear mixed-effects model was used to determine whether the time trend in sleep quality, as measured by the WHI Insomnia Rating Scale (WHIIRS), a measure of perceived insomnia symptoms from the past 4 weeks, changed following a cancer diagnosis. To examine sleep duration, we fit a logistic regression model with random effects for both short (<6 h) and long (≥9 h) sleep. In addition, we studied the association between depressive symptoms and changes in WHIIRS and sleep duration. There was a significantly slower increase in the trend of WHIIRS after diagnosis ( β  = 0.06; p  = 0.03), but there were non-significant increases in the trend of the probability of short or long sleep after diagnosis. The probability of depressive symptoms significantly decreased, though the decrease was more pronounced after diagnosis ( p  < 0.01). Trends in WHIIRS worsened at a relatively slower rate following diagnosis and lower depression rates may explain the slower worsening in WHIIRS. Our findings suggest that over a long period of time, breast cancer diagnosis does not adversely affect sleep quality and duration in postmenopausal women compared to sleep pre-diagnosis, yet both sleep quality and duration continue to worsen over time., Competing Interests: The authors declare no competing interests.

Importance: Systemic inflammation and sarcopenia are easily evaluated, predict mortality in many cancers, and are potentially modifiable. The combination of inflammation and sarcopenia may be able to identify patients with early-stage colorectal cancer (CRC) with poor prognosis., Objective: To examine associations of prediagnostic systemic inflammation with at-diagnosis sarcopenia, and determine whether these factors interact to predict CRC survival, adjusting for age, ethnicity, sex, body mass index, stage, and cancer site., Design, Setting, and Participants: A prospective cohort of 2470 Kaiser Permanente patients with stage I to III CRC diagnosed from 2006 through 2011., Exposures: Our primary measure of inflammation was the neutrophil to lymphocyte ratio (NLR). We averaged NLR in the 24 months before diagnosis (mean count = 3 measures; mean time before diagnosis = 7 mo). The reference group was NLR of less than 3, indicating low or no inflammation., Main Outcomes and Measures: Using computed tomography scans, we calculated skeletal muscle index (muscle area at the third lumbar vertebra divided by squared height). Sarcopenia was defined as less than 52 cm2/m2 and less than 38 cm2/m2 for normal or overweight men and women, respectively, and less than 54 cm2/m2 and less than 47 cm2/m2 for obese men and women, respectively. The main outcome was death (overall or CRC related)., Results: Among 2470 patients, 1219 (49%) were female; mean (SD) age was 63 (12) years. An NLR of 3 or greater and sarcopenia were common (1133 [46%] and 1078 [44%], respectively). Over a median of 6 years of follow-up, we observed 656 deaths, 357 from CRC. Increasing NLR was associated with sarcopenia in a dose-response manner (compared with NLR < 3, odds ratio, 1.35; 95% CI, 1.10-1.67 for NLR 3 to <5; 1.47; 95% CI, 1.16-1.85 for NLR ≥ 5; P for trend < .001). An NLR of 3 or greater and sarcopenia independently predicted overall (hazard ratio [HR], 1.64; 95% CI, 1.40-1.91 and HR, 1.28; 95% CI, 1.10-1.53, respectively) and CRC-related death (HR, 1.71; 95% CI, 1.39-2.12 and HR, 1.42; 95% CI, 1.13-1.78, respectively). Patients with both sarcopenia and NLR of 3 or greater (vs neither) had double the risk of death, overall (HR, 2.12; 95% CI, 1.70-2.65) and CRC related (HR, 2.43; 95% CI, 1.79-3.29)., Conclusions and Relevance: Prediagnosis inflammation was associated with at-diagnosis sarcopenia. Sarcopenia combined with inflammation nearly doubled risk of death, suggesting that these commonly collected biomarkers could enhance prognostication. A better understanding of how the host inflammatory/immune response influences changes in skeletal muscle may open new therapeutic avenues to improve cancer outcomes.