{"paper_id":"008376fd-a034-4787-a979-f65fc7063170","body_text":"1\nAn evaluation of metabolic, dietetic, and nutritional status reveals impaired nutritional \noutcomes in breast cancer patients undergoing chemotherapy compared with a matched \ncontrol group.\nBruna Ramos da Silva1, Sarah Rufato1.  Mirele S. Mialich1, Loris P. Cruz2, Thais Gozzo2, Alceu A. Jordao1 \n1Department of Health Sciences, Ribeirão Preto Medical School. University of São Paulo (USP), Ribeirão \nPreto, São Paulo, Brazil. \n2 Nursing School of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.\nCorresponding author: Bruna Ramos da Silva, ORCID iD: 0000-0002-8674-5753 \n(\nbruna.ramos.silva@.usp.br). Bandeirantes Ave, 3900 – Postal code: 14049-900 - Ribeirão Preto, \nSão Paulo, Brazil. \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n2\nAbstract\nPurpose: Nutritional status changes in breast cancer patients during treatment are prevalent. \nHowever, the metabolic implications of those alterations are poorly understood. We aimed to \ncharacterize body composition, lipids, glucose levels, and indices that express cardiovascular risk \nin breast cancer patients after completion of chemotherapy and then to compare those results \nwith a matched control group. Methods: A cross-sectional study was performed. Women who \ncompleted their chemotherapy were recruited (BC group) and compared with a group of non-\nmalignant age- and body mass index-matched (MC group), as well as a group of healthy, non-\nmalignant women (HC group). Body composition by bioelectrical impedance analysis, handgrip \nstrength, and blood sample were collected. Visceral adiposity, triglyceride glucose and lipid \naccumulation product indices were calculated. Food consumption was assessed. Results: 88 \nwomen were included (BC=36, MC=36, HC=16). BC patients demonstrated worse values of \nphase angle, nutritional risk index, extracellular body water to total body water ratio and lower \nhandgrip strength. Additionally, those women had impairments in lipids, worst glucose levels, \nvisceral fat dysfunction and consequently higher cardiovascular risk, presenting important \nunhealthy dietary patterns with higher carbohydrate and caloric intake and insufficient protein \nand fiber ingestion. No differences were observed between MC and HC. Conclusion: Breast \ncancer patients present unhealthy metabolic, nutritional, and dietetic features when compared to \na group of age- and BMI-matched non-malignant females. Also, breast cancer patients had \nhigher levels of cardiovascular risk. Further investigations are required to examine the \nunderlying mechanisms and the potential longitudinal changes during surveillance time.\nKeywords: Early breast cancer; cardiovascular risk; nutritional status; metabolic changes.\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n3\nIntroduction\nBreast cancer is the most diagnosed cancer across the world, with more than 2.2 million cases in \n2020 1. Likewise, in Brazil breast cancer was one of the most diagnosed cancers in 2020 with \n66.280 new cases 2. Although breast cancer is the main prevalent form of cancer, it has one of \nthe best survival rates as well. In Brazil, the relative survival rate of 5 years between 2005 to \n2009 was 87% 3, whereas high-income countries presented 85% to 90% during 2010 through \n2014 1. Considering the risk factors, this tumour is strongly associated with obesity and \nunhealthy body composition at the diagnosis 4, however, weight gain and fat mass increase can \nbe enhanced after treatment 5.\nNot only adiposity factors are subject to alterations by cancer treatment, but several other \nnutritional indicators, as lean mass, and sarcopenia 6, and functional capacity measured by Hand \nGrip Strength (HCS) 7 can also be affected. Phase angle (PhA), obtained by bioelectrical \nimpedances, is considered both a prognosis and survival marker 8–10 and might be related to \ninflammatory and oxidative impairments 11. Its alteration has already been demonstrated as \nlinked to an increased nutritional risk measured by the Nutritional risk index (NRI) after cancer \ntreatment in breast cancer patients 12. \nSimilarly, metabolic changes are another possible consequence for those patients, such as lipids \nand glucose levels increase 13,14. Moreover, Godinho-Mota et al (2020) reported a visceral fat \ndysfunction among breast cancer patients after chemotherapy 15. Considering visceral fat \naccumulation, the adiposity indices as the visceral adiposity index (VAI), lipid accumulation \nproduct index (LAP), and triglyceride glucose index (TyG), could be important metabolic \nalterations tracking tools 16–20. Furthermore, in a previous study, our research group found a \nmetabolic syndrome prevalence of more than 50% of breast cancer survivors 21, and the \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n4\ncombination of those alterations with unhealthy body composition and improperly food intake \nmight lead to the development of secondary illness, for instance, the cardiovascular diseases in \nbreast cancer survivors 22–24, reflecting directly to the survival rates and clinical evolution after \nthe cancer care. However, worsening in blood pressure and metabolism components are \ncommonly identified in the association with other conditions besides cancer and the treatment, \nsuch as age, body mass index (BMI), dietetics imbalance 25. In particular, obesity role plays as a \ntrigger for these alterations, in which widespread obesity is related to the increasing metabolic \nsyndrome (MetS) cases 26.\nAccordingly, a comparison group is important in order to identify whether the bad outcomes are \nassociated with breast cancer and the treatment, or it is associated with age, BMI, and body fat \nmass amount, once those characteristics are also associated with breast cancer incidence 27. We \nhypothesized that breast cancer patients would demonstrate impairments in lipids, glucose, and \nbody composition, which would be worse in patients compared to a matched control group of \nnon-malignancy history females. We further hypothesized that these impairments may be \nexplained by the presence of unhealthy body composition and dietetic inadequacy. In order to \ncontribute to this field of knowledge, this study aims comprehensively characterize metabolism \ncomponents in breast cancer patients post-chemotherapy, and to compare body composition, \nmetabolic profile, and food intake results to non-malignant females of similar age and BMI. We \nalso aimed to compare breast cancer patients and matched control females to a reference group \nof nonmalignant, healthy normal BMIs females.  \nMethods\nStudy Population\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n5\nA cross-sectional study was performed. This study involved 88 participants: 36 patients \ndiagnosed with early breast cancer after 1 month of chemotherapy completion (BC females), 36 \nnon-malignant females of similar age and BMI (MC females) and 16 as a reference group of \nnonmalignant, healthy females (HC females) with normal BMIs (normal range). The data \ncollection for BC was made 1 month after finalizing the chemotherapy and before the hormone \ntherapy started, due to the possible association between hormone therapy and the increase of \nmetabolic alterations 28.  None of the participants have received nutritional counselling. Breast \ncancer patients were recruited through clinical oncology practices at Mastology ambulatory of \nGeneral Hospital of School of Medicine of Ribeirão Preto, São Paulo, Brazil. During the clinical \nconsultation, a responsible nurse informed the patient about the study. Those who were \ninterested in knowing more about it were forwarded to talk to the study researcher. Women who \nmet the following inclusion criteria were enrolled in the study: age ≥18 years and <65 years; a \nhistological confirmed diagnosis of early breast cancer (range of stage I – III); completion of the \nbreast cancer chemotherapy treatment course. Patients who previously have already received or \nstarted chemotherapy in any other moment of life; with any type of diabetes (type 1, type II or \nhad diabetes gestational); those fitted with a defibrillator, cardiac pacemaker, metal implants or \nthose with a local infection/wound preventing the use of bioelectric impedance analysis pads, \nthose unable to use a handheld dynamometer due to a neuromuscular disorder were all excluded. \nIt was adopted the breast cancer patient data collection with 1 month after finalized the \nchemotherapy due to the possible association between hormone therapy and the increase of MetS \nrisk 28. Thus, to study only the effect of chemotherapy on the sample, the evaluation was made \nbefore the hormone therapy starting to avoid possible bias.\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n6\nWomen in both control groups (MC and HC) were recruited at the same hospital, the participants \nwere employees. For both groups (BC and CG) potential participants were weighed and \nmeasured to determine BMI and completed a Health Status Screening Form to determine if they \nhad any prior cancer or were under hormone or any other medication which could modify the \nmetabolism that would have excluded them from participating in the study.  Table 1 shows all \nthe inclusion and exclusion criteria among the groups. \nTable 1: Eligibility criteria for all participant groups.\nCriteria Breast Cancer Patients\nMatched \nControl Health Control\nInclusion Criteria\nAge > 18 years old\nWithin ± 3 years \nof matched \npatient\n> 18 years old <60 \nyears old\nBMI\nWithin ± 2kg/m² \nof matched \npatient\n18.5 - 24.9\nSex female female female\nClinical characteristics:\nCancer diagnosis \nRecent diagnosis of breast \ncancer without previous \nchemotherapy \nNo history of \ncancer No history of cancer \ncancer stage Clinical stages I- III\nTreatment\nAfter completion of \nchemotherapy OR finished \nchemotherapy course\nExclusion criteria\nMetastasis\nPrevious diagnosis of \ncancer\nDiabetes any type\nHIV\nthyroid disease that is not currently managed with \nmedication\nPregnancy\nBIA exclusion factors\nUncontrolled BP    \nCaptions: BMI: Body mass index; BP: Blood Pressure. \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n7\nAfter screening, the participants eligible for the study were scheduled for the data collection \nvisit. The Institutional Review Board at the University of São Paulo, General Hospital, approved \nthe current study, protocol number: HCRP 14608/2017. \nData Collection\nAll participants underwent anthropometric assessments, bioelectrical impedance analysis, \nhandgrip strength test, food intake; and blood chemical analyzes were collected. Socioeconomic, \ndemographic, behavioral, clinical, and therapeutic data were collected directly from participants \nusing questionnaires or obtained from medical records in the BC group. In addition, written \ninformed consent was obtained at the begging of the visit. After 3 weeks of the data collection, a \ndietary food record was collected by phone call. \nAnthropometric Assessments\nMeasured anthropometric characteristics include body weight, body height, waist (WC), and hip \ncircumference (HC) as proposed by Lohman 29. Body mass index (BMI) was calculated as the \nratio between the body weight and the height squared (kg/m²). Interpretation of these results \nfollowed the international classification proposed by the World Health Organization 30.\nBioelectrical impedance analysis\nBody composition was assessed by using the bioelectrical impedance multiple-frequency (BIS) \nanalysis (Body Composition Monitor – Fresenius Medical Care®), with different frequencies (5 \nto 1,000 kHz). The BIS analysis provided data regarding fat mass (FM), fat-free mass (FFM), \nphase angle (PhA), total body water (TBW), extracellular water (EW) and intracellular water \n(IW). It was calculated the ratio between EW and TBW as well. For the PhA, it was considered \nas worse values < 5.6º 8, and for the ratio between EW and TBW the overhydrated was \nconsidered as ECW/TBW ≥0.4 31.\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n8\nHandgrip Strength\nHandgrip strength (HGS) was assessed by the CharderMG4800 dynamometer. Participants were \nasked to sit comfortably with their shoulder adducted and forearm neutrally rotated, elbow flexed \nto 90°, and forearm and wrist in a neutral position using the dominant hand 32 or contralateral \nside to mastectomy, in the adjuvant cases, and lymphedema (BC group). The highest value of the \nthree tests was used for the analysis 33. The interpretation of muscle weakness followed the \nclassification proposed by a Brazilian cohort 34, in which values below < 16kg were classified as \nweakness. It was considered as “yes” for the weakness group participants whose HGS values \nwere below the cutoff.\nDietary data collection\nThe collection of dietary data occurred through a 24-hour food record for the study. It was \ncollected 2 dietary records: the first one was collected on the day of the study visit and the \nsecond was collected after 3 weeks. The specific time frame was from the time the participant \nawoke in the morning until the time they slept at night. For this method it was used the \nmethodology of the triple-pass 24-hour recall according to Nightingale et al 35, to improve the \naccuracy for quantification of the recall. The results obtained by the recall were inserted in the \nbrazilian nutritional software Diet Box® to calculate the total amount of ingested energy and \nmacronutrients. This software uses the Brazilian table of food composition in the assessment. \nReported values were analyzed by the Multiple Source Method (MSM) to estimate the usual \nintake distribution for daily-consumed nutrients. The MSM is a statistical method proposed in \nEurope by a German team [43] which accessible is through an open source online platform. By \nthe probability of consumption and the amount consumed and regressions models, it corrects the \nwithin-person variance of the food intake results obtained by the record and yet it generates the \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n9\nusual intake for each participant [43]. Prior studies have shown that the MSM is an useful tool \nthat provides usual nutrient and food intake estimates [44,45], thus, in order to improve the \naccuracy of the food consumption collected data, the MSM was applied. For the protein \nrequirements and adequacy it was used for breast cancer patients the recommendation of 1.2 \ng/kg, as proposed by ESPEN guidelines 36. For the fiber requirements and adequacy, it was used \nfor adult female recommendations being 25 g/d, according to a review with definitions and \nregulations for dietary fiber based on official recommendations by dietary reference intakes \n(DRIs) 37.\nBlood biochemical analysis\nFor the blood biochemical analysis it was asked to all groups, to fast for 12 hours previously. \nDuring the study visit at the hospital a nurse collected a 9ml tube of peripheral blood for the BC \ngroup and a researcher nurse collected it for MC and HC groups. This sample was processed in \nthe nutrition and metabolism laboratory. The peripheral blood was collected, and serum was used \nfor the following analysis: Albumin (AL); Total protein (TP); C-reactive Protein (CRP); fasting \nglucose (FG); Triglycerides (TG); High-density lipoprotein (HDL); total cholesterol levels (CT).  \nFor the low-density lipoprotein (LDL) it was used the Friedwald equation 38.\nNutritional Risk Index (NRI)\nThe nutritional risk index was proposed in 1988 39 in order to assess the nutritional status of \nparticipants through albumin levels. In 2005, this index was modified 40, introducing the ideal \nbody weight into the formula. The NRI was calculated following the equation: \nNRI = (1.519 × serum albumin, g/dL) + {41.7 × present weight (kg)/ideal body weight(kg)}\nThe ideal body weight was calculated using the Lorentz formula for females 41:\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n10\nIdeal weight = (height − 100) − ((height − 150)/2). In those cases that body weight was over \nthan ideal weight, the fraction present weight (kg)/ideal body weight(kg) was adopted as 1 40.\nRisk stratification the NRI for malnutrition was classified as:\nnormal risk (≥100); mild risk (97.5 ≤ NRI<100); moderate risk (83.5≤ NRI <97.5); severe risk \n(NRI <83.5) 40,42. It was considered as “no” for patients with nutritional risk group, participants \nwhose NRI values were below the cutoff (<100).\nVisceral Adiposity Index, Lipid Accumulation Product Index and Triglyceride Glucose \nIndex.\nMetabolic disorders, insulin resistance, visceral fat dysfunction and lipid over accumulation were \nused to assess cardiovascular risk by using the triglyceride glucose index (TyG), visceral \nadiposity index (VAI), and lipid accumulation product index (LAP). TyG was calculated as \ndescribed by Simental-Mendia et al (2008), according to the formula: TyG index = Ln (Natural \nlogarithm) [(TG(mg/dL) × FG(mg/dL)/2] 43. VAI was calculated according to the formula for \nwomen: VAI = (WC(cm)/(36,58+(BMI *1.89) *(TG/0.81) *(1.52/HDL) 44, and LAP was \ncalculated according to the formula for women LAP= [waist (cm)−58] × TG concentration \n(mmol/l) 45. For TyG index was considered as cutoff for metabolic syndrome and insulin \nresistance values >8.45 for females 46. VAI index classification considered as being \n“metabolically healthy” was defined as VAI <1.59, and “metabolically unhealthy” as VAI ≥1.59 \n47. For LAP index classification it was considered LAP >30.40 as metabolically unhealthy 48.\nBlood pressure\nThe blood pressure (BP) was evaluated using automated cuff, the Omron device (HEM-7200) \nfrom the Omron 7000 line. Two measures were taken 60 seconds apart and repeat until both \nmeasures are within 6 mmHC for both systolic and diastolic.\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n11\nStatistical Analysis\nThe sample size calculation was performed using G*Power software version 3.1.9.4, taking into \nconsideration the effect of chemotherapy on lipids status 49. The effect size of 0.575 showed that \nwith a significance level of 95% and statistical power of 80%, using a Student t-test for paired \ndata with a 2-sided significance level of .05. The minimum number of participants required was \n29. Characteristics were summarized with the use of descriptive statistics such as mean, standard \ndeviation (SD), median, and percentage. Shapiro-Wilk test was used to verify the distribution of \ncontinuous variables. Paired t-tests to compare the BC group to matched MC group, and two-\ntailed two-sample t-tests were used to compare BC group to HC group as well as MC females to \nHC females to analyze whether there was a statistically significant difference among the mean \nvalues of the variables of interest and to compare the differences among the groups. The analysis \nwas run twice: the first test was considered the entire data, and in the second the outliers were \nremoved. The results were the same for both, therefore the outliers did not influence the results \nreported. A level of significance was set at 0.05, and SAS Studio on SAS Institute Inc. 2015. \nSAS/IML® 14.1 User's Guide was used for all data analysis.\nResults \nRegarding the BC group, 36 females were included, 67% were Stage II, 28% were Stage III, and \nthere were 5.5% at Stage I. The mean age was 45 years old (range, 26 – 64 years old), and the \nmajority of women was younger than 50 years (69.5%). The prescibed protocol of treatment was \nthe combination among Doxorubicin, Cyclophosphamide, and Docetaxel (AC-T). Clinic \ncharacteristics of the BC group are shown in table 2.\nTable 2: Sample clinic characteristics.\nVariables N %\nCancer stage\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n12\n I 2 5.50%\nII 24 67%\nIII 10 28%\nChemotherapy\nNeoadjuvant 25 69%\nAdjuvant 11 31%\nExpected cycle numbers\n4* 1 3%\n8 35 97%\nTreatment Protocol\nAC-T 36 100%\n* One participant received a shorter protocol of chemotherapy. Caption: ACT – Cyclophosphamide, \nDoxorubicin and Docetaxel\n There were no differences between the breast cancer patients and matched and health control in \nterms of age (45.3 years, 44.8 years, and 41.4 years respectively, P>0.05), and FFM (34.2 kg, \n36.1 kg and 35.2 kg years respectively, P>0.05). Regarding of weight, BMI, WC and FM, there \nwere also no differences between BC and MC (P>0.05). According to BMI classification and FM \nresults, it was observed a high prevalence of overweight and obesity in the BC group as well as \nin the MC, and for both measurements (BMI and FM) there were significant differences when \nboth BC and MC were compared to CH (P<0.05). BC females also differed from the MC and HC \nin terms of PhA and EX/TBW results, in which BC had the lowest values for PhA (5.3). The \nnon-malignancy groups (MC and HC) presented better values of HCS, NRI and BP as well. \nTable 3 present the complete data of the anthropometric, body composition, nutritional risk, \nHGS, and blood pressure among the groups. \nTable 3: Sample characteristics.\nVariable BC \nn=36)  MC \n(n=36)  HC (n=16)  Significance\n Mean SD Mean SD Mean  BC vs \nMC\nBC vs \nHC\nMC vs \nHC\nAge (y) 45.3 8.9 44.8 9.0 41.4 9.9 0.23 0.18 0.23\nHeight (cm) 159.3 7.7 162.9 5.8 161.5 7.8 0.03 0.37 0.47\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n13\nWeight (kg) 74.0 13.8 76.6 15.3 59.8 8.2 0.1 0.03 0.01\nBMI (kg/m²) 29.0 4.9 28.6 4.7 22.2 2.7 0.11 0.001 0.001\nWC (cm) 95.4 10.5 94.4 11.8 82.6 8.1 0.56 0.001 0.007\nFFM (KG) 34.2 9.5 36.1 6.2 35.2 7.3 0.28 0.7 0.65\nFM (KG) 28.1 9.6 30.1 11.3 18.9 4.4 0.25 0.02 <0.001\nPhA 5.3 0.8 6.4 0.8 6.3 0.9 <0.001 <0.001 0.69\nTBW 33.3 7.1 33.5 4.8 30.3 7.5 0.83 0.18 0.06\nEW 15.8 3.5 14.7 2.3 13.3 3.4 0.03 0.02 0.08\nIW 17.5 3.9 18.5 2.7 17.0 3.7 0.17 0.7 0.12\nEW/TBW 0.5 0.0 0.4 0.0 0.4 0 <0.001 <0.001 0.04\nBPsys \n[mmHC] 122.1 16.1 115.5 13.8 111.3 10.3 0.06 0.02 0.29\nBPdia \n[mmHC] 80.7 11.6 74.3 9.0 71.1 10.5 0.02 0.008 0.28\nHGS (kg) 22.5 5.7 27.1 6.3 24.4 5.1 <0.001 0.19 0.39\nNRI 93.4 9.5 101.4 7.0 98.0 7.4 <0.001 0.14 0.11\nBC: Breast cancer group, MC: Matched control group, HC: healthy control group, WC: waist \ncircumference, BMI: Body mass index, HGS: Handgrip strength, FFM: Fat-free mass, FM: Fat mass, \nPhA: Phase angle. TBW: Total body water. EW: Extracellular water. IW:  Intracellular water. EX/TW: \nThe ratio between extracellular water and total water BP sys: Systolic blood pressure. BP dia: Diastolic \nblood pressure. NRI: Nutritional risk index * The mean difference is significant at a level of 0.05.\nConsidering the nutritional markers tools, BC females had the highest prevalence of inadequacy \nand critical values for all measurements (PhA; HGS and NRI) when compared with matched and \nhealthy control. MC and HC had no difference in any of those markers. Figure 1 shows those \ncomparisons. \nFig 1a: Prevalence of low handgrip strength; Fig 1b: Prevalence of nutritional risk; Fig 1c: \nPrevalence of low phase angle values. Captions: BC: Breast cancer patients; MC: Matched \ncontrol group; HC: Healthy control group. The mean difference is significant at a level of 0.05.\nRegarding the food consumption of the groups, daily caloric and carbohydrate intake were higher \nin the BC group (1744 kcal and 245.2 g respectively) and differ in statistically significance from \nMC for both values. The range of protein intake/kg for BC group was 0.3 g/kg – 1.9 g/kg, and \nonly 41.6% of the patient (N=15) achieved the minimal recommendation from Espen guidelines. \nInteresting, BC females also were the group with the highest intake of fiber, being statically \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n14\nsignificant when compared to the matched group (P=0.005). Additionally, the other \nmacronutrient distribution did not differ between any participant groups. Table 4 shows the \ncomplete food intake results and their comparisons among the groups. \nTable 4: Food intake results among the groups.\nVariable BC n=36) MC (n=36) HC (n=16) Significance\n Mean SD Mean SD Mean SD BC vs \nMC\nBC vs \nHC\nMC vs \nHC\nEnergy \n(kcal) 1744.3 559.1 1363.8 572.6 1590.2 498.0 0.004 0.35 0.19\nCHO (g) 245.2 93.0 177.9 729.2 177.8 93.2 0.001 0.02 0.99\nProtein (g) 77.9 24.0 72.7 39.1 78.5 25.9 0.5 0.93 0.59\nProtein g/kg 1.1 0.0 1.0 0.6 1.3 0.3 0.37 0.1 0.08\nTotal fat (g) 50.7 21.0 47.3 22.3 48.5 23.1 0.51 0.74 0.86\nCol (g) 281.5 141.7 255.3 220.0 262.1 184.9 0.99 0.69 0.83\nFiber (g) 15.9 7.5 10.4 6.9 13.3 7.5 0.005 0.26 0.19\nCaptions: Breast cancer group; MC: Matched control group; HC: healthy control group; CHO: \nCarbohydrate; Protein g/kg: it was considered the ratio between the total amount of protein and body \nweight for each participant. Col: Cholesterol. * The mean difference is significant at a level of 0.05.\nConcerning about biochemical results, and overall, BC group had the worst value among all \nanalyses, and it was significantly different from the matched group in regarding of FG, TG, \nHDL, TC, TP, and albumin results (P<0.05). MC and HC did not differ in any biochemical \nparameters. Table 5 presents the complete data of biochemical test and their variance among the \ngroup results. \nTable 5:  Biochemical test and their variance between the groups. \nVariable BC n=36) MC (n=36) HC (n=16) Significance\n Mean SD Mean SD Mean SD BC vs \nMC\nBC vs \nHC\nMC vs \nHC\nFG 96.6 13.4 86.2 10.6 86.7 10.2 0.02 0.11 0.88\nTG 178.3 85.7 103.4 47.3 101.6 46.9 <0.001 0.001 0.9\n HDL 30.6 7.4 40.4 9.6 44.8 9.5 <0.001 <0.001 0.14\nLDL 94.6 21.1 86.1 19.0 80.9 21.6 0.09 0.04 0.4\nTC 160.9 27.3 147.1 23.1 146.0 26.0 0.02 0.07 0.88\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n15\nTP 7.5 0.9 8.2 0.8 8.5 0.7 0.001 <0.001 0.22\nCRP 17.8 31.8 12.1 12.9 10.6 10.3 0.4 0.46 0.67\nAlbumin 3.4 0.6 3.9 0.5 3.7 0.5 <0.001 0.12 0.15\nCaptions: BC: Breast cancer group; MC: Matched control group; HC: healthy control group; FG: Fasting \nglucose; TG: Triglycerides; HDL: High-density lipoprotein; LDL: Low-density lipoprotein; TC: Total \ncholesterol; TP: Total protein. CRP: C reactive protein. The mean difference is significant at a level of \n0.05.\nAs expected, following the metabolic differences observed in table 5, BC group patients had \nworse values of all adiposity markers, for both adiposity index (VAI and LAP), and metabolic \nand cardiovascular risks measured by TyG index. For the three indices, the mean value of BC \ngroup was statistically higher (P<0.05). Furthermore, it was not found difference regarding MC \nand HC groups for those evaluations. Figure 2 present the distribution of VAI, LAP and TyG \namong the groups. \nFig 2a: Distribution of visceral fat index; Fig 2b: Distribution of lipid accumulation index; Fig \n2c: Distribution of triglyceride glucose index.  Captions: BC: Breast cancer patients; MC: \nMatched control group; HG: Healthy control group. The mean difference is significant at a level \nof 0.05\nDiscussion\nTo our knowledge, only a few articles aimed to make similar comparisons. A meta-analysis \nconducted by Hernandez et al (2014) identified 22 studies in which compared breast cancer \npatients with a control group 50. However, only 2 studies included dietetic data besides the \nmetabolic factors comparisons 51,52, and we were the only study conducted with Brazilian \npopulation in which included both body composition and nutrition status parameters. Breast \ncancer patients on average are presented with a high prevalence of abdominal obesity, high body \nweight, BMI and fat mass, and consequently the matched control as well. Both groups differed \nfrom the healthy control group in all of those obesity indicators. \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n16\nThe results of our study indicate that, despite similar age, BMI, waist and hip circumferences fat-\nfree mass and fat mass (not statically significant), it was possible to verify impairments in \naspects of nutritional status markers among BC and matched control group, but not between the \nMC and HC groups. BC group presented the lowest values of PhA, and the highest prevalence of \nlow HGS, nutritional risk by NRI and overhydration by EW/TBW. All those parameters are \nconsidered indicators of poor nutritional status 8,53–55. Regarding PhA, the BC group had values \nlower than the cutoff proposed by Gupta et al (2008) in which values below 5.6 are considered a \nsign of poor prognosis for breast cancer patients 8. PhA values for both healthy controls did not \ndiffer as well as NRI and HGS values. Besides nutritional status, breast cancer patients on \naverage presented poor indicators of metabolic health, with the highest levels of BP, FG, all \nlipids’ markers, CRP, and the lowest level of albumin. Despite significant differences in body \nweight, WC, and fat mass levels, MC and HC did not differ in any biochemical parameters. This \nresult is concordant with previous research that has already reported differences in glucose \nmetabolism and metabolic syndrome prevalence among breast cancer patients 51, as well as \nalterations in insulin homeostasis when compared to the control group 56.  \nObesity is a condition that is frequently associated with abnormalities in lipid metabolism 57, \nhowever, in this study, we did not find lipids impairments in the MC group, only among the \ncancer patients. In addition to body composition, other components can contribute to lipids \nalterations, as the own tumor, in which lipid metabolism changes influence proliferation and \ndissemination of cancer cells 58, and chemotherapy itself has the potential to promotes \nmodifications in serum lipids 59. Thus, those components may explain the reason of presence of \nlipids alterations only in BC group. Moreover, poor metabolic indicators contribute to increasing \nthe risk of various conditions such as atherosclerosis, and other cardiovascular diseases 24, and \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n17\naccording to Bell et al (2014) metabolic syndrome components can increase risk of death by 3 \ntimes 51.\n In order to verify and compare cardiovascular risk, we included in this study adiposity and lipid \naccumulation indices. Several studies have already shown the VAI, LAP and TyG indices as \nsimple and good markers of cardiovascular outcomes and as screen tools for cardiovascular \ndisease risk 60–65. Kouli et al (2017), during a 10-year follow-up of a cohort of 3,042 adults, \nfound that VAI was independently associated with an elevated risk of CVD in 10 years 60. \nFurthermore, considering the TyG index, a study with a Brazilian population found superior \nperformance compared to the HOMA method for estimation of insulin resistance 66. In this study, \nas expected according to the discrepancies of biochemical blood results among the groups, the \nBC had the worst value of VAI, LAP and TyG, indicating a visceral fat dysfunction, therefore, \nhigh cardiovascular disease risk. Additionally, despite the difference in body composition, it was \nnot found any difference of those indices among the MC and HC.\nWe attempted to identify possible reasons for the difference in the metabolic and nutritional \nmarkers between patients and MC females by measuring food intake as body composition did \nnot influence those results (MC group presented healthier results than BC). There have been \nmany studies performed outlining the role of diet and disturb on glucose and lipids metabolism. \nA review conducted by Siôn A.P & Hodson L (2017) concluded that energy intake, independent \nof nutrient content, is a crucial regulator of hepatic lipid accumulation 67. Furthermore, CHO \nlevels in diet are also responsible for metabolic profile alterations where high ingestion is \nassociated with an increase in serum lipids 68,69. Concordantly, in this study, we confirmed breast \ncancer patients had the highest level of energy and carbohydrate intake, and it was statistically \ndifferent from the matched group intakes and from HC regarding CHO consumption, however, \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n18\nconsidering caloric intakes, it did not differ from the healthy females. We hypothesized that \nalong the reasons we did not find discrepancies in caloric ingestion among patients and the \nhealthy control. There could be differences in the energy expenditure and level of physical \nactivity, notably, and, as a limitation of our study, we did not evaluate those components. \nCuriously, BC presented the highest level of fiber ingestion, despite being far from the 25 g/day \nrecommendation, evidencing the diet inadequacies among the population overall. In addition to \nthe dietary shortcomings observed, the patients had low protein intake/kg as well. Although it \nwas not statistically significant when compared to the other groups (MC and HC), it is still \nclinically relevant, especially considering that changes in nutritional status markers have already \nbeen identified in this sample (PhA, NRI and EW/TBW) and low HGS. Besides, there is a \npotential for the development of sarcopenic obesity in those patients with an intake below 1.2g / \nkg 70.  \nContrary to our hypotheses, we observed no differences in body composition (FM and FFM) \nbetween breast cancer patients and matched females, and also no differences in FFM among the \n3 groups, though BC still had a higher nutritional risk. However, as we hypothesized, cancer \npatients demonstrated impairments in lipids, worst glucose levels, visceral fat dysfunction and \nconsequently higher cardiovascular risk in which those females presented important unhealthy \ndietary patterns with higher carbohydrate and caloric intake and insufficient protein and fiber \ningestion. Accordingly, our findings highlight the need for the implementation of a targeted \ndietetic approach to treat and mostly to prevent unfavorable metabolic and nutritional outcomes. \nSuccessfully, dietetic management has already shown to be an effective method to control and \nprevent metabolic impairments 71–74; it is particularly important in the breast cancer patient \npopulation where the metabolic risks are increased by the tumor and chemotherapy besides the \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n19\ndiet and body composition unfavorable. Remarkably our study has already mentioned-limitations \nas not inclusion of energy expenditure and physical activity investigation and the sample size \nwas relatively small. For further studies, the inclusion of those components and expanding the \nfollow-up of these patients could better elucidate the mechanism involved in metabolic changes \nand whether these results are maintained in the long term or enhanced by hormone therapy.\nFinally, this study has found that women undergoing breast cancer chemotherapy, after \ncompletion of the treatment, presented poor indicators of nutritional and metabolic health, such \nas PhA, NRI, EW/TBW HGS, dyslipidemia, and visceral fat dysfunction by adiposity indices \nwhen compared to a group of age- and BMI-matched non-malignant females. Body composition \nand age do not explain these differences. Furthermore, the dietetic investigation revealed a \nhigher energy intake and carbohydrate and insufficient consumption of protein and fiber.\n Considering the possibility of poor prognosis related to the nutritional markers, sarcopenic \nobesity or the subsequent threat of developing cardiovascular disease in survivorship, this study \nhighlights the necessity for more effective lifestyle intervention as exercise and nutrition \ncounseling during breast cancer treatment.\nDeclarations\nFunding:\nBRS was founded by São Paulo Research Foundation (FAPESP). Grant number: 2017/07963-0 \nand FAPESP fellowship Grant number: 2019/09877-9. LAPC was founded by Coordenação de \nAperfeiçoamento de Pessoal de Nível Superior – CAPES Brasil (Coordination for the \nImprovement of Higher Education Personnel, in free translation) – Financing Code 001 Doctoral \nscholarship granted.\nAuthors' contributions: \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n20\nThe authors’ responsibilities were as follows – AAJJ: conceptualized the study; BRS, LAPC, \nTOG, and AAJJ: were responsible for the research design; BRS and LAPC: conducted the \nresearch and analyzed the data; BRS, MM, and AAJJ: wrote the paper and had primary \nresponsibility for final content; and all authors: contributed to data interpretation and read and \napproved the final manuscript.\nConflicts of interest/ Competing interests: \nThe authors declare that they have no conflict of interest. \nEthical standard:\nAll human studies have been approved by the appropriate ethics committee and have, therefore, \nbeen performed in accordance with the ethical standards laid down in the 1964 Declaration of \nHelsinki and its later amendments. \nAll persons gave their informed consent prior to their inclusion in the study.\nAvailability of data and material:\nAll relevant data are within the paper \nCode availability:\nNot applicable\nAcknowledgments:\nWe thank all of the research group on Nutrition and Breast Cancer of the University of São \nPaulo, especially the students who assisted in all phases of the study.\n . 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(which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint \n\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted February 5, 2022. ; https://doi.org/10.1101/2022.02.03.22270381doi: medRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}