Sarcopenic Obesity in Survivors of Childhood Acute Lymphoblastic Leukemia: Prevalence, Risk Factors, and Implications for Cancer Survivors

Sarcopenic Obesity in Survivors of Childhood Acute Lymphoblastic Leukemia: Prevalence, Risk Factors, and Implications for Cancer Survivors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sarcopenic Obesity in Survivors of Childhood Acute Lymphoblastic Leukemia: Prevalence, Risk Factors, and Implications for Cancer Survivors Gargi Das, Kritika Setlur, Manisha Jana, Lakshmy Ramakrishnan, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4889834/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2024 Read the published version in Supportive Care in Cancer → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose: Sarcopenic obesity, characterized by increased adiposity with low skeletal muscle mass, contributes to frailty and the development of chronic disease. Data on sarcopenic obesity in survivors of childhood acute lymphoblastic leukemia (cALL) is limited. Methodology: A cross-sectional study on 65 cALL survivors (7-18 years, >2 years from treatment completion) was conducted on cALL survivors with the primary outcome to determine the prevalence of sarcopenic obesity. Sarcopenic obesity was defined as patients with a positive Fat Mass (FM) z-score with a negative Appendicular Lean Body Mass (APLBM) z-score, measured using Dual-Energy Xray Absorptiometry (DXA) scan. In addition, we assessed the factors associated with sarcopenic obesity by multivariable regression analysis. Results : The mean (±SD) age was 12.9 (±3.2) years, the median (Interquartile Range) time since diagnosis was 6.5 (5.9;8) years, and 66% received cranial radiotherapy. Central obesity, insulin resistance, and metabolic syndrome were seen in 21.5%, 23.1%, and 21% respectively. DXA-derived body composition variables revealed higher fat percentage despite normal body mass index (BMI) and lower muscle mass compared to the general population. Sarcopenic obesity was seen in 21 (32%) of survivors. On multivariable regression analysis, age at diagnosis (OR: 0.95 (95% CI: 0.92-0.98), p=0.02), central obesity (OR: 18.99 (95% 2.32-155.5), p=0.006) and insulin resistance (OR: 10.2 (95% CI: 1.75-59.09), p=0.01) were associated with sarcopenic obesity. Conclusions and Implications for cancer survivors : Sarcopenia, an early clinical indicator for metabolic disease despite normal BMI, was significantly worse in children diagnosed with ALL at a younger age and was associated with central obesity and insulin resistance, which may contribute to adverse outcomes later in life. Sarcopenic Obesity Adiposity Acute lymphoblastic leukemia Survivor Figures Figure 1 INTRODUCTION Sarcopenia is a syndrome characterized by progressive and generalized loss of skeletal muscle mass. It is either primary (age-related) or secondary to other illnesses, among which cancer is an important cause 1 . Sarcopenic obesity is a condition characterized by a combination of low muscle mass (sarcopenia) and high body fat (obesity) 1 . Sarcopenic obesity is associated with higher rates of complications during cancer therapy leading to frailty, increased chronic health morbidities, and mortality 2 . There is increasing evidence that sarcopenic obesity and frailty extend beyond cancer treatment and occur in long-term childhood cancer survivors 2 . Multiple pathophysiological changes occur leading to sarcopenic obesity in childhood cancer survivors (Figure I). Due to the loss of muscle mass, there is reduced expression of GLUT4, which in turn reduces the intake of insulin-mediated glucose uptake in the remaining skeletal muscles, hence perpetuating a state of insulin resistance 3 . Simultaneously, due to increased adipose tissue, there is a rise in pro-inflammatory cytokines, mimicking chronic inflammation 4 . The accumulation of adipose tissue and inflammation exacerbates the production of reactive oxygen species (ROS) by mitochondria, causing mitochondrial damage, activating proteolytic intracellular pathways, and inducing apoptosis 5 . Sarcopenic obesity and frailty are increasingly being studied in the context of childhood cancer survivorship and factors like general inactivity and improper nutrition and cancer treatment contribute to its occurrence. Children receiving Cranial radiotherapy (CRT) and recipients of Hematopoietic Stem Cell Transplantation (HSCT) are at an increased risk due to endocrine effects secondary to the impact of radiation on the hypothalamic-pituitary axis 6 . Corticosteroids, L-asparaginase, Anthracyclines, and other neurotoxic chemotherapeutic agents like methotrexate and vincristine may also predispose to sarcopenic obesity by various mechanisms 7 . There is evidence of a significant association of sarcopenic obesity with adverse cardiometabolic outcomes, non-alcoholic fatty liver disease, inflammation, and mental health in children and adolescents without cancer 8 . Sarcopenic obesity ultimately predisposes to an increased risk of metabolic and cardiovascular late effects 5 resulting in poor quality of life for childhood cancer survivors 9 . With improvement in survival of childhood acute lymphoblastic leukemia (cALL), there is an increase in the burden of chronic health morbidities 10 . With contemporary protocols, the endocrine and musculoskeletal late effects predominate; compared to controls, nearly twice as many cALL survivors had impaired muscle function, regardless of CNS prophylaxis therapy 11 . Muscle development starts from a young age and hence the impact of cancer therapy and lifestyle on the muscle health of childhood cancer survivors is of growing interest 7 . There are various definitions of sarcopenic obesity in children and adolescents 8,9,12–14 , and they may vary slightly depending on the specific criteria used. There is ongoing debate and research on the best way to define and diagnose sarcopenic obesity in pediatric populations, and more studies are needed to establish standardized criteria for this condition. For this study, we used variables derived from a whole-body dual-energy X-ray absorptiometry (DXA) scan and defined sarcopenic obesity as individuals with a positive (+) Fat mass (FM) z-score along with a negative (-) Appendicular Lean body mass (ALMB) z-score 9 . This definition was used previously in a study analyzing sarcopenic obesity in childhood ALL survivors and are simple variables, retrievable from a whole-body DXA scan, which we thought would gave us an overview of the problem 9 . We hence aimed to evaluate the prevalence of sarcopenic obesity in a cohort of cALL survivors and tried to delineate various factors associated with increased risk of sarcopenic obesity. METHODOLOGY Participants: This study was set in the Division of Pediatric Oncology, Department of Pediatrics, AIIMS-New Delhi. Participants were sequentially enrolled over one year (November 2020 to December 2021). Survivors of cALL who were more than 2 years from treatment completion and consented to participate, were included in this study. Sequential enrolment was done and survivors with known hypothyroidism, hypertension, deranged lipid profile, and diabetes, diagnosed before the treatment of ALL, were excluded from the study. Ethical approval: Ethics approval was taken by the institute ethics committee of the All India Institute of Medical Sciences vide Ref-no: IECPG-628/28.11.2019, RT-08/19.12.2019, and the research was conducted per the ethical guidelines laid down by the Helsinki Declaration. Treatment Received: Before 2012, children with ALL were treated on various protocols including the International Network for Cancer Treatment and Research protocol (INCTR) protocol 15 , and the ALL-Berlin Frankfurt Munster-95 (ALL-BFM 95) protocol 16 . Most children received prophylactic CRT in addition to chemotherapy for their management (12.6Gy in the INCTR protocol and 18Gy in the BFM protocol). Children with CNS Leukemia received 18Gy and 24Gy CRT in the INCTR and BFM protocols, respectively. In 2012, the Indian Childhood Collaborative Leukemia Group (ICiCLe) was established under the aegis of the Indian Pediatric Oncology Group (InPOG) 17 . In this protocol, only children presenting with CNS leukemia received CRT (24Gy). Data acquisition, general examination, anthropometric assessment: Demographic and treatment details were abstracted from medical records and included age at enrolment and diagnosis, time since diagnosis and treatment completion, protocol used, chemotherapy received (including cumulative doses for specific drugs), and details of radiation. Weight and height were measured and Body Mass Index (BMI) was defined as weight (kg)/height (m 2 ). After calculating BMI for children, the BMI was plotted on the Indian Academy of Pediatrics (IAP) BMI-for-age growth charts to obtain a percentile ranking. A BMI of more than 23 adult-equivalent was classified as overweight and more than 27 adult-equivalent as obese 18 . Waist circumference (WC) was measured and central obesity was defined for the 10-16 years age group as WC of ≥90 th percentile 19 or Indian adult WC cut-offs 20 if lower. For children older than 16 years of age WC was defined as per ethnicity-specific values for adults (Indian men 90 cm and women 80 cm) 20 . Blood Pressure was classified according to the American Academy of Pediatrics (AAP) updated guidelines as normal, elevated BP, stage 1 hypertension, and stage 2 hypertension using reference data specific for sex, age, and height 21 . The pubertal stage was determined based on Tanner’s standard photographs for pubic hair and genital development 22 . Measurement of analytes: Blood samples were obtained in the morning after fasting. Fasting plasma glucose concentrations were determined by the hexokinase method in Olympus AU680 (Beckman Coulter). Impaired fasting glucose was defined as ≥100mg/dL 23 , 24 . Triglycerides and High-density Lipoprotein (HDL) were measured by the enzymatic colorimetric method in Olympus AU680 (Beckman Coulter). Elevated triglyceride levels were defined as ≥150mg/dL, and low HDL levels of 10 years only) were considered significant 23 . The consensus definition of metabolic syndrome by the International diabetes federation (IDF) in 2007 23 was used for this study. This definition applies to children older than 10 years of age. Plasma insulin was determined by electrochemiluminescence assay (ECLIA, Roche Cobas e411). Insulin resistance (IR) was defined by fasting insulin level greater than 15μU/mL during prepuberty, 30μU/mL at puberty, and greater than 20μU/mL after puberty (Tanner stage I prepuberty, stage II-IV puberty, and stage V post-puberty) 25 . Body composition assessment: A DXA scan, using a HOLOGIC DISCOVERY DXA scanner was used to assess the body composition of the survivors. Primarily, the DXA scan provides an in-depth analysis of the main components of the body; fat, muscle, and bone. It provides the raw bone mineral content, fat mass, and lean mass content. Lean mass constitutes both soft tissue and muscle mass. Appendicular lean mass (part of lean mass) is more representative of the skeletal muscle mass of an individual. All the above masses were calculated in grams and presented after adjustment for the height (/m 2 ) as indices. The fat mass index (FMI) was Fat Mass (FM)/height 2 , the Lean Body Mass Index (LBMI) was Lean Body Mass (LBM)/height 2 , and the Skeletal muscle index (SMI), for this study, was defined as Appendicular Lean Body Mass (ALBM)/height 2 . Additional data gathered was percentage body fat, android/gynoid ratio, trunk to limb fat mass and percentage fat ratio. Percentiles were calculated for total body fat percentage, FMI, and android/gynoid ratios (>85 th percentile defined as increased cardiometabolic risk) in reference to Indian standards 26 . Since Indian values for z-score estimation are not available, we used the DXA whole-body dataset from the National Health and Nutrition Examination Survey (NHANES) population-based sample to calculate z-scores for these various indices 27 . Sarcopenic obesity was defined as a positive (+) FM z-score along with a negative (-) appendicular LBM z-score in a particular individual 28 . Bone mineral density (BMD) was assessed using whole body (WB) DXA scan parameter and low-BMD was considered when z-scores were<-2 29 . Sample size: The sample size for the study was calculated based on a previous study in India with a prevalence of sarcopenic obesity of 14%. With a 95% confidence interval, 10% precision, and 10% drop-out, a minimum of 53 patients were required for sequential sampling in this study. Statistical Analysis: The data was analyzed using STATA/SE 14.0 software. All qualitative variables were expressed as frequency (N, %). Normality was assessed using the Kolmogorov-Smirnov test. All quantitative variables were expressed as mean (±SD) for normally distributed data and median with interquartile range (IQR) for non-normally distributed data. A univariate logistic regression analysis was done to assess the association of sarcopenic obesity in cALL survivors with independent variables. Significant variables (considered as a p-value of <0.05) were included in the multivariable logistic regression along with age and gender. Additionally, an exploratory analysis was done, where we looked at body composition differences in variables that were significant in the multivariable analysis. Comparisons between continuous variables were performed with the Student’s t-test/Analysis of Variance (ANOVA) test if data was normally distributed, or the Wilcoxon rank-sum (Mann–Whitney U), if the data was skewed. RESULTS Clinical, and metabolic profile of cALL survivors We enrolled 65 consecutive survivors of cALL. None of them had pre-existing hypothyroidism, hypertension, deranged lipid profile, or diabetes diagnosed during treatment. The mean (±SD) age at enrolment was 12.9 (±3.2) years and the median (IQR) time since diagnosis was 6.5 (5.9;8) years. Among the survivors, 48 (74%) were male and 37 (57%) were between Tanner stage 2-4. The clinical details are provided in Table 1. Among the survivors, the mean (±SD) BMI was 19.1 (±3.2), and the median (IQR) BMI z-score was -0.14 (-1; 0.96). The metabolic evaluation of the survivors is given in Table 1. Metabolic syndrome was present in 11/53 (21%) survivors, and insulin resistance was seen in 15/65 (23.1%) cALL survivors. Table 1: Clinical and Metabolic Profile of Survivors Variable Result N (%) Diagnosis (N=65) B-cell ALL T-cell ALL 55 (85) 10 (15) Chemotherapy Protocol Used ( N=65) INCTR BFM ICiCLe 38 (58) 5 (8) 22 (34) Cranial Radiotherapy (N=65) Prophylactic RT- 12.6 Gy Prophylactic RT- 18 Gy CNS Leukemia- 18 Gy CNS positive- 24 Gy 43/65 (66) 38 4 1 0 HSCT 0 BMI categories (N=65) Underweight 27) 3 (4.6) 42 (64.6) 10 (15.4) 10 (15.4) Central Obesity (N=65) 14 (21.5) Stage 1 & 2 Hypertension (N=65) 12 (18.5) Impaired Fasting Glucose (N=65) 12 (18.5) Triglycerides >150mg/dL (N=53) 14 (26) HDL <40mg/dL (N=53) 21 (40) Metabolic Syndrome (N=53) 11 (21) Insulin Resistance (N=65) 15 (23.1) * ALL: Acute Lymphoblastic Leukemia, INCTR: International Network for Cancer Treatment and Research , BFM: Berlin Frankfurt Munster , ICiCLe: Indian Childhood Collaborative Leukemia Group , BMI: Body Mass Index, HSCT: Hematopoietic Stem Cell Transplant Body composition cALL survivors Body composition was assessed by a DXA scan and is presented in Table 2. Increased cardiometabolic risk, defined as >85 th percentile of total body fat percentage, FMI, and android/gynoid ratios was seen in 50%, 45%, and 26% respectively, and among them, BMI was normal in 44%, 34%, and 24% of survivors respectively. Interestingly, mean LBMI and SMI were also higher in overweight and obese as compared to survivors with normal BMI. Sarcopenic obesity was seen in 32% of survivors. Among the survivors with sarcopenic obesity, around half (47%) were overweight/obese and half had normal BMI or were underweight. The median BMD z-score was -0.95 (-1.85; -0.3), with 8/40 (20%) having low BMD. Table 2: Body composition as derived by DXA scan Variable Result FAT INDICES Total Body Fat % (Mean ± SD) 32.7 ± 8.6 Total Body Fat >85 th Percentile (N, %) Normal BMI Overweight BMI Obese BMI 32/65, 50 14/32, 44 8/32, 25 10/32, 31 Fat Mass Index (Median (IQR)) 5.27 (4.1;8.3) Fat Mass Index >85 th Percentile (N, %) Normal BMI Overweight BMI Obese BMI 29/65, 45 10/29, 34 9/29, 32 10/29, 34 Android/Gynoid ratio (Mean ± SD) 0.89 ± 0.13 Android/Gynoid ratio >85 th Percentile (N, %) Normal BMI Overweight BMI Obese BMI 17/65, 26 4/17, 24 4/17, 24 9/17, 52 Trunk to Limb Fat mass ratio 0.85 ± 0.21 Trunk to Limb Fat mass ratio in Normal BMI Overweight BMI Obese BMI Male 0.8 ± 0.2 1.0 ± 0.4 1.0 ± 0.1 Female 0.8 ± 0.1 0.9 ± 0.2 0.9 Trunk to Limb Percentage Fat ratio 0.84 ± 0.12 Trunk to Limb Percentage Fat ratio in Normal BMI Overweight BMI Obese BMI Male 0.8 ± 0.1 0.9 ± 0.2 1.0 ± 0.2 Female 0.8 ± 0.1 0.9 ± 0.1 0.9 MUSCLE INDICES Lean Body Mass Index (Mean ± SD) 12.8 ± 3.8 Lean Body Mass Index (Mean ± SD) in Normal BMI Overweight BMI Obese BMI Male 11.9 ± 2.0 14.0 ± 2.3 18.2 ± 6.9 Female 10.7 ± 0.7 12.2 ± 1.4 13.9 Skeletal Muscle Index (Mean ± SD) 5.5 ± 2 Skeletal Muscle Index (Mean ± SD) in Normal BMI Overweight BMI Obese BMI Male 5.2 ± 1.1 6.1 ± 1.4 8.2 ± 3.5 Female 4.3 ± 0.6 4.8 ± 0.7 5.8 Z-SCORES Fat mass z-score (Median (IQR)) -0.1 (-0.7;0.9) Appendicular lean mass z-score (Median (IQR)) -1.3 (-2.2; -0.6) Sarcopenic Obesity Normal BMI Overweight BMI Obese BMI 21/65 (33%) 10/21 47 5/21, 24 6/21, 29 Regression analysis for association of Sarcopenic obesity and various demographic, metabolic, and treatment-associated variables Variables including demographic and treatment-related risk factors, younger age at diagnosis, longer time since diagnosis, female gender, baseline immunophenotype, presence of overweight/obesity, central obesity, insulin resistance, the radiation received, cumulative doses of prednisolone and other chemotherapeutic agents were included in the regression model (Table 3, presented as (OR, (95% CI), p-value)). Age at diagnosis (0.95 (0.92-0.98), p=0.02), central obesity (18.99 (2.32-155.5), p=0.006) and insulin resistance (10.2 (1.75-59.09), p=0.01) were associated with the presence of sarcopenic obesity, while treatment-related variables, did not have a direct impact. Table 3 Association between Sarcopenic obesity and various demographic, metabolic, and treatment-associated variables Variable Sarcopenic Obesity Unadjusted Regression Multivariable model (adjusted for age and gender) OR (95% CI) p-value OR (95% CI, p-value) Female Sex 1.24 (0.38-4.06) 0.722 Younger age at diagnosis 0.98 (0.96-0.99) 0.020 0.95 (0.92-0.98), 0.002 Time since diagnosis 1.03 (1.01-1.05) 0.009 Overweight/Obese 4.53 (1.43-14.38) 0.010 Central Obesity 5.40 (1.51-19.29) 0.009 18.99 (2.32-155.49), 0.006 Insulin Resistance 8.41 (2.2-32.14) 0.002 10.2 (1.75-59.09), 0.010 Low BMD z-score 1.14 (0.29-4.45 0.847 Cranial Radiation 0.83 (0.27-2.56) 0.743 Prednisolone Equivalent (mg/m 2 ) 1.00 (0.99-1.00) 0.488 Doxorubicin(mg/m 2 ) 1.00 (0.99-1.00) 0.771 Cyclophosphamide (mg/m 2 ) 1.00 (0.99-1.00) 0.704 L-Asparaginase (U/m 2 ) 1.00 (0.99-1.00) 0.413 Body composition distribution in the significant variables The results of our exploratory analysis on the body composition distribution in the variables that were significant in the multivariable logistic regression analysis are given in Table 4. In survivors with insulin resistance and central obesity, there was a significantly higher fat composition (higher FMI) with similar to increased proportion of muscle composition. On the contrary, patients younger than 5 years at diagnosis had a significantly lower muscle composition (lower LBMI and skeletal muscle mass index), with similar fat composition (FMI), compared to older survivors. Table 4: Distribution of body composition in the significant variables in the regression analysis Variable Fat Mass/Height 2 , kg/m 2 (Median (IQR)) Lean Mass/Height 2 , kg/m 2 (Mean ± SD) Appendicular Lean Mass/Height 2 , kg/m 2 (Mean ± SD) Age at diagnosis 5 years 6.2 (4.1-9.9) 14.2 ± 4.8 6.3 ± 2.5 p-value 0.264 0.003 0.001 Insulin Resistance Yes 9.0 (6.4-12) 13.4 ± 0.8 5.6 ± 0.4 No 4.89 (3.7-6.7) 12.6 ± 0.6 5.5 ± 0.3 p-value 0.0002 0.497 0.903 Central Obesity Yes 10.3 (9.2-13.7) 16.4 ± 6.2 7.3 ± 3.2 No 4.9 (3.7-6.4) 11.8 ± 1.8 5.1 ± 1.7 p-value <0.001 <0.001 <0.001 DISCUSSION The prevalence of sarcopenic obesity in this group of predominantly adolescent survivors of cALL, more than 2 years from treatment completion, was 34%. Other groups have shown a prevalence of sarcopenia and sarcopenic obesity to vary between 4 to 43% 28,31–33 . These studies mainly included adult survivors of childhood cancer from high-income countries with varying definitions of sarcopenic obesity. In a similar study from North India, sarcopenic obesity was seen in 14% of adolescent survivors of childhood cancer. They used body fat percentage and lean body mass criteria to define sarcopenic obesity 30 . Even though their group of survivors had a similar body fat percentage (35.2% vs 32%) and LBMI (12.3 vs 12.8%) to our group, the prevalence of sarcopenic obesity was half of that seen in our population. Hence it is important to have standardized definitions for sarcopenic obesity, which can be easily replicated in our clinics to generate data and assess the true magnitude of the problem. For our study, we used a simple definition for sarcopenic obesity defined previously as a positive fat mass z-score along with a negative appendicular lean body mass z-score 9 . These simple variables, retrievable from a whole-body DXA scan, gave us an overview of the problem and this definition was used previously in a study analyzing sarcopenic obesity in childhood ALL survivors 9 . There is limited data on body adiposity in healthy Indian children and adolescents. In our study, more than 85 th percentile of total body fat percentage, FMI, and android/gynoid ratios was seen in 50%, 45%, and 26% respectively, indicating those at increased risk for Metabolic Syndrome 26 . A large proportion of these patients had a normal BMI. They also had a much lower skeletal muscle index when compared to values reported in another study from our institute on non-cancer children and adolescents from New Delhi (Males: Normal BMI- 8.2 vs 5.2, Overweight- 9.4 vs 6.1, Obese- 9.4 vs 8.2; Females: Normal BMI- 6.5 vs 4.3, Overweight- 7.7 vs 4.8, and 8.1 vs 5.8 34 ) 34 . Similarly, in our study, sarcopenic obesity occurs in close to 50% of survivors with a normal BMI. This signifies that a significant proportion of cancer survivors in the study are at an increased risk for cardiometabolic late effects, despite having a normal BMI. This indicates that body composition, specifically high body fat percentage and android/gynoid ratios, may be more important indicators of metabolic health than BMI alone in this population. Additionally, the lower skeletal muscle index in these patients compared to non-cancer children and adolescents suggests potential muscle wasting or loss, which can also impact metabolic health and overall well-being. Hence sarcopenic obesity may be overlooked unless actively screened for, leading to an underestimation of the problem. The prevalence of sarcopenic obesity is closely linked with the prevalence of frailty (limitations in physical performance/poor fitness or simply premature aging) because of a similar underlying pathophysiology 31,35,36 . With the increase in the number of childhood cancer survivors living into adulthood, a subset of them will be at risk for both sarcopenic obesity and frail health, which may ultimately lead to a poor quality of life 37 . From our regression model, age at diagnosis, central obesity, and insulin resistance were associated with the presence of sarcopenic obesity, while treatment-related variables, did not have a direct impact. Male sex, cranial irradiation, HSCT, and age at diagnosis are variables that have been reported to be associated with sarcopenic obesity 31–33 . Previous studies have not reported the association of central obesity or insulin resistance with sarcopenic obesity in childhood cancer survivors. Our exploratory analysis found that patients with central obesity and insulin resistance had a greater increase in fat mass compared to muscle mass. This trend has also been observed in obese children without cancer 34 . The associations between central obesity, insulin resistance, and high muscle and fat mass are novel findings. Interestingly, we also found that children diagnosed at a younger age had an increased association with sarcopenic obesity and they had lower lean and appendicular mass with similar fat mass compared to older patients at diagnosis. Muscle has a variety of functions including movement, glucose, and amino acid homeostasis and protection of other organs against trauma 7 . Hence, poor muscle health is an indicator of metabolic disease, eventually leading to chronic morbidity and mortality 38,39 . There is emerging data on the long-term effects of childhood leukemia treatment on muscle health 40–45 . Based on our results it can be hypothesized that younger children, when exposed to chemo- or radiotherapy, are at a greater risk of reduction in muscle health, which in turn may lead to adverse long-term muscle-related late effects. Our study on sarcopenic obesity in young cALL survivors bears all the limitations of a cross-sectional study. It focused on metabolic late effects and used only muscle and fat mass criteria for sarcopenic obesity. Additional assessment of muscle function would have added to the validity of our results. A large proportion of the cohort received cranial radiation, limiting generalizability. However, they do contribute to a large proportion of childhood leukemia survivors, especially in low-middle-income countries like India. Confidence intervals in the regression analysis are wide and should be interpreted with caution. Most importantly, normative data for DXA-derived body adiposity variables are not available for growing children and adolescents. We have compared results among subgroups and to other studies whenever possible. Limitations notwithstanding, this data can be used for larger studies on muscle health in cALL survivors, guiding future trials and rehabilitative interventions. To conclude, sarcopenic obesity in adolescent survivors of cALL is an early clinical indicator of metabolic disease. Factors such as age at diagnosis, central obesity, and insulin resistance were associated with sarcopenic obesity in this group, highlighting the complex interplay of various risk factors. Given that muscle development occurs early in life, a time when childhood cancer patients are exposed to aggressive therapy, they are at risk for early decline in muscle health that may contribute to adverse outcomes later in life. Rehabilitative interventions should be targeted earlier in survivorship to improve the health and overall quality of life of our growing cALL survivor population. Abbreviations Abbreviation Full Form cALL Childhood ALL APLBM Appendicular Lean Body Mass BMC Bone Mineral Content BMD Bone Mineral Density BMI Body Mass Index CNS Central nervous system CRT Cranial Radiotherapy DXA Dual-Energy Xray Absorptiometry ECLIA Electrochemiluminescence assay FMI Fat Mass Index HDL High density lipoprotein HOMA-IR Homeostatic Model Assessment of Insulin Resistance HSCT Hematopoietic stem cell transplant IAP Indian Academy of Pediatrics ICiCLe Indian Childhood Collaborative Leukemia IDF International diabetes federation InPOG Indian Pediatric Oncology Group INCTR International Network for Cancer Treatment and Research protocol IR Insulin Resistance LAR Leptin to Adiponectin Ratio LBM Lean Body Mass LBMI Lean Body Mass Index LDL Low Density Lipoprotein NHANES National Health and Nutrition Examination Survey SMI Skeletal Muscle Index VLDL Very Low-Density Lipoprotein WC Waist circumference Declarations Funding: The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author contribution: All authors contributed to the study's conception and design. Gargi Das, Kritika Setlur, and Rachna Seth performed material preparation, data collection, and analysis. Final Data analysis and interpretation were performed by Gargi Das, Sadanand Dwivedi, Aditya Gupta, and Jagdish Prasad Meena. DXA scans and laboratory tests were performed and interpreted by Manisha Jana, Lakshmy Ramaswamy, and Vandana Jain. The first draft of the manuscript was written by Gargi Das and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Competing Interests: The authors have no relevant financial or non-financial interests to disclose. Data Availability: The datasets generated during and analyzed during the current study are available from the corresponding author upon reasonable request. Ethics: The research was conducted per the ethical guidelines laid down by the Helsinki Declaration. Ethics approval was taken by the institute ethics committee of the All-India Institute of Medical Sciences vide Ref no.: IECPG-628/28.11.2019, RT-08/19.12.2019. Consent to Participate: Written informed consent was obtained from the parents and children provided assent (verbal and written) wherever necessary. Consent to Publish: Not applicable References Santilli V, Bernetti A, Mangone M, Paoloni M. Clinical definition of sarcopenia. Clin Cases Miner Bone Metab Off J Ital Soc Osteoporos Miner Metab Skelet Dis. 2014;11(3):177–180. Baracos VE, Arribas L. Sarcopenic obesity: hidden muscle wasting and its impact for survival and complications of cancer therapy. Ann Oncol. 2018;29:ii1-ii9. doi: 10.1093/annonc/mdx810 Silveira EA, Da Silva Filho RR, Spexoto MCB, Haghighatdoost F, Sarrafzadegan N, De Oliveira C. The Role of Sarcopenic Obesity in Cancer and Cardiovascular Disease: A Synthesis of the Evidence on Pathophysiological Aspects and Clinical Implications. 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Cancer. 2015;121(10):1540–1547. doi: 10.1002/cncr.29211 Ness K, Howell C, Bjornard K. Frailty and quality of life in adult survivors of childhood cancer. Expert Rev Qual Life Cancer Care. 2017;2(2):79–85. doi: 10.1080/23809000.2017.1300507 Steene-Johannessen J, Anderssen SA, Kolle E, Andersen LB. Low muscle fitness is associated with metabolic risk in youth. Med Sci Sports Exerc. 2009;41(7):1361–1367. doi: 10.1249/MSS.0b013e31819aaae5 Benson AC, Torode ME, Singh MAF. Muscular strength and cardiorespiratory fitness is associated with higher insulin sensitivity in children and adolescents. Int J Pediatr Obes IJPO Off J Int Assoc Study Obes. 2006;1(4):222–231. doi: 10.1080/17477160600962864 Ness KK, Hudson MM, Ginsberg JP, et al. Physical performance limitations in the Childhood Cancer Survivor Study cohort. J Clin Oncol Off J Am Soc Clin Oncol. 2009;27(14):2382–2389. doi: 10.1200/JCO.2008.21.1482 Hovi L, Era P, Rautonen J, Siimes MA. Impaired muscle strength in female adolescents and young adults surviving leukemia in childhood. Cancer. 1993;72(1):276–281. doi: 10.1002/1097-0142(19930701)72:13.0.co;2-2 Ness KK, Baker KS, Dengel DR, et al. Body composition, muscle strength deficits and mobility limitations in adult survivors of childhood acute lymphoblastic leukemia. Pediatr Blood Cancer. 2007;49(7):975–981. doi: 10.1002/pbc.21091 Ness KK, DeLany JP, Kaste SC, et al. Energy balance and fitness in adult survivors of childhood acute lymphoblastic leukemia. Blood. 2015;125(22):3411–3419. doi: 10.1182/blood-2015-01-621680 Ness KK, Hudson MM, Pui CH, et al. Neuromuscular impairments in adult survivors of childhood acute lymphoblastic leukemia: associations with physical performance and chemotherapy doses. Cancer. 2012;118(3):828–838. doi: 10.1002/cncr.26337 van Brussel M, Takken T, van der Net J, et al. Physical function and fitness in long-term survivors of childhood leukaemia. Pediatr Rehabil. 2006;9(3):267–274. doi: 10.1080/13638490500523150 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2024 Read the published version in Supportive Care in Cancer → Version 1 posted Editorial decision: Revision requested 10 Oct, 2024 Reviews received at journal 09 Oct, 2024 Reviews received at journal 01 Oct, 2024 Reviewers agreed at journal 27 Sep, 2024 Reviewers agreed at journal 26 Sep, 2024 Reviewers invited by journal 26 Sep, 2024 Editor assigned by journal 22 Sep, 2024 Submission checks completed at journal 13 Aug, 2024 First submitted to journal 09 Aug, 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. 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03:57:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4889834/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4889834/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00520-024-09025-w","type":"published","date":"2024-11-26T15:57:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68653777,"identity":"cab0a05b-74ae-456b-8e75-bcbeb0010e1d","added_by":"auto","created_at":"2024-11-10 13:46:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":367443,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCancer treatment and its link to sarcopenic obesity and other chronic health morbidities\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1Cancertreatmentanditslinktosarcopenicobesityandotherchronichealthmorbidities.png","url":"https://assets-eu.researchsquare.com/files/rs-4889834/v1/3c9f6791a780341c5c4d56e7.png"},{"id":70389646,"identity":"ba77e47b-bbd9-450e-8930-253205d0e85b","added_by":"auto","created_at":"2024-12-02 17:29:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1426749,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4889834/v1/6e4dcd03-7eb3-4df7-9a3e-5ce3b39cb865.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSarcopenic Obesity in Survivors of Childhood Acute Lymphoblastic Leukemia: Prevalence, Risk Factors, and Implications for Cancer Survivors\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSarcopenia is a syndrome characterized by progressive and generalized loss of skeletal muscle mass. It is either primary (age-related) or secondary to other illnesses, among which cancer is an important cause\u003csup\u003e1\u003c/sup\u003e. Sarcopenic obesity is a condition characterized by a combination of low muscle mass (sarcopenia) and high body fat (obesity)\u003csup\u003e1\u003c/sup\u003e. Sarcopenic obesity is associated with higher rates of complications during cancer therapy leading to frailty, increased chronic health morbidities, and mortality\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere is increasing evidence that sarcopenic obesity and frailty extend beyond cancer treatment and occur in long-term childhood cancer survivors\u003csup\u003e2\u003c/sup\u003e. Multiple pathophysiological changes occur leading to sarcopenic obesity in childhood cancer survivors (Figure I). Due to the loss of muscle mass, there is reduced expression of GLUT4, which in turn reduces the intake of insulin-mediated glucose uptake in the remaining skeletal muscles, hence perpetuating a state of insulin resistance\u003csup\u003e3\u003c/sup\u003e. Simultaneously, due to increased adipose tissue, there is a rise in pro-inflammatory cytokines, mimicking chronic inflammation\u003csup\u003e4\u003c/sup\u003e. The accumulation of adipose tissue and inflammation exacerbates the production of reactive oxygen species (ROS) by mitochondria, causing mitochondrial damage, activating proteolytic intracellular pathways, and inducing apoptosis\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSarcopenic obesity and frailty are increasingly being studied in the context of childhood cancer survivorship and factors like general inactivity and improper nutrition and cancer treatment contribute to its occurrence. Children receiving Cranial radiotherapy (CRT) and recipients of Hematopoietic Stem Cell Transplantation (HSCT) are at an increased risk due to endocrine effects secondary to the impact of radiation on the hypothalamic-pituitary axis\u003csup\u003e6\u003c/sup\u003e. Corticosteroids, L-asparaginase, Anthracyclines, and other neurotoxic chemotherapeutic agents like methotrexate and vincristine may also predispose to sarcopenic obesity by various mechanisms\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere is evidence of a significant association of sarcopenic obesity with adverse cardiometabolic outcomes, non-alcoholic fatty liver disease, inflammation, and mental health in children and adolescents without cancer\u003csup\u003e8\u003c/sup\u003e. Sarcopenic obesity ultimately predisposes to an increased risk of metabolic and cardiovascular late effects\u003csup\u003e5\u003c/sup\u003e resulting in poor quality of life for childhood cancer survivors\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWith improvement in survival of childhood acute lymphoblastic leukemia (cALL), there is an increase in the burden of chronic health morbidities\u003csup\u003e10\u003c/sup\u003e. With contemporary protocols, the endocrine and musculoskeletal late effects predominate; compared to controls, nearly twice as many cALL survivors had impaired muscle function, regardless of CNS prophylaxis therapy\u003csup\u003e11\u003c/sup\u003e. Muscle development starts from a young age and hence the impact of cancer therapy and lifestyle on the muscle health of childhood cancer survivors is of growing interest\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere are various definitions of sarcopenic obesity in children and adolescents\u003csup\u003e8,9,12\u0026ndash;14\u003c/sup\u003e, and they may vary slightly depending on the specific criteria used. There is ongoing debate and research on the best way to define and diagnose sarcopenic obesity in pediatric populations, and more studies are needed to establish standardized criteria for this condition. For this study, we used variables derived from a whole-body dual-energy X-ray absorptiometry (DXA) scan and defined sarcopenic obesity as individuals with a positive (+) Fat mass (FM) z-score along with a negative (-) Appendicular Lean body mass (ALMB) z-score\u003csup\u003e9\u003c/sup\u003e. This definition was used previously in a study analyzing sarcopenic obesity in childhood ALL survivors and are simple variables, retrievable from a whole-body DXA scan, which we thought would gave us an overview of the problem\u003csup\u003e9\u003c/sup\u003e. We hence aimed to evaluate the prevalence of sarcopenic obesity in a cohort of cALL survivors and tried to delineate various factors associated with increased risk of sarcopenic obesity.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003e\u003cstrong\u003eParticipants:\u0026nbsp;\u003c/strong\u003eThis study was set in the Division of Pediatric Oncology, Department of Pediatrics, AIIMS-New Delhi. Participants were sequentially enrolled over one year (November 2020 to December 2021). \u0026nbsp;Survivors of\u0026nbsp;cALL who were more than 2 years from treatment completion and consented to participate, were included in this study. Sequential enrolment was done and survivors with known hypothyroidism, hypertension, deranged lipid profile, and diabetes, diagnosed before the treatment of ALL, were excluded from the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eEthics approval was taken by the institute ethics committee of the All India Institute of Medical Sciences vide Ref-no: IECPG-628/28.11.2019, RT-08/19.12.2019, and the research was conducted per the ethical guidelines laid down by the Helsinki Declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTreatment Received:\u0026nbsp;\u003c/strong\u003eBefore\u0026nbsp;2012, children with ALL were treated on various protocols including the\u0026nbsp;International Network for Cancer Treatment and Research protocol (INCTR) protocol\u003csup\u003e15\u003c/sup\u003e, and the ALL-Berlin Frankfurt Munster-95 (ALL-BFM 95) protocol\u003csup\u003e16\u003c/sup\u003e. Most children received prophylactic CRT in addition to chemotherapy for their management (12.6Gy in the INCTR protocol and 18Gy in the BFM protocol). Children with CNS Leukemia received 18Gy and 24Gy CRT in the INCTR and BFM protocols, respectively. In\u0026nbsp;2012, the\u003cem\u003eIndian Childhood Collaborative Leukemia Group (ICiCLe) was\u003c/em\u003eestablished under the aegis of the Indian Pediatric Oncology Group (InPOG)\u003csup\u003e17\u003c/sup\u003e. In this protocol, only children presenting with CNS leukemia received CRT (24Gy).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData acquisition, general examination, anthropometric assessment:\u0026nbsp;\u003c/strong\u003eDemographic and treatment details were abstracted from medical records and included age at enrolment and diagnosis, time since diagnosis and treatment completion, protocol used, chemotherapy received (including cumulative doses for specific drugs), and details of radiation.\u0026nbsp;Weight and height were measured and\u0026nbsp;Body Mass Index (BMI) was defined as weight (kg)/height (m\u003csup\u003e2\u003c/sup\u003e). After calculating BMI for children, the BMI was plotted on the Indian Academy of Pediatrics (IAP) BMI-for-age growth charts to obtain a percentile ranking. A BMI of more than 23 adult-equivalent was classified as overweight and more than 27 adult-equivalent as obese\u003csup\u003e18\u003c/sup\u003e. Waist circumference (WC) was measured and central obesity was defined for the 10-16 years age group as WC of ≥90\u003csup\u003eth\u003c/sup\u003e percentile\u003csup\u003e19\u003c/sup\u003e or Indian adult WC cut-offs\u003csup\u003e20\u003c/sup\u003e if lower. For children older than 16 years of age WC was defined as per ethnicity-specific\u0026nbsp;values for adults (Indian men 90 cm and women 80 cm)\u003csup\u003e20\u003c/sup\u003e. Blood Pressure was\u0026nbsp;classified according to the American Academy of Pediatrics (AAP) updated guidelines as normal, elevated BP, stage 1 hypertension, and stage 2 hypertension using reference data specific for sex, age, and height\u003csup\u003e21\u003c/sup\u003e. The pubertal stage was determined based on Tanner’s standard photographs for pubic hair and genital development\u003csup\u003e22\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of analytes:\u0026nbsp;\u003c/strong\u003eBlood samples were obtained in the morning after fasting.\u0026nbsp;Fasting plasma glucose concentrations were determined by the hexokinase method in Olympus AU680 (Beckman Coulter). Impaired fasting glucose was defined as\u0026nbsp;≥100mg/dL\u003csup\u003e23\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e24\u003c/sup\u003e. Triglycerides and High-density Lipoprotein (HDL) were measured by the enzymatic colorimetric method in Olympus AU680 (Beckman Coulter). Elevated triglyceride levels were defined as ≥150mg/dL, and low HDL levels of \u0026lt;40mg/dL (for children \u0026gt;10 years only) were considered significant\u003csup\u003e23\u003c/sup\u003e.\u0026nbsp;The consensus\u0026nbsp;definition of metabolic syndrome\u0026nbsp;by the International diabetes federation (IDF) in 2007\u003csup\u003e23\u003c/sup\u003e was used for this study. This definition applies to children older than 10 years of age. Plasma insulin was determined by electrochemiluminescence assay (ECLIA, Roche Cobas e411). Insulin resistance (IR) was defined by fasting insulin level greater than 15μU/mL during prepuberty, 30μU/mL at puberty, and greater than 20μU/mL after puberty (Tanner stage I prepuberty, stage II-IV puberty, and stage V post-puberty)\u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBody composition assessment:\u0026nbsp;\u003c/strong\u003eA DXA\u0026nbsp;scan, using a HOLOGIC DISCOVERY DXA scanner\u0026nbsp;was used to assess the body composition of the survivors.\u0026nbsp;Primarily, the DXA scan provides an in-depth analysis of the main components of the body; fat, muscle, and bone. It provides the raw bone mineral content, fat mass, and lean mass content. Lean mass constitutes both soft tissue and muscle mass. Appendicular lean mass (part of lean mass) is more representative of the skeletal muscle mass of an individual. All the above masses were calculated in grams and presented after adjustment for the height (/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;as indices. The fat mass index (FMI) was Fat Mass (FM)/height\u003csup\u003e2\u003c/sup\u003e, the Lean Body Mass Index (LBMI) was Lean Body Mass (LBM)/height\u003csup\u003e2\u003c/sup\u003e, and the Skeletal muscle index (SMI), for this study, was defined as Appendicular Lean Body Mass (ALBM)/height\u003csup\u003e2\u003c/sup\u003e. Additional data gathered was percentage body fat, android/gynoid ratio, trunk to limb fat mass and percentage fat ratio. Percentiles were calculated for\u0026nbsp;total body fat percentage, FMI, and android/gynoid ratios (\u0026gt;85\u003csup\u003eth\u003c/sup\u003e percentile defined as increased cardiometabolic risk) in reference to Indian standards\u003csup\u003e26\u003c/sup\u003e.\u0026nbsp;Since Indian values for z-score estimation are not available, we used the\u0026nbsp;DXA whole-body dataset from the National Health and Nutrition Examination Survey (NHANES) population-based sample to calculate z-scores for these various indices\u003csup\u003e27\u003c/sup\u003e.\u0026nbsp;Sarcopenic obesity was defined as a positive (+) FM z-score along with a negative (-) appendicular LBM z-score in a particular individual\u003csup\u003e28\u003c/sup\u003e. Bone mineral density (BMD) was assessed using whole body (WB) DXA scan parameter and \u0026nbsp;low-BMD was considered when z-scores were\u0026lt;-2\u003csup\u003e29\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size:\u0026nbsp;\u003c/strong\u003eThe sample size for the study was calculated based on a previous study in India with a prevalence of sarcopenic obesity of 14%. With a 95% confidence interval, 10% precision, and 10% drop-out, a minimum of 53 patients were required for sequential sampling in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis:\u0026nbsp;\u003c/strong\u003eThe data was analyzed using STATA/SE 14.0 software. All qualitative variables were expressed as frequency (N, %). Normality was assessed using the Kolmogorov-Smirnov test. All quantitative variables were expressed as mean (±SD) for normally distributed data and median with interquartile range (IQR) for non-normally distributed data. A univariate logistic regression analysis was done to assess the association of sarcopenic obesity in cALL survivors with independent variables. Significant variables (considered as a p-value of \u0026lt;0.05) were included in the multivariable logistic regression along with age and gender. Additionally, an exploratory analysis was done, where we looked at body composition differences in variables that were significant in the multivariable analysis. Comparisons between continuous variables were performed with the Student’s t-test/Analysis of Variance (ANOVA) test if data was normally distributed, or the Wilcoxon rank-sum (Mann–Whitney U), if the data was skewed.\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eClinical, and metabolic profile of cALL survivors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe enrolled 65 consecutive survivors of cALL. None of them had pre-existing hypothyroidism, hypertension, deranged lipid profile, or diabetes diagnosed during treatment. The mean (\u0026plusmn;SD) age at enrolment was 12.9 (\u0026plusmn;3.2) years and the median (IQR) time since diagnosis was 6.5 (5.9;8) years. Among the survivors, 48 (74%) were male and 37 (57%) were between Tanner stage 2-4. The clinical details are provided in Table 1. Among the survivors, the mean (\u0026plusmn;SD) BMI was 19.1 (\u0026plusmn;3.2), and the median (IQR) BMI z-score was -0.14 (-1; 0.96). The metabolic evaluation of the survivors is given in Table 1. Metabolic syndrome was present in 11/53 (21%) survivors, and insulin resistance was seen in 15/65 (23.1%) cALL survivors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Clinical and Metabolic Profile of Survivors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult N (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eB-cell ALL\u003c/p\u003e\n \u003cp\u003eT-cell ALL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e55 (85)\u003c/p\u003e\n \u003cp\u003e10 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChemotherapy Protocol Used (\u003c/strong\u003e\u003cstrong\u003eN=65)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eINCTR\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eBFM\u003c/p\u003e\n \u003cp\u003eICiCLe\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38 (58)\u003c/p\u003e\n \u003cp\u003e5 (8)\u003c/p\u003e\n \u003cp\u003e22 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCranial Radiotherapy (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eProphylactic RT- 12.6 Gy\u003c/p\u003e\n \u003cp\u003eProphylactic RT- 18 Gy\u003c/p\u003e\n \u003cp\u003eCNS Leukemia- 18 Gy\u003c/p\u003e\n \u003cp\u003eCNS positive- 24 Gy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e43/65 (66)\u003c/p\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHSCT\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI categories (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eUnderweight \u0026lt;5\u003csup\u003eth\u003c/sup\u003e centile\u003c/p\u003e\n \u003cp\u003eNormal (5-23)\u003c/p\u003e\n \u003cp\u003eOverweight (23-27)\u003c/p\u003e\n \u003cp\u003eObese (\u0026gt;27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 (4.6)\u003c/p\u003e\n \u003cp\u003e42 (64.6)\u003c/p\u003e\n \u003cp\u003e10 (15.4)\u003c/p\u003e\n \u003cp\u003e10 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCentral Obesity (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e14 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage 1 \u0026amp; 2 Hypertension (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e12 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImpaired Fasting Glucose (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e12 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTriglycerides \u0026gt;150mg/dL (N=53)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e14 (26)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL \u0026lt;40mg/dL (N=53)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e21 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetabolic Syndrome (N=53)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e11 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51.5152%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsulin Resistance (N=65)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48.4848%;\"\u003e\n \u003cp\u003e15 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e*\u003c/em\u003e\u003cem\u003eALL: Acute Lymphoblastic Leukemia, INCTR:\u003c/em\u003e\u003cem\u003e\u0026nbsp;International Network for Cancer Treatment and Research\u003c/em\u003e\u003cem\u003e, BFM:\u0026nbsp;\u003c/em\u003e\u003cem\u003eBerlin Frankfurt Munster\u003c/em\u003e\u003cem\u003e, ICiCLe: \u003cem\u003eIndian Childhood Collaborative Leukemia Group\u003c/em\u003e, BMI: Body Mass Index, HSCT: Hematopoietic Stem Cell Transplant\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBody composition cALL survivors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBody composition was assessed by a DXA scan and is presented in Table 2.\u0026nbsp;Increased cardiometabolic risk, defined as\u0026nbsp;\u0026gt;85\u003csup\u003eth\u003c/sup\u003e percentile of total body fat percentage, FMI, and android/gynoid ratios was seen in 50%, 45%, and 26% respectively, and among them, BMI was normal in 44%, 34%, and 24% of survivors respectively. Interestingly, mean LBMI and SMI were also higher in overweight and obese as compared to survivors with normal BMI. Sarcopenic obesity was seen in 32% of survivors. Among the survivors with sarcopenic obesity, around half (47%) were overweight/obese and half had normal BMI or were underweight. The median BMD z-score was -0.95 (-1.85; -0.3), with 8/40 (20%) having low BMD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Body composition as derived by DXA scan\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFAT INDICES\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eTotal Body Fat % (Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e32.7 \u0026plusmn; 8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Body Fat \u0026gt;85\u003csup\u003eth\u003c/sup\u003e Percentile (N, %)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e32/65, 50\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e14/32, 44\u003c/p\u003e\n \u003cp\u003e8/32, 25\u003c/p\u003e\n \u003cp\u003e10/32, 31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eFat Mass Index (Median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e5.27 (4.1;8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFat Mass Index \u0026gt;85\u003csup\u003eth\u003c/sup\u003e Percentile (N, %)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29/65, 45\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e10/29, 34\u003c/p\u003e\n \u003cp\u003e9/29, 32\u003c/p\u003e\n \u003cp\u003e10/29, 34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eAndroid/Gynoid ratio (Mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e0.89 \u0026plusmn; 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAndroid/Gynoid ratio \u0026gt;85\u003csup\u003eth\u003c/sup\u003e Percentile (N, %)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17/65, 26\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e4/17, 24\u003c/p\u003e\n \u003cp\u003e4/17, 24\u003c/p\u003e\n \u003cp\u003e9/17, 52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eTrunk to Limb Fat mass ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e0.85 \u0026plusmn; 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrunk to Limb Fat mass ratio in\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e1.0 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e1.0 \u0026plusmn; 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.1\u003c/p\u003e\n \u003cp\u003e0.9 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eTrunk to Limb Percentage Fat ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e0.84 \u0026plusmn; 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrunk to Limb Percentage Fat ratio in\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.1\u003c/p\u003e\n \u003cp\u003e0.9 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e1.0 \u0026plusmn; 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.8 \u0026plusmn; 0.1\u003c/p\u003e\n \u003cp\u003e0.9 \u0026plusmn; 0.1\u003c/p\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMUSCLE INDICES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eLean Body Mass Index (Mean \u0026plusmn; SD)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e12.8 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLean Body Mass Index (Mean \u0026plusmn; SD) in\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e11.9 \u0026plusmn; 2.0\u003c/p\u003e\n \u003cp\u003e14.0 \u0026plusmn; 2.3\u003c/p\u003e\n \u003cp\u003e18.2 \u0026plusmn; 6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e10.7 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e12.2 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eSkeletal Muscle Index (Mean \u0026plusmn; SD)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e5.5 \u0026plusmn; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkeletal Muscle Index (Mean \u0026plusmn; SD) in\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e5.2 \u0026plusmn; 1.1\u003c/p\u003e\n \u003cp\u003e6.1 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e8.2 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e4.3 \u0026plusmn; 0.6\u003c/p\u003e\n \u003cp\u003e4.8 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ-SCORES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eFat mass z-score (Median (IQR))\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e-0.1 (-0.7;0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003eAppendicular lean mass z-score\u0026nbsp;(Median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e-1.3 (-2.2; -0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 57%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSarcopenic Obesity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNormal BMI\u003c/p\u003e\n \u003cp\u003eOverweight BMI\u003c/p\u003e\n \u003cp\u003eObese BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 42%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21/65 (33%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e10/21 47\u003c/p\u003e\n \u003cp\u003e5/21, 24\u003c/p\u003e\n \u003cp\u003e6/21, 29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegression analysis for association of Sarcopenic obesity and various demographic, metabolic, and treatment-associated variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVariables including demographic and treatment-related risk factors, younger age at diagnosis, longer time since diagnosis, female gender, baseline immunophenotype, presence of overweight/obesity, central obesity, insulin resistance, the radiation received, cumulative doses of prednisolone and other chemotherapeutic agents were included in the regression model (Table 3, presented as (OR, (95% CI), p-value)). Age at diagnosis (0.95 (0.92-0.98), p=0.02), central obesity (18.99 (2.32-155.5), p=0.006) and insulin resistance (10.2 (1.75-59.09), p=0.01) were associated with the presence of sarcopenic obesity, while treatment-related variables, did not have a direct impact.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Association between Sarcopenic obesity and various demographic, metabolic, and treatment-associated variables\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 30%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSarcopenic Obesity Unadjusted Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable model (adjusted for age and gender)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI, p-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003eFemale Sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.24 (0.38-4.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYounger age at diagnosis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.98 (0.96-0.99)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.95 (0.92-0.98), 0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime since diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.03 (1.01-1.05)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 34%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverweight/Obese\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.53 (1.43-14.38)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCentral Obesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.40 (1.51-19.29)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.99 (2.32-155.49), 0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsulin Resistance\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.41 (2.2-32.14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.2 (1.75-59.09), 0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003eLow BMD z-score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.14 (0.29-4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 34%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003eCranial Radiation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e0.83 (0.27-2.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003ePrednisolone Equivalent (mg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.00 (0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003eDoxorubicin(mg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.00 (0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003eCyclophosphamide (mg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.00 (0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35%;\"\u003e\n \u003cp\u003eL-Asparaginase (U/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.00 (0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10%;\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBody composition distribution in the significant variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of our exploratory analysis on the body composition distribution in the variables that were significant in the multivariable logistic regression analysis are given in Table 4. In survivors with insulin resistance and central obesity, there was a significantly higher fat composition (higher FMI) with similar to increased proportion of muscle composition. On the contrary, patients younger than 5 years at diagnosis had a significantly lower muscle composition (lower LBMI and skeletal muscle mass index), with similar fat composition (FMI), compared to older survivors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Distribution of body composition in the significant variables in the regression analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 28%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFat Mass/Height\u003csup\u003e2\u003c/sup\u003e, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Median (IQR))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLean Mass/Height\u003csup\u003e2\u003c/sup\u003e, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAppendicular Lean Mass/Height\u003csup\u003e2\u003c/sup\u003e, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u0026lt;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e5.0 (4.1-7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e11.5\u0026nbsp;\u0026plusmn; 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e4.8\u0026nbsp;\u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u0026gt;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e6.2 (4.1-9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e14.2\u0026nbsp;\u0026plusmn; 4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e6.3\u0026nbsp;\u0026plusmn; 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsulin Resistance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e9.0 (6.4-12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e13.4\u0026nbsp;\u0026plusmn; 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e5.6\u0026nbsp;\u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e4.89 (3.7-6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e12.6\u0026nbsp;\u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e5.5\u0026nbsp;\u0026plusmn; 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCentral Obesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e10.3 (9.2-13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e16.4\u0026nbsp;\u0026plusmn; 6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e7.3\u0026nbsp;\u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e4.9 (3.7-6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e11.8\u0026nbsp;\u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e5.1\u0026nbsp;\u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe prevalence of sarcopenic obesity in this group of predominantly adolescent survivors of cALL, more than 2 years from treatment completion, was 34%. Other groups have shown a prevalence of sarcopenia and sarcopenic obesity to vary between 4 to 43%\u003csup\u003e28,31–33\u003c/sup\u003e. These studies mainly included adult survivors of childhood cancer from high-income countries with varying definitions of sarcopenic obesity. In a similar study from North India, sarcopenic obesity was seen in 14% of adolescent survivors of childhood cancer. They used body fat percentage and lean body mass criteria to define sarcopenic obesity\u003csup\u003e30\u003c/sup\u003e. Even though their group of survivors had a similar body fat percentage (35.2% vs 32%) and LBMI (12.3 vs 12.8%) to our group, the prevalence of sarcopenic obesity was half of that seen in our population. Hence it is important to have standardized definitions for sarcopenic obesity, which can be easily replicated in our clinics to generate data and assess the true magnitude of the problem. For our study, we used a simple definition for sarcopenic obesity defined previously as a positive fat mass z-score along with a negative appendicular lean body mass z-score\u003csup\u003e9\u003c/sup\u003e. These simple variables, retrievable from a whole-body DXA scan, gave us an overview of the problem and this definition was used previously in a study analyzing sarcopenic obesity in childhood ALL survivors\u003csup\u003e9\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere is limited data on body adiposity in healthy Indian children and adolescents. In our study, more than\u0026nbsp;85\u003csup\u003eth\u003c/sup\u003e percentile\u0026nbsp;of\u0026nbsp;total body fat percentage, FMI, and android/gynoid ratios\u0026nbsp;was seen in 50%, 45%, and 26% respectively, indicating those at increased\u0026nbsp;risk for Metabolic Syndrome\u003csup\u003e26\u003c/sup\u003e. \u0026nbsp;A large proportion of these patients had a normal BMI.\u0026nbsp;They also had a much lower skeletal muscle index when compared to values reported in another study from our institute on non-cancer children and adolescents from New Delhi (Males: Normal BMI- 8.2 vs 5.2, Overweight- 9.4 vs 6.1, Obese- 9.4 vs 8.2; Females: Normal BMI- 6.5 vs 4.3, Overweight- 7.7 vs 4.8, and 8.1 vs 5.8\u003csup\u003e34\u003c/sup\u003e)\u003csup\u003e34\u003c/sup\u003e. Similarly, in our study, sarcopenic obesity occurs in close to 50% of survivors with a normal BMI. This signifies that a significant proportion of cancer survivors in the study are at an increased risk for cardiometabolic late effects, despite having a normal BMI. This indicates that body composition, specifically high body fat percentage and android/gynoid ratios, may be more important indicators of metabolic health than BMI alone in this population. Additionally, the lower skeletal muscle index in these patients compared to non-cancer children and adolescents suggests potential muscle wasting or loss, which can also impact metabolic health and overall well-being.\u0026nbsp;Hence sarcopenic obesity may be overlooked unless actively screened for, leading to an underestimation of the problem. The prevalence of sarcopenic obesity is closely linked with the prevalence of frailty (limitations in physical performance/poor fitness\u0026nbsp;or simply premature aging) because of a similar underlying pathophysiology\u003csup\u003e31,35,36\u003c/sup\u003e. With the increase in the number of childhood cancer survivors living into adulthood, a subset of them will be at risk for both sarcopenic obesity and frail health, which may ultimately lead to a poor quality of life\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFrom our regression model,\u0026nbsp;age at diagnosis, central obesity, and insulin resistance were associated with the presence of sarcopenic obesity, while treatment-related variables, did not have a direct impact. Male sex, cranial irradiation, HSCT, and age at diagnosis are variables that have been reported to be associated with sarcopenic obesity\u003csup\u003e31–33\u003c/sup\u003e. Previous studies have not reported the association of central obesity or insulin resistance with sarcopenic obesity in childhood cancer survivors. Our exploratory analysis found that patients with central obesity and insulin resistance had a greater increase in fat mass compared to muscle mass. This trend has also been observed in obese children without cancer\u003csup\u003e34\u003c/sup\u003e. The associations between central obesity, insulin resistance, and high muscle and fat mass are novel findings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, we also found that children diagnosed at a younger age had an increased association with sarcopenic obesity and they had lower lean and appendicular mass with similar fat mass compared to older patients at diagnosis. Muscle has a variety of functions including movement, glucose, and amino acid homeostasis and\u0026nbsp;protection of other organs against trauma\u003csup\u003e7\u003c/sup\u003e.\u0026nbsp;Hence, poor muscle health is an indicator of metabolic disease, eventually leading to chronic morbidity and mortality\u003csup\u003e38,39\u003c/sup\u003e. There is\u0026nbsp;emerging data on the long-term effects of childhood leukemia treatment on muscle health\u003csup\u003e40–45\u003c/sup\u003e. Based on our results it can be hypothesized that younger children, when exposed to chemo- or radiotherapy, are at a greater risk of reduction in muscle health, which in turn may lead to adverse long-term muscle-related late effects.\u003c/p\u003e\n\u003cp\u003eOur study on sarcopenic obesity in young cALL survivors\u0026nbsp;bears all the limitations of\u0026nbsp;a cross-sectional study. It focused on metabolic late effects and used only muscle and fat mass criteria for sarcopenic obesity.\u0026nbsp;Additional assessment of muscle function would have added to the validity of our results.\u0026nbsp;A large proportion of the cohort received cranial radiation, limiting generalizability. However, they do contribute to a large proportion of childhood leukemia survivors, especially in low-middle-income countries like India. Confidence intervals in the regression analysis are wide and\u0026nbsp;should be interpreted with caution. Most importantly, normative data for DXA-derived body adiposity variables are not available for growing children and adolescents. We have compared results among subgroups and to other studies whenever possible. Limitations notwithstanding, this data can be used for larger studies on muscle health in cALL survivors, guiding future trials and rehabilitative interventions.\u003c/p\u003e\n\u003cp\u003eTo conclude, sarcopenic obesity in adolescent survivors of cALL is an early clinical indicator of metabolic disease. Factors such as age at diagnosis, central obesity, and insulin resistance were associated with sarcopenic obesity in this group, highlighting the complex interplay of various risk factors. Given that muscle development occurs early in life, a time when childhood cancer patients are exposed to aggressive therapy, they are at risk for early decline in muscle health that may contribute to adverse outcomes later in life. Rehabilitative interventions should be targeted earlier in survivorship to improve the health and overall quality of life of our growing cALL survivor population.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAbbreviation\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eFull Form\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003ecALL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eChildhood ALL\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAPLBM\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eAppendicular Lean Body Mass\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBMC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eBone Mineral Content\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBMD\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eBone Mineral Density\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eBMI\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eBody Mass Index\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCNS\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCentral nervous system\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCRT\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eCranial Radiotherapy\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eDXA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eDual-Energy Xray Absorptiometry\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eECLIA\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eElectrochemiluminescence assay\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eFMI\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eFat Mass Index\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHDL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eHigh density lipoprotein\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHOMA-IR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eHomeostatic Model Assessment of Insulin Resistance\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eHSCT\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eHematopoietic stem cell transplant\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIAP\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eIndian Academy of Pediatrics\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eICiCLe\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eIndian Childhood Collaborative Leukemia\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIDF\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eInternational diabetes federation\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eInPOG\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eIndian Pediatric Oncology Group\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eINCTR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eInternational Network for Cancer Treatment and Research protocol\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eIR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eInsulin Resistance\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLAR\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eLeptin to Adiponectin Ratio\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLBM\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eLean Body Mass\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLBMI\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eLean Body Mass Index\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eLDL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eLow Density Lipoprotein\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eNHANES\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eNational Health and Nutrition Examination Survey\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eSMI\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSkeletal Muscle Index\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eVLDL\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eVery Low-Density Lipoprotein\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eWC\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eWaist circumference\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u003c/strong\u003e All authors contributed to the study\u0026apos;s conception and design. Gargi Das, Kritika Setlur, and Rachna Seth performed material preparation, data collection, and analysis. Final Data analysis and interpretation were performed by Gargi Das, Sadanand Dwivedi, Aditya Gupta, and Jagdish Prasad Meena. DXA scans and laboratory tests were performed and interpreted by Manisha Jana, Lakshmy Ramaswamy, and Vandana Jain. The first draft of the manuscript was written by Gargi Das and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe datasets generated during and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics:\u0026nbsp;\u003c/strong\u003eThe research was conducted per the ethical guidelines laid down by the Helsinki Declaration. Ethics approval was taken by the institute ethics committee of the All-India Institute of Medical Sciences vide Ref no.: IECPG-628/28.11.2019, RT-08/19.12.2019.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u0026nbsp;\u003c/strong\u003eWritten informed consent was obtained from the parents and children provided assent (verbal and written) wherever necessary.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSantilli V, Bernetti A, Mangone M, Paoloni M. Clinical definition of sarcopenia. Clin Cases Miner Bone Metab Off J Ital Soc Osteoporos Miner Metab Skelet Dis. 2014;11(3):177\u0026ndash;180.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaracos VE, Arribas L. Sarcopenic obesity: hidden muscle wasting and its impact for survival and complications of cancer therapy. 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Pediatr Rehabil. 2006;9(3):267\u0026ndash;274. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13638490500523150\u003c/span\u003e\u003cspan address=\"10.1080/13638490500523150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"Sarcopenic Obesity, Adiposity, Acute lymphoblastic leukemia, Survivor","lastPublishedDoi":"10.21203/rs.3.rs-4889834/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4889834/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eSarcopenic obesity, characterized by increased adiposity with low skeletal muscle mass, contributes to frailty and the development of chronic disease. Data on sarcopenic obesity in survivors of childhood acute lymphoblastic leukemia (cALL) is limited.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology: \u003c/strong\u003eA cross-sectional study on 65 cALL survivors (7-18 years, \u0026gt;2 years from treatment completion) was conducted on cALL survivors with the primary outcome to determine the prevalence of sarcopenic obesity. Sarcopenic obesity was defined as patients with a positive Fat Mass (FM) z-score with a negative Appendicular Lean Body Mass (APLBM) z-score, measured using Dual-Energy Xray Absorptiometry (DXA) scan. In addition, we assessed the factors associated with sarcopenic obesity by multivariable regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The mean (±SD) age was 12.9 (±3.2) years, the median (Interquartile Range) time since diagnosis was 6.5 (5.9;8) years, and 66% received cranial radiotherapy. Central obesity, insulin resistance, and metabolic syndrome were seen in 21.5%, 23.1%, and 21% respectively. DXA-derived body composition variables revealed higher fat percentage despite normal body mass index (BMI) and lower muscle mass compared to the general population. Sarcopenic obesity was seen in 21 (32%) of survivors. On multivariable regression analysis, age at diagnosis (OR: 0.95 (95% CI: 0.92-0.98), p=0.02), central obesity (OR: 18.99 (95% 2.32-155.5), p=0.006) and insulin resistance (OR: 10.2 (95% CI: 1.75-59.09), p=0.01) were associated with sarcopenic obesity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions and Implications for cancer survivors\u003c/strong\u003e: Sarcopenia, an early clinical indicator for metabolic disease despite normal BMI, was significantly worse in children diagnosed with ALL at a younger age and was associated with central obesity and insulin resistance, which may contribute to adverse outcomes later in life.\u003c/p\u003e","manuscriptTitle":"Sarcopenic Obesity in Survivors of Childhood Acute Lymphoblastic Leukemia: Prevalence, Risk Factors, and Implications for Cancer Survivors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-10 13:46:20","doi":"10.21203/rs.3.rs-4889834/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-10T15:56:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-10T00:08:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-01T15:40:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173545084502373157640230406886369348656","date":"2024-09-27T13:07:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134873414082843730055702236770397998800","date":"2024-09-26T15:33:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-26T14:19:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-22T15:21:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-13T04:44:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2024-08-10T03:55:47+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":"9bffc6c2-e70c-44c7-ad3a-f574db76db89","owner":[],"postedDate":"November 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T17:24:55+00:00","versionOfRecord":{"articleIdentity":"rs-4889834","link":"https://doi.org/10.1007/s00520-024-09025-w","journal":{"identity":"supportive-care-in-cancer","isVorOnly":false,"title":"Supportive Care in Cancer"},"publishedOn":"2024-11-26 15:57:48","publishedOnDateReadable":"November 26th, 2024"},"versionCreatedAt":"2024-11-10 13:46:20","video":"","vorDoi":"10.1007/s00520-024-09025-w","vorDoiUrl":"https://doi.org/10.1007/s00520-024-09025-w","workflowStages":[]},"version":"v1","identity":"rs-4889834","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4889834","identity":"rs-4889834","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}