Nutritional Intervention in Acute Lymphoblastic Leukemia (ALL)

Effect of a Food-based Nutrition Intervention on Body Composition of Children and Adolescents Diagnosed With Acute Lymphoblastic Leukemia (2-14 y)

International Atomic Energy Agency, Hospital Civil de Guadalajara, Centro de Investigación en Alimentación y Desarrollo A.C.

Introduction: Annually 400,000 children are diagnosed with cancer in the world. Approximately 90% live in low/middle-income countries, with survival rates of 10-30%. In Mexico, children and adolescents' hospital admissions for cancer are mainly leukemias (46%), being acute lymphoblastic leukemia (ALL) the most common. Half of ALL patients have an altered nutritional status at the time of diagnosis. Nutritional assessment is performed using conventional anthropometric measures, which are not sensitive to changes in fat-free mass and fat mass (FFM and FFM). Our objective is to evaluate the effect of an individualized food-based nutritional intervention according to the nutritional status, body composition and comorbidities in pediatric patients with ALL. This is a pre-test/post-test clinical trial. Children 2-14 y olds diagnosed with ALL and in the remission stage (4-6 weeks post-diagnosis) will participate. The nutritional status will be evaluated using questionnaires and body composition. The intervention will be a 6 mo individualized food-based nutrition plan changing meal plans every 2 wk; every plan provides 5 interchangeable meals, adapting to personal preferences and symptoms related to antineoplastic treatment (nausea, diarrhea, taste alteration, etc.). For hospitalized patients, the options offered by the hospital will be evaluated and adapted to the nutritional intervention. Effectiveness of the intervention will be assessed using a paired test dependant on the distribution of the data.

JUSTIFICATION Nutritional assessment of cancer patients is usually performed using conventional anthropometric techniques, which are not sensitive to short-term changes and do not reflect changes in the FFM, FM, and hydration status. Assessing body composition using a reference technique such as deuterium oxide dilution (DOD), and also using field methods (BIA and anthropometry), which are more accessible in clinical practice, can detect short-term changes in children and adolescents with ALL. In cancer patients, protein and muscle stores are frequently affected; an increase in FM and a decrease in FFM were observed within the first 6 months of antineoplastic treatment. The DOD technique identifies three compartments (total body water, FFM, and FM). Similar changes in body composition are seen in patients with breast cancer; the work carried out by Limón-Miró et al; where it was observed that an individualized nutritional intervention preserved FFM while reducing FM, both associated with quality of life and survival in breast cancer patients. This highlights the importance of a specialized nutritional intervention in the comprehensive treatment of cancer patients; in children and adolescents with ALL, monitoring body composition combined with a nutrition intervention, could reduce the deterioration of FFM and provide a window to assess prognosis, clinical outcome, and survival of ALL pediatric patients in remission. HYPOTHESES An individualized food-based nutritional intervention for 6 months in pediatric patients with ALL in remission: Promotes maintenance and improvement of the FFM Promotes the normalization of FM Will show differences in body composition in children with ALL, before and after nutritional intervention GENERAL OBJECTIVE To assess the impact of an individualized food-based nutritional intervention (6 months) on the body composition of children diagnosed with ALL. SPECIFIC OBJECTIVES To assess the nutritional status of children diagnosed with ALL based on anthropometric and dietary indicators before and after 6 months of individualized nutritional intervention. To evaluate fat mass and fat-free mass using reference and field techniques, before and after 6 months of individualized nutritional intervention in minors diagnosed with ALL. To analyze the change in body composition after 6 months of individualized nutritional intervention in minors diagnosed with ALL. To establish a protocol on nutritional monitoring of patients with acute lymphoblastic leukemia that can be applied in clinical practice. To monitor body composition in the medium term (3 years) and associate it with quality of life variables. METHODOLOGY Study design This is a clinical trial with a pre-test/post-test design. Children from 2 to 14 years old with a diagnosis of Acute Lymphoblastic Leukemia (ALL) in remission stage (4 - 6 weeks) from two areas of Mexico (Hermosillo, Sonora / Guadalajara, Jalisco) will participate. Sample size: To determine the sample size, we will work on the assumptions of a standard deviation (SD) of Fat-Free Mass (FFM) of 2.19 Kg, with a Variance of 4.8 Kg, a Zα of 1.96 for a p = 0.05, with a mean difference (Ԁ) of 1 Kg. The sample size was calculated considering the Beta error of 20% (B = 0.84), depending on the availability of the number of patients who agreed to participate, as well as those excluded by established criteria. Based on the data mentioned, the estimated sample size calculation is 38 participants, as detailed in the following equation. N = ((Zα + Zβ) ^ 2 〖(DE)〗 ^ 2) / 〖(d)〗 ^ 2 = 38 participants Clinical record: The principles of the Official Mexican Norm (NOM) NOM-024-SSA3-201 will be followed, which establishes the functional objectives and functionalities that must be followed in the use of electronic clinical records. For this purpose, a confidential file number will be assigned, so that when analyzing the biological samples or data collected in the field, no access will be given to the names, address, telephone number, or related information that may be exposed to the participant. Screening: Predictive screening will be used for the "Nutrition Screening Tool For Childhood Cancer (SCAN)" which consists of 6 questions. This tool identifies the need for a nutritional intervention according to the symptoms of the patients who classify at risk of malnutrition. Screening should be applied to all study subjects at each consultation or weekly to patients who are hospitalized since they are at high risk of malnutrition at the time of diagnosis and increases in the stages of treatment. The Lansky pediatric scale will also be applied, which allows evaluating the general condition of the patient, representing the degree of autonomy in the activities of daily life. In addition, the PedsQL Cancer Module © will be used, which is derived from the Pediatric Quality of Life Questionnaire (PedsQL), which is a generic instrument designed for children and parents to assess the quality of life as a self-report. Dietary evaluation: The ENSANUT frequency questionnaire will be applied for the respective age groups: preschoolers, schoolchildren, and adolescents. Anthropometry Weight and height: Body weight will be measured (electronic scale with 0.150 + 0.05 kg scales) or child scale (0-20 kg). Height will be measured by SECA stadiometers or infantometers, as required to the nearest 0.1 cm. Mid-upper arm circumference (MUAC): This measure allows the identification of malnutrition in children under 5 years of age without taking weight, height, and age, by measuring the arm circumference at its midpoint. Tricipital skinfold (TSF): With the participant standing, with the feet together, the shoulders relaxed and the arms hanging relaxed at the sides. The examiner will stand on the right side of the patient and place the top point on the back surface of the arm in the same area as the midpoint marked for the arm circumference. The skin fold of the skin and subcutaneous adipose tissue will be gently grasped with the thumb and index finger, approximately 1.0 cm above the point where the skin was scored, with the skin fold parallel to the longitudinal axis of the upper arm. The jaws of the calipers will be placed at the level that the skin was marked, these should be positioned perpendicular to the length of the fold. The skinfold will be held gently and the skinfold thickness will be measured to the nearest 1mm. Waist circumference (WC): The waist circumference will be measured with a retractable tape at the level of the umbilical scar in a standing position and after exhaling. All measurements will be processed by the Anthro software of the World Health Organization, for the calculation of nutritional indices such as Z score of weight/age, height/age, and weight/height in children <60 months, BMI-age- sex, and height/age in children> 60 months. A physical examination will be performed to observe signs of malnutrition (loss of subcutaneous fat, muscle wasting, edema, etc.). Body composition Deuterium oxide dilution: Total body water will be measured by dilution of deuterium oxide (DOD) using isotope ratio mass spectrometry with a urine sample. Our laboratory has reduced the dose necessary to obtain the enrichment of> 800 ppm in children and adults, which is 0.2 g of deuterium/kg of body weight, an amount that does not represent a risk for minors. The measurement will be taken once the patient has gone to the bathroom, sterile material will be used taking care of the cleanliness and safety of the personnel in charge of the measurement. A pre-dose urine sample will be taken, once the dose is calculated by the patient's weight, the DOD plus 50 ml of natural water will be administered, this should be taken with a straw to avoid spilling the dose. After 4 hours, a post-dose urine sample will be taken, at the time of calculation, it will be taken into account if the patient ingested extra fluids. Urine samples will be analyzed using isotope ratio mass spectrometry to obtain the values of deuterium spaces, total body water and calculate the FFM and FM. Electrical bioimpedance (BIA): BIA is considered a simple, fast, and non-invasive technique that allows the estimation of total body water (TBW), fat-free mass (FFM), and, by difference, fat mass (FM). The patient must be in the supine position at the time of measurement for at least 5 minutes before starting. 4 electrodes will be placed on its left ends, two on the hand and two on the foot, 5 cm away from each other, a current of 50 mHz is administered, then a resistance and reactance reading is taken to obtain the result of the test. impedance, following the standardized methodology. For the study population, it is proposed to use the equation validated in the child population proposed by Ramírez E., et al. In this way, when knowing the FFM, the FM will be estimated by difference with the total body weight. FFM(kg) = 0.661 x Ht2 / R + 0.200 x Wt - 0.320 Where Ht is height in cm squared, R is resistance, and Wt is weight in kg. Individualized nutritional intervention After the diagnosis of ALL is established, an individualized food-based nutritional plan will be given to study patients. The dietary intervention will be developed based on the nutritional status of the patients, habits, schedule, activities, cultural preferences since all these characteristics are critical factors that determine adherence to the nutritional plan. Currently, there are no standardized protocols for the nutritional management of patients with acute lymphoblastic leukemia in Mexico. Some articles propose levels that are necessary to achieve or maintain, such as weight/age Z-score between -2 and 2, <30% fat/day (mainly monounsaturated and polyunsaturated fatty acids), 55 - 60% carbohydrates ( whole grains), we propose to use 1 - 1.5 g of protein/kg/day depending on the age of the patient. If excess weight / fat mass is detected, a mild calorie restriction will be evaluated. Every two weeks a new 7-day meal plan will be provided with 5 interchangeable meals per day. At each visit, they will be asked about food intake, percentage of adherence to the nutritional plan, modifications, symptoms related to treatment (nausea, diarrhea, alteration in taste, etc.). For hospitalized patients, the options offered by the hospital will be evaluated and adapted to the intervention. Statistic analysis Descriptive statistics will be used using NCSS v11. To evaluate the effectiveness of the intervention, the t-student test or non-parametric tests will be performed depending on the distribution of the data. For BIA an algorithm will be used to predict total body water for the calculation of FFM and FM compared to the results of dilution with deuterium. Intention-to-treat analysis will also be performed, which should be seen more as a global strategy for the design, execution, and analysis of clinical trials, rather than solely as an alternative analysis. It is the recommended strategy, especially in pragmatic trials. The intention-to-treat analysis gives an estimate of the benefit of a treatment closer to daily practice (effectiveness).

Clinical trial with a pre-test/post-test design. Intervention group: Children and adolescents between 2 and 14 years old with a diagnosis of ALL in the remission stage who agree to participate in the project with the approval of their legal guardian. Control group: Being a pre-test/post-test design, the same child will be the control at the end of the intervention. Additionally, children without ALL of the same age and sex will be taken as reference. The potential of including paired measurements against healthy children for external control is analyzed.

Masking during data analysis. Technicians and investigators will not be aware of the participants personal data and particularities.

As it is a pre-test / post-test design, the child himself will be the control at the end of the intervention. Additionally, children without ALL of the same age and sex will be taken as reference. The potential of including paired measurements against healthy children for external control is analyzed.

Pre-test / post-test clinical trial. Children aged 2-14 years in the remission stage of ALL (4-6 weeks post-diagnosis) will participate. The nutritional status will be evaluated using a diagnostic questionnaire (SCAN), habitual diet (ENSANUT consumption frequency questionnaire) and body composition (dilution with deuterium oxide, electrical bioimpedance and anthropometry). Subsequently, an individualized nutritional plan will be implemented for 6 months with the following distribution of nutrients: <30% fat / day, 55-60% carbohydrates and 1-1.5 g protein / kg / day. Every two weeks a new 7-day eating plan will be provided with 5 interchangeable meals, adapting to food intake, percentage of adherence to the nutritional plan, modifications and symptoms related to treatment (nausea, diarrhea, taste alteration, etc.). For hospitalized patients, the options offered by the hospital will be evaluated and adapted to the intervention.

Inclusion Criteria: Patients in remission stage (4 - 6 weeks) Life expectancy> 6 months and sufficient general conditions according to scales (Lansky ≥ 50 points for children <16 years) Histopathological/molecular clinical confirmation of the ALL diagnosis Signature of the consent by the relative or legal guardian of the patient and as well as the consent informed by the patient. Exclusion Criteria: Pathological conditions that can alter body composition (diabetes, hypothyroidism, among others) Patients with sepsis that causes hemodynamic compromise and cannot be evaluated Severely ill patients unable to participate in baseline measurements Relapsed patients Patients with developmental problems of a genetic order as well as innate errors of metabolism

Ward EJ, Henry LM, Friend AJ, Wilkins S, Phillips RS. Nutritional support in children and young people with cancer undergoing chemotherapy. Cochrane Database Syst Rev. 2015 Aug 24;2015(8):CD003298. doi: 10.1002/14651858.CD003298.pub3.

Cohen JE, Wakefield CE, Cohn RJ. Nutritional interventions for survivors of childhood cancer. Cochrane Database Syst Rev. 2016 Aug 22;2016(8):CD009678. doi: 10.1002/14651858.CD009678.pub2.

Francis DK, Smith J, Saljuqi T, Watling RM. Oral protein calorie supplementation for children with chronic disease. Cochrane Database Syst Rev. 2015 May 27;2015(5):CD001914. doi: 10.1002/14651858.CD001914.pub2.

Ladas EJ, Orjuela M, Stevenson K, Cole PD, Lin M, Athale UH, Clavell LA, Leclerc JM, Michon B, Schorin MA, Welch JG, Asselin BL, Sallan SE, Silverman LB, Kelly KM. Dietary intake and childhood leukemia: The Diet and Acute Lymphoblastic Leukemia Treatment (DALLT) cohort study. Nutrition. 2016 Oct;32(10):1103-1109.e1. doi: 10.1016/j.nut.2016.03.014. Epub 2016 Mar 28.

Ramirez E, Valencia ME, Moya-Camarena SY, Aleman-Mateo H, Mendez RO. Four-compartment model and validation of deuterium dilution technique to estimate fat-free mass in Mexican youth. Nutrition. 2009 Feb;25(2):194-9. doi: 10.1016/j.nut.2008.08.007. Epub 2008 Oct 23.

Yang HR, Choi HS. A prospective study on changes in body composition and fat percentage during the first year of cancer treatment in children. Nutr Res Pract. 2019 Jun;13(3):214-221. doi: 10.4162/nrp.2019.13.3.214. Epub 2019 Mar 13.

De Palo T, Messina G, Edefonti A, Perfumo F, Pisanello L, Peruzzi L, Di Iorio B, Mignozzi M, Vienna A, Conti G, Penza R, Piccoli A. Normal values of the bioelectrical impedance vector in childhood and puberty. Nutrition. 2000 Jun;16(6):417-24. doi: 10.1016/s0899-9007(00)00269-0.

Cameron N. Essential anthropometry: Baseline anthropometric methods for human biologists in laboratory and field situations. Am J Hum Biol. 2013 May-Jun;25(3):291-9. doi: 10.1002/ajhb.22388. No abstract available.

Jones PJ, Leatherdale ST. Stable isotopes in clinical research: safety reaffirmed. Clin Sci (Lond). 1991 Apr;80(4):277-80. doi: 10.1042/cs0800277.

Abrams SA. Assessing mineral metabolism in children using stable isotopes. Pediatr Blood Cancer. 2008 Feb;50(2 Suppl):438-41; discussion 451. doi: 10.1002/pbc.21417.

Wauben IP, Atkinson SA, Bradley C, Halton JM, Barr RD. Magnesium absorption using stable isotope tracers in healthy children and children treated for leukemia. Nutrition. 2001 Mar;17(3):221-4. doi: 10.1016/s0899-9007(00)00507-4.

Egnell C, Ranta S, Banerjee J, Merker A, Niinimaki R, Lund B, Mogensen PR, Jonsson OG, Vaitkeviciene G, Lepik K, Forslund A, Heyman M, Harila-Saari A. Impact of body mass index on relapse in children with acute lymphoblastic leukemia treated according to Nordic treatment protocols. Eur J Haematol. 2020 Dec;105(6):797-807. doi: 10.1111/ejh.13517. Epub 2020 Sep 20.

Brinksma A, Roodbol PF, Sulkers E, Kamps WA, de Bont ES, Boot AM, Burgerhof JG, Tamminga RY, Tissing WJ. Changes in nutritional status in childhood cancer patients: a prospective cohort study. Clin Nutr. 2015 Feb;34(1):66-73. doi: 10.1016/j.clnu.2014.01.013. Epub 2014 Jan 23.

Chincesan MI, Marginean CO, Voidazan S. Assessment of Body Composition in a Group of Pediatric Patients With Cancer: A Single Romanian Center Experience. J Pediatr Hematol Oncol. 2016 Oct;38(7):e217-22. doi: 10.1097/MPH.0000000000000586.

Jaime-Perez JC, Gonzalez-Llano O, Herrera-Garza JL, Gutierrez-Aguirre H, Vazquez-Garza E, Gomez-Almaguer D. Assessment of nutritional status in children with acute lymphoblastic leukemia in Northern Mexico: A 5-year experience. Pediatr Blood Cancer. 2008 Feb;50(2 Suppl):506-8; discussion 517. doi: 10.1002/pbc.21397.

Beer SS, Juarez MD, Vega MW, Canada NL. Pediatric Malnutrition: Putting the New Definition and Standards Into Practice. Nutr Clin Pract. 2015 Oct;30(5):609-24. doi: 10.1177/0884533615600423. Epub 2015 Sep 1.

Martinez EE, Smallwood CD, Quinn NL, Ariagno K, Bechard LJ, Duggan CP, Mehta NM. Body Composition in Children with Chronic Illness: Accuracy of Bedside Assessment Techniques. J Pediatr. 2017 Nov;190:56-62. doi: 10.1016/j.jpeds.2017.07.045.

den Hoed MA, Pluijm SM, de Groot-Kruseman HA, te Winkel ML, Fiocco M, van den Akker EL, Hoogerbrugge P, van den Berg H, Leeuw JA, Bruin MC, Bresters D, Veerman AJ, Pieters R, van den Heuvel-Eibrink MM. The negative impact of being underweight and weight loss on survival of children with acute lymphoblastic leukemia. Haematologica. 2015 Jan;100(1):62-9. doi: 10.3324/haematol.2014.110668. Epub 2014 Oct 10.

Loeffen EA, Brinksma A, Miedema KG, de Bock GH, Tissing WJ. Clinical implications of malnutrition in childhood cancer patients--infections and mortality. Support Care Cancer. 2015 Jan;23(1):143-50. doi: 10.1007/s00520-014-2350-9. Epub 2014 Jul 11.

Martin-Trejo JA, Nunez-Enriquez JC, Fajardo-Gutierrez A, Medina-Sanson A, Flores-Lujano J, Jimenez-Hernandez E, Amador-Sanchez R, Penaloza-Gonzalez JG, Alvarez-Rodriguez FJ, Bolea-Murga V, Espinosa-Elizondo RM, de Diego Flores-Chapa J, Perez-Saldivar ML, Rodriguez-Zepeda MD, Dorantes-Acosta EM, Nunez-Villegas NN, Velazquez-Avina MM, Torres-Nava JR, Reyes-Zepeda NC, Gonzalez-Bonilla CR, Flores-Villegas LV, Rangel-Lopez A, Rivera-Luna R, Paredes-Aguilera R, Cardenas-Cardos R, Martinez-Avalos A, Gil-Hernandez AE, Duarte-Rodriguez DA, Mejia-Arangure JM. Early mortality in children with acute lymphoblastic leukemia in a developing country: the role of malnutrition at diagnosis. A multicenter cohort MIGICCL study. Leuk Lymphoma. 2017 Apr;58(4):898-908. doi: 10.1080/10428194.2016.1219904. Epub 2016 Aug 26.

Mejia-Arangure JM, Bonilla M, Lorenzana R, Juarez-Ocana S, de Reyes G, Perez-Saldivar ML, Gonzalez-Miranda G, Bernaldez-Rios R, Ortiz-Fernandez A, Ortega-Alvarez M, Martinez-Garcia Mdel C, Fajardo-Gutierrez A. Incidence of leukemias in children from El Salvador and Mexico City between 1996 and 2000: population-based data. BMC Cancer. 2005 Apr 4;5:33. doi: 10.1186/1471-2407-5-33.

Juarez-Ocana S, Gonzalez-Miranda G, Mejia-Arangure JM, Rendon-Macias ME, Martinez-Garcia Mdel C, Fajardo-Gutierrez A. Frequency of cancer in children residing in Mexico City and treated in the hospitals of the Instituto Mexicano del Seguro Social (1996-2001). BMC Cancer. 2004 Aug 13;4:50. doi: 10.1186/1471-2407-4-50.

Bonaventure A, Harewood R, Stiller CA, Gatta G, Clavel J, Stefan DC, Carreira H, Spika D, Marcos-Gragera R, Peris-Bonet R, Pineros M, Sant M, Kuehni CE, Murphy MFG, Coleman MP, Allemani C; CONCORD Working Group. Worldwide comparison of survival from childhood leukaemia for 1995-2009, by subtype, age, and sex (CONCORD-2): a population-based study of individual data for 89 828 children from 198 registries in 53 countries. Lancet Haematol. 2017 May;4(5):e202-e217. doi: 10.1016/S2352-3026(17)30052-2. Epub 2017 Apr 11. Erratum In: Lancet Haematol. 2017 May;4(5):e201.

Pritchard-Jones K, Pieters R, Reaman GH, Hjorth L, Downie P, Calaminus G, Naafs-Wilstra MC, Steliarova-Foucher E. Sustaining innovation and improvement in the treatment of childhood cancer: lessons from high-income countries. Lancet Oncol. 2013 Mar;14(3):e95-e103. doi: 10.1016/S1470-2045(13)70010-X. Epub 2013 Feb 20.

Steliarova-Foucher E, Colombet M, Ries LAG, Moreno F, Dolya A, Bray F, Hesseling P, Shin HY, Stiller CA; IICC-3 contributors. International incidence of childhood cancer, 2001-10: a population-based registry study. Lancet Oncol. 2017 Jun;18(6):719-731. doi: 10.1016/S1470-2045(17)30186-9. Epub 2017 Apr 11. Erratum In: Lancet Oncol. 2017 Jun;18(6):e301.

Stenholm S, Harris TB, Rantanen T, Visser M, Kritchevsky SB, Ferrucci L. Sarcopenic obesity: definition, cause and consequences. Curr Opin Clin Nutr Metab Care. 2008 Nov;11(6):693-700. doi: 10.1097/MCO.0b013e328312c37d.

Limon-Miro AT, Lopez-Teros V, Astiazaran-Garcia H. Dietary Guidelines for Breast Cancer Patients: A Critical Review. Adv Nutr. 2017 Jul 14;8(4):613-623. doi: 10.3945/an.116.014423. Print 2017 Jul.

Rock CL, Doyle C, Demark-Wahnefried W, Meyerhardt J, Courneya KS, Schwartz AL, Bandera EV, Hamilton KK, Grant B, McCullough M, Byers T, Gansler T. Nutrition and physical activity guidelines for cancer survivors. CA Cancer J Clin. 2012 Jul-Aug;62(4):243-74. doi: 10.3322/caac.21142. Epub 2012 Apr 26. Erratum In: CA Cancer J Clin. 2013 May;63(3):215.

Polyzos SA, Margioris AN. Sarcopenic obesity. Hormones (Athens). 2018 Sep;17(3):321-331. doi: 10.1007/s42000-018-0049-x. Epub 2018 Jul 16.

Prado CM, Purcell SA, Laviano A. Nutrition interventions to treat low muscle mass in cancer. J Cachexia Sarcopenia Muscle. 2020 Apr;11(2):366-380. doi: 10.1002/jcsm.12525. Epub 2020 Jan 8.

Kyle UG, Schutz Y, Dupertuis YM, Pichard C. Body composition interpretation. Contributions of the fat-free mass index and the body fat mass index. Nutrition. 2003 Jul-Aug;19(7-8):597-604. doi: 10.1016/s0899-9007(03)00061-3.

Kelly TL, Wilson KE, Heymsfield SB. Dual energy X-Ray absorptiometry body composition reference values from NHANES. PLoS One. 2009 Sep 15;4(9):e7038. doi: 10.1371/journal.pone.0007038.

Liu P, Ma F, Lou H, Liu Y. The utility of fat mass index vs. body mass index and percentage of body fat in the screening of metabolic syndrome. BMC Public Health. 2013 Jul 3;13:629. doi: 10.1186/1471-2458-13-629.

Bilen MA, Martini DJ, Liu Y, Lewis C, Collins HH, Shabto JM, Akce M, Kissick HT, Carthon BC, Shaib WL, Alese OB, Pillai RN, Steuer CE, Wu CS, Lawson DH, Kudchadkar RR, El-Rayes BF, Master VA, Ramalingam SS, Owonikoko TK, Harvey RD. The prognostic and predictive impact of inflammatory biomarkers in patients who have advanced-stage cancer treated with immunotherapy. Cancer. 2019 Jan 1;125(1):127-134. doi: 10.1002/cncr.31778. Epub 2018 Oct 17.

Charuhas Macris P, Schilling K, Palko R. Academy of Nutrition and Dietetics: Revised 2017 Standards of Practice and Standards of Professional Performance for Registered Dietitian Nutritionists (Competent, Proficient, and Expert) in Oncology Nutrition. J Acad Nutr Diet. 2018 Apr;118(4):736-748.e42. doi: 10.1016/j.jand.2018.01.012.

Heymsfield SB, Gonzalez MC, Lu J, Jia G, Zheng J. Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc. 2015 Nov;74(4):355-66. doi: 10.1017/S0029665115000129. Epub 2015 Apr 8.

Krenitsky J. Adjusted body weight, pro: evidence to support the use of adjusted body weight in calculating calorie requirements. Nutr Clin Pract. 2005 Aug;20(4):468-73. doi: 10.1177/0115426505020004468.

Renzi C, Kaushal A, Emery J, Hamilton W, Neal RD, Rachet B, Rubin G, Singh H, Walter FM, de Wit NJ, Lyratzopoulos G. Comorbid chronic diseases and cancer diagnosis: disease-specific effects and underlying mechanisms. Nat Rev Clin Oncol. 2019 Dec;16(12):746-761. doi: 10.1038/s41571-019-0249-6. Epub 2019 Jul 26.

da Silva JR Jr, Wiegert EVM, Oliveira L, Calixto-Lima L. Different methods for diagnosis of sarcopenia and its association with nutritional status and survival in patients with advanced cancer in palliative care. Nutrition. 2019 Apr;60:48-52. doi: 10.1016/j.nut.2018.09.003. Epub 2018 Sep 15.

Charan J, Biswas T. How to calculate sample size for different study designs in medical research? Indian J Psychol Med. 2013 Apr;35(2):121-6. doi: 10.4103/0253-7176.116232.

Ramos Chaves M, Boleo-Tome C, Monteiro-Grillo I, Camilo M, Ravasco P. The diversity of nutritional status in cancer: new insights. Oncologist. 2010;15(5):523-30. doi: 10.1634/theoncologist.2009-0283. Epub 2010 Apr 15.

Malard F, Mohty M. Acute lymphoblastic leukaemia. Lancet. 2020 Apr 4;395(10230):1146-1162. doi: 10.1016/S0140-6736(19)33018-1.

Murphy-Alford AJ, Prasad M, Slone J, Stein K, Mosby TT. Perspective: Creating the Evidence Base for Nutritional Support in Childhood Cancer in Low- and Middle-Income Countries: Priorities for Body Composition Research. Adv Nutr. 2020 Mar 1;11(2):216-223. doi: 10.1093/advances/nmz095.

Murphy AJ, White M, Viani K, Mosby TT. Evaluation of the nutrition screening tool for childhood cancer (SCAN). Clin Nutr. 2016 Feb;35(1):219-224. doi: 10.1016/j.clnu.2015.02.009. Epub 2015 Feb 21.

Terwilliger T, Abdul-Hay M. Acute lymphoblastic leukemia: a comprehensive review and 2017 update. Blood Cancer J. 2017 Jun 30;7(6):e577. doi: 10.1038/bcj.2017.53.

Mosby TT, Romero AL, Linares AL, Challinor JM, Day SW, Caniza M. Testing efficacy of teaching food safety and identifying variables that affect learning in a low-literacy population. J Cancer Educ. 2015 Mar;30(1):100-7. doi: 10.1007/s13187-014-0666-2.

Barr RD, Stevens MCG. The influence of nutrition on clinical outcomes in children with cancer. Pediatr Blood Cancer. 2020 Jun;67 Suppl 3:e28117. doi: 10.1002/pbc.28117. Epub 2020 Mar 5.

Srivastava R, Batra A, Dhawan D, Bakhshi S. Association of energy intake and expenditure with obesity: A cross-sectional study of 150 pediatric patients following treatment for leukemia. Pediatr Hematol Oncol. 2017 Feb;34(1):29-35. doi: 10.1080/08880018.2016.1272025. Epub 2017 Mar 13.

Totadri S, Trehan A, Mahajan D, Viani K, Barr R, Ladas EJ. Validation of an algorithmic nutritional approach in children undergoing chemotherapy for cancer. Pediatr Blood Cancer. 2019 Dec;66(12):e27980. doi: 10.1002/pbc.27980. Epub 2019 Aug 28.

Arends J, Bachmann P, Baracos V, Barthelemy N, Bertz H, Bozzetti F, Fearon K, Hutterer E, Isenring E, Kaasa S, Krznaric Z, Laird B, Larsson M, Laviano A, Muhlebach S, Muscaritoli M, Oldervoll L, Ravasco P, Solheim T, Strasser F, de van der Schueren M, Preiser JC. ESPEN guidelines on nutrition in cancer patients. Clin Nutr. 2017 Feb;36(1):11-48. doi: 10.1016/j.clnu.2016.07.015. Epub 2016 Aug 6.

Ladas EJ, Arora B, Howard SC, Rogers PC, Mosby TT, Barr RD. A Framework for Adapted Nutritional Therapy for Children With Cancer in Low- and Middle-Income Countries: A Report From the SIOP PODC Nutrition Working Group. Pediatr Blood Cancer. 2016 Aug;63(8):1339-48. doi: 10.1002/pbc.26016. Epub 2016 Apr 15.

Jansen H, Postma A, Stolk RP, Kamps WA. Acute lymphoblastic leukemia and obesity: increased energy intake or decreased physical activity? Support Care Cancer. 2009 Jan;17(1):103-6. doi: 10.1007/s00520-008-0531-0. Epub 2008 Nov 7.

Fuemmeler BF, Pendzich MK, Clark K, Lovelady C, Rosoff P, Blatt J, Demark-Wahnefried W. Diet, physical activity, and body composition changes during the first year of treatment for childhood acute leukemia and lymphoma. J Pediatr Hematol Oncol. 2013 Aug;35(6):437-43. doi: 10.1097/MPH.0b013e318279cd3e.

Iughetti L, Bruzzi P, Predieri B, Paolucci P. Obesity in patients with acute lymphoblastic leukemia in childhood. Ital J Pediatr. 2012 Jan 27;38:4. doi: 10.1186/1824-7288-38-4.

Butturini AM, Dorey FJ, Lange BJ, Henry DW, Gaynon PS, Fu C, Franklin J, Siegel SE, Seibel NL, Rogers PC, Sather H, Trigg M, Bleyer WA, Carroll WL. Obesity and outcome in pediatric acute lymphoblastic leukemia. J Clin Oncol. 2007 May 20;25(15):2063-9. doi: 10.1200/JCO.2006.07.7792.

Woolcott OO, Bergman RN. Relative Fat Mass as an estimator of whole-body fat percentage among children and adolescents: A cross-sectional study using NHANES. Sci Rep. 2019 Oct 24;9(1):15279. doi: 10.1038/s41598-019-51701-z.

Atherton RR, Williams JE, Wells JC, Fewtrell MS. Use of fat mass and fat free mass standard deviation scores obtained using simple measurement methods in healthy children and patients: comparison with the reference 4-component model. PLoS One. 2013 May 17;8(5):e62139. doi: 10.1371/journal.pone.0062139. Print 2013.

Tan SY, Poh BK, Nadrah MH, Jannah NA, Rahman J, Ismail MN. Nutritional status and dietary intake of children with acute leukaemia during induction or consolidation chemotherapy. J Hum Nutr Diet. 2013 Jul;26 Suppl 1:23-33. doi: 10.1111/jhn.12074. Epub 2013 May 24.

Murphy AJ, White M, Davies PS. Body composition of children with cancer. Am J Clin Nutr. 2010 Jul;92(1):55-60. doi: 10.3945/ajcn.2010.29201. Epub 2010 May 19.

Rogers PC, Barr RD. The relevance of nutrition to pediatric oncology: A cancer control perspective. Pediatr Blood Cancer. 2020 Jun;67 Suppl 3:e28213. doi: 10.1002/pbc.28213. Epub 2020 Feb 25.

Ding YY, Ramakrishna S, Long AH, Phillips CA, Montiel-Esparza R, Diorio CJ, Bailey LC, Maude SL, Aplenc R, Batra V, Reilly AF, Rheingold SR, Lacayo NJ, Sakamoto KM, Hunger SP. Delayed cancer diagnoses and high mortality in children during the COVID-19 pandemic. Pediatr Blood Cancer. 2020 Sep;67(9):e28427. doi: 10.1002/pbc.28427. Epub 2020 Jun 26. No abstract available.

Mehta NM, Corkins MR, Lyman B, Malone A, Goday PS, Carney LN, Monczka JL, Plogsted SW, Schwenk WF; American Society for Parenteral and Enteral Nutrition Board of Directors. Defining pediatric malnutrition: a paradigm shift toward etiology-related definitions. JPEN J Parenter Enteral Nutr. 2013 Jul;37(4):460-81. doi: 10.1177/0148607113479972. Epub 2013 Mar 25.

Bauer J, Jurgens H, Fruhwald MC. Important aspects of nutrition in children with cancer. Adv Nutr. 2011 Mar;2(2):67-77. doi: 10.3945/an.110.000141. Epub 2011 Mar 10.

Rogers PC, Melnick SJ, Ladas EJ, Halton J, Baillargeon J, Sacks N; Children's Oncology Group (COG) Nutrition Committee. Children's Oncology Group (COG) Nutrition Committee. Pediatr Blood Cancer. 2008 Feb;50(2 Suppl):447-50; discussion 451. doi: 10.1002/pbc.21414.

Redondo-Del-Rio MP, Camina-Martin MA, Marugan-de-Miguelsanz JM, de-Mateo-Silleras B. Bioelectrical impedance vector reference values for assessing body composition in a Spanish child and adolescent population. Am J Hum Biol. 2017 Jul 8;29(4). doi: 10.1002/ajhb.22978. Epub 2017 Feb 6.