Assessment of Malnutrition among Chemotherapy Naïve and Experienced Breast Cancer Patients: A Comparative Cross- sectional and longitudinal

Assessment of Malnutrition among Chemotherapy Naïve and Experienced Breast Cancer Patients: A Comparative Cross- sectional and longitudinal | 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 Assessment of Malnutrition among Chemotherapy Naïve and Experienced Breast Cancer Patients: A Comparative Cross- sectional and longitudinal Samuel Asifiha, Abraha Gebreselama, Gidey Gebremeskel, Mulugeta Hiruy, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8506598/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Malnutrition is prevalent in cancer patients and is associated with a poor response to treatment. Thus, the early assessment of malnutrition is crucial for successful chemotherapy. This study aimed to assess malnutrition status among chemotherapy-naïve and experienced female breast cancer patients using Global Leadership Initiative on Malnutrition (GLIM) tools, blood biomarkers, and body mass index (BMI) at Ayder Comprehensive Specialized Hospital (ACSH), Northern Ethiopia. Methods: A hospital-based comparative cross-sectional and longitudinal study was conducted at the ACSH from June 5, 2022, to June 13, 2023. This study included 166 female study subjects who were selected via convenience sampling and surveyed using a structured questionnaire at an oncology center. Briefly, 6 mL of venous blood was drawn and analyzed using a Cobas®6000 chemistry analyzer and Hemax®330 hematology analyzer. Independent t-test, chi-square test, Pearson’s correlation coefficient (r), and one-way ANOVA were used for analysis. Results: Among the cases, 77.5% and 81% were at an advanced cancer stage, with mean ages of 45.3 and 44.9 years for the chemotherapy-experienced and chemotherapy-naïve groups, respectively. The prevalence of malnutrition, as determined by GLIM, was 58.1% and 71.4% for chemotherapy-experienced and chemotherapy-naïve patients, respectively. Malnutrition prevalence was significantly higher among chemotherapy-naïve patients (p < 0.001), with a decrease in albumin, total protein (TP), and BMI. Conclusions: The high prevalence and risk of malnutrition among patients with breast cancer suggests that blood biomarkers and GLIM criteria can be used as alternative tools for the prompt detection of chemotherapy-related malnutrition levels and for guiding personalized cancer treatment plans. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Breast cancer (BC) is the most frequently diagnosed malignancy and a leading cause of cancer‑related death among women worldwide, with 2,261,419 new cases reported in 2020 and accounting for approximately one quarter of all female cancers. 1,2 Although incidence rates are highest in Western Europe and North America, BC is increasingly common in developing countries, driven by rising life expectancy, urbanization, and lifestyle changes. 1,3 Improvements in early detection, surgery, and adjuvant treatment have markedly increased survival in high‑income settings; however, many patients in sub‑Saharan Africa continue to present at advanced stages due to limited awareness, reduced access to healthcare, and the absence of organized screening and diagnostic programs. 4-6 A recently published study on cancer prevalence in Addis Ababa found BC to be the most common type among females, constituting 31% of all cases. The age-standardized incidence rate for BC was 40.6 per 100,000 females. 7,8 Similarly, in Tigray, northern Ethiopia, the seven-year average prevalence of breast cancer was 26.9%. 9 Malnutrition frequently occurs in cancer patients. The global prevalence of malnutrition in patients with neoplasia has been reported to range from about 40% to 80%. 10,11 However, nearly 20% of cancer patient deaths are attributed to malnutrition and its complications rather than the malignancy itself. 12-15 A study conducted in southern Ethiopia reported that 61.4% of cancer patients were malnourished, and a study in central Ethiopia found a malnutrition prevalence of 58.4% among individuals with cancer. In Ethiopia overall, cancer accounts for approximately 5.8% of total national mortality, with a high proportion of deaths occurring in women and breast cancer among the most common fatal cancers. 16-18 Despite its recognized clinical importance, malnutrition in breast cancer patients remains under-evaluated in many low-resource settings, and standardized methods for its diagnosis and monitoring are not routinely implemented. The Global Leadership Initiative on Malnutrition (GLIM) criteria were developed to standardize malnutrition diagnosis by combining phenotypic and etiologic components, facilitating global comparisons and guiding clinical decision‑making. 13,19 In addition to GLIM, biochemical markers such as plasma albumin, globulin, total protein, creatinine, total lymphocyte count (TLC), and body mass index (BMI) have been proposed as practical tools for nutritional assessment and monitoring. However, evidence on the prevalence and profile of malnutrition using these criteria and biomarkers among breast cancer patients in Ethiopia is limited. Moreover, differences in nutritional status between chemotherapy‑naïve and chemotherapy‑experienced patients have not been well characterized in this context, leaving a critical gap in understanding how treatment exposure influences nutritional deterioration and associated risks. This study aimed to address these gaps by assessing the nutritional status of chemotherapy‑naïve and chemotherapy‑experienced female breast cancer patients using GLIM criteria alongside key biochemical, hematological, and anthropometric measures at Ayder Comprehensive Specialized Hospital in Northern Ethiopia. By elucidating the magnitude and characteristics of malnutrition in this population, the findings are expected to inform targeted nutritional interventions, support evidence‑based clinical practice, and guide health policy efforts to integrate nutritional care into comprehensive cancer management. Methods Study setting and period This study was conducted at Mekelle University, Ayder Comprehensive Specialized Hospital (ACSH), over a one-year period from June 5, 2022, to June 13, 2023. ACSH is situated in Mekelle, the capital city of the Tigray region in Northern Ethiopia. Serving as a training center for both postgraduate and undergraduate students in medical and health sciences at the College of Health Sciences, Mekelle University, the hospital is the largest referral center in the region. It caters to a population of up to 8 million across the Tigray region and neighboring areas, boasting 500 inpatient beds across all departments and additional special centers (Oncology, Cardiac, and Psychiatry centers), with ongoing construction. Trained laboratory professionals and investigators conducted sample collection and analysis at the central and emergency laboratories of the hospital. Subsequently, sample storage took place in the inpatient oncology unit of the ACSH for a duration of nine months. Study design A hospital-based comparative cross-sectional study with a longitudinal follow-up component was conducted. Study population and participants The study population comprised women with pathologically confirmed breast cancer who were scheduled to receive chemotherapy at Ayder Comprehensive Specialized Hospital during the study period. Eligible participants were recruited using convenience sampling from patients attending the oncology unit for chemotherapy. Inclusion criteria Women aged 25–64 years with pathologically confirmed breast cancer who were receiving chemotherapy and/or hormonal therapy during the study period were eligible for inclusion. Exclusion criteria Women aged ≥65 years; those with chronic co-morbid conditions, including renal disease, liver disease, HIV/AIDS, or tuberculosis; patients undergoing dialysis or receiving immunosuppressive therapy; and individuals unwilling or unable to provide written informed consent were excluded from the study. Sample size determination and sampling technique The sample size was determined based on the prevalence of malnutrition among breast cancer patients in Ethiopia 56.8%. 16 A formula for comparing two population proportions was applied to detect differences between cases and controls, assuming a specified confidence level and statistical power. Given the finite population of breast cancer patients in the study area N= 4,630, 9 a finite population correction was applied. The final sample size was 166 participants. Dependent variable Nutritional status Independent variables: The independent variables included age, duration of delay between symptom onset and first medical consultation, appetite status, unintentional weight loss, type and duration of chemotherapy, mode of feeding, clinical stage of breast cancer, and socioeconomic status. Sample collection and handling At each sampling point, 6 mL of venous blood was collected into EDTA and serum separator tubes. Serum samples were stored at ≤ –20 °C and analyzed for biochemical parameters, including albumin and total protein, after a storage period of up to nine months. Global Leadership Initiative on Malnutrition (GLIM) Tool Malnutrition was diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) criteria, requiring at least one phenotypic criterion (unintentional weight loss ≥5%, low BMI, or reduced muscle mass) and one etiologic criterion (reduced food intake or inflammation). Malnutrition severity was classified as moderate (BMI <20 kg/m²) or severe (BMI <18.5 kg/m²) among participants aged <65 years Data quality control and management We used a clear, daily-updated form to collect questionnaire data. We ran blood tests on a COBAS 6000 machine following its quality checks and lab rules. A trained technician ran blood cell counts daily on a Hemax 330, after checking quality. I coded, entered, checked, and cleaned all the data carefully. Data collection and statistical analysis Malnutrition was diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) criteria, requiring at least one phenotypic criterion (unintentional weight loss ≥5%, low BMI, or reduced muscle mass) and one etiologic criterion (reduced food intake or inflammation). Malnutrition severity was classified as moderate (BMI <20 kg/m²) or severe (BMI <18.5 kg/m²) among participants aged <65 years. Results Socio-demographic, behavioral, and clinical characteristics Comparative cross-sectional and longitudinal study: 166 women (62 experienced, 42 naïve, 32 longitudinal, 30 controls) aged 25–65. Mean ages: 45.3, 44.9, 42.4 years. Most were married, premenopausal, urban, low-income; minimal alcohol or smoking. Delays over a year occurred in ~45% are presented in (see Table 1). Table 1. Socio-demographic, behavioral, and clinical characteristics of the chemotherapy-nave, chemotherapy-experienced, and control groups Variables Chemotherapy-naïve Chemotherapy-experienced Control (n = 42 ) (n = 62) (n = 30) Age, mean (SE) 44.86 (±1.6) 45.29 (±1.4) 42.43 (±1.8) Marital status, n (%) Married 29 (69.1) 41 (66.1) 11(36.7) Single 5 (11.9) 9 (14.5) 16 (53.3) Divorced 5 (11.9) 9 (14.5) 2 (6.7) Widowed 3 (7.1) 3 (4.8) 1 (3.3) Menopausal status, n (%) Pre-menopausal 26 (61.9) 28 (45.2) 22 (73.3) Post-menopausal 16 (38.1) 34 (54.8) 8 (26.7) Residential area, n (%) Urban 26 (61.9) 45 (72.6) 17 (56.7) Rural 16 (38.1) 17 (27.4) 13 (43.3) Economic status, n (%) Low 34 (81) 41 (66.1) 16 (53.3) Middle 8 (19) 21 (33.9) 14 (46.7) Higher 0 0 0 Approximately how long did you have health concerns before contacting a doctor, n (%) Less than a month 5 (11.9) 8 (12.9) _ 1 -5 months 9 (21.4) 11 (17.7) _ 6 – 12 months 11 (26.2) 13 (21) _ More than a year 17 (40.5) 30 (48.4) _ Experienced loss of appetite, n (%)? Yes 6 (14.3) 24 (38.7) _ No 36 (85.7) 38 (61.3) _ Mode of feeding, n (%) Self-fed 32 (76.2) 38 (61.3) _ Self-fed with difficulty 7 (16.7) 21 (33.9) _ No self-fed 3 (7.1) 3 (4.8) _ Unintentional weight loss from the start of illness in kg, n (%) <5 kg lost in 3 months 9 (21.4) 12 (19.3) _ <10 kg lost in 6 months 4 (9.5) 19 (30.6) _ No change 29 (69) 31 (50) _ Presence of severe concomitant disease and comedication (name, dose, etc.), n (%) Yes 0 (0) 0 (0) NO 42 (100) 62 (100) TNM stage of the tumor, n (%) Stage I 0 (0) 2 (3.1) _ Stage II 8 (19) 12 (19.4) _ Stage III 17 (40.5) 28 (45.2) _ Stage IV 17 (40.5) 20 (32.3) _ Have you ever had surgery done previously, n (%)? Yes 25 (59.5) 52 (83.9) _ No 17 (40.5) 10 (16.1) _ Which type of surgery had done, n (%) Mastectomy 21 (84) 45 (84.9) Breast-conserving 4 (16) 8 (15.1) Chemotherapy, n (%) AC + Taxane 0 (0) 7 (11.3) AC 0 (0) 19 (30.6) C/G/P 0 (0) 12 (19.4) Tamoxifen 0 (0) 22 (35.5) Anastrozole 0 (0) 2 (3.2) No chemotherapy 42 (0) 0 (0) 1st line chemotherapy, n (%) New 42 (100) 0 (0) 1 – 3 cycles 0 (0) 11 (22.9) 4 – 6 cycles 0 (0) 11 (22.9) Completed 1st line 0 (0) 26 (54.1) 2nd line chemotherapy, n (%) New for 2nd chemotherapy _ 3 (24.4) 1 – 3 cycles _ 9 (64.3) 4 – 6 cycles _ 0 (0) Completed 2nd line _ 2 (14.3) Abbreviation: AC, andromycin (doxorubicin) + cyclophosphamide; C/G/P, Carboplatin, Gemcitabine, Paclitaxel; TNM, tumor, node, and metastasis. Note: a Age, a continuous variable, is expressed as mean ± standard error; b for the rest of the variables, qualitative; the numbers are in percentage out of the total 62- experienced, 42- naive, and 30- controls. Levels of Biochemical and BMI Characteristics among study participants Assessment of malnutrition among breast cancer patients (experienced and naive), and age matched controls was performed using anthropometric techniques and biochemical tests using standard kits. The results for the three groups are shown in (see Figure 1). Prevalence of malnutrition in breast cancer patients (experienced, and naive), and control groups GLIM-defined malnutrition: 63.4% overall (28.8% moderate, 34.6% severe). Higher in chemo-naïve (71.4%) than experienced patients (58.1%). Biochemical and anthropometric markers (e.g., albumin, protein, BMI, lymphocytes, creatinine) all indicated significantly more malnutrition in patients versus controls in Figure 2. Prevalence of malnutrition among advanced breast cancer patients based on GLIM tool, biochemical and anthropometry parameters Significantly, the prevalence of malnutrition in patients with advanced breast cancer was assessed using various markers, including the GLIM tool (80.5% and 76.6%), albumin (88.5% and 83%), total protein (TP) (82% and 79%), creatinine (74% and 84%), globulin (71.5% and 80%), TLC (76.5% and 87.5%), and BMI (85% and 82%), for chemotherapy-experienced and chemotherapy-naïve patients, respectively Figure 3 and Figure 4. Comparison of plasma albumin, TP, and BMI between well-nourished and malnourished breast cancer patients Among 104 breast cancer patients, 36.5% were well-nourished and 63.5% malnourished. Malnourished patients had significantly lower albumin, total protein, and BMI (p < 0.001), though albumin and TP were higher in malnourished chemotherapy-naïve individuals, as shown in Table 2. Table 2. Comparison of mean level of biochemical and anthropometric between well-nourished and malnourished by independent sample t-test among study groups. Variables Well-nourished Malnourished P-value (n= 38 (36.5%) ( n= 66 (63.5%) Albumin, mean and standard error Chemotherapy-naïve 3.777 ±.162 2.959 ±.259 <0.007 Chemotherapy-experienced 3.375 ±.127 2.908 ±.154 <0.03 Total protein, mean and standard error Chemotherapy-naïve 6.850 ±.900 5.673 ±.328 <0.03 Chemotherapy-experienced 3.777 ±.162 2.959 ±.259 <0.007 Body mass index, mean and standard error Chemotherapy-naïve 22.533 ±.570 17.840 ±.365 <0.001 Chemotherapy-experienced 24.420 ±.616 17.890 ±.303 <0.001 Note: ••statistically significant at p <0.05 Compare clinical features, and biochemical, hematological, anthropometric, GLIM tool conducted to independent t-test and one-way ANOVA The effect of appetite status on blood biochemical and nutritional parameters was assessed using an independent t-test. There was a statistically significant difference between the mean values of plasma albumin, plasma total protein, and GLIM and the appetite status of patients with breast cancer. However, the non-statistically significant differences in serum creatinine, plasma globulin, TLC, and BMI (see Table 3). Unintentional weight loss was also assessed using a one-way ANOVA. There was a strong statistically significant difference observed in the mean values of BMI and the GLIM tool (p <0.001) among breast cancer patients experiencing unintentional weight loss. In addition to plasma albumin (p = 0.003) and plasma total protein (p = 0.008), statistically significant associations were found with unintentional weight loss in patients with breast cancer. However, there were no statistically significant differences in serum creatinine, globulin, or TLC (see Table 4). Table 3 Independent Samples t-Test of the Effect of Appetite Status on Biochemical, Hematological, BMI Parameters, and GLIM Tool Scores in Breast Cancer Patients. Parameters Loss of appetite No loss of appetite P- value (n= 30 (28.8%)) (n= 74 (71.2%)) Plasma albumin a 2.648 ±.190 3.340 ±0.081 <0.001 Serum creatinine b 0.548 ±0.03 0.583 ±0.014 0.24 Plasma TP a 5.175 ±.353 6.173 ±.149 0.003 Plasma globulin a 2.516 ±.178 2.832 ±.090 0.085 Blood TLC c 1197.01 ±107.7 1420.43 ±117 0.26 BMI d 19.175 ±.863 20.396 ±.366 0.12 GLIM tool d 0.30 ±.16 1.85 ±.80 0.01 Abbreviations: SE, standard error; TP, total protein; TLC, total lymphocyte count; GLIM-global leadership initiative malnutrition. Note: P < 0.05, significant; data are expressed as mean ±SE; values bearing different superscripts a, b, c, d, represent units a, g/dl; b, mg/dl; c, cells/mm³; d, kg/m² Table 4 One-Way ANOVA of the Effect of Unintentional Weight Loss on Biochemical, Hematological, BMI Parameters, and GLIM Tool Scores in Breast Cancer Patients. Parameters last 3 months last 6 months No changed p-value lost 5% - 10% lost 10% - 20% n= 20 (19.2%) n= 23 (22.1%) n=61 (58.65%) Albumin a 2.73 ±0.19 3.16 ±0.22 3.30 ±0.08 0.003 Total protein a 5.26 ±0.36 5.86 ±0.39 6.16 ±0.16 0.008 Globulin a 2.51 ±0.19 2.69 ±0.20 2.86 ±0.09 0.08 Creatinine b 0.55 ±0.02 0.57 ±0.03 0.58 ±0.01 0.5 TLC c 1174.1 ±142 1683.6 ±351 1296.8 ±59 0.2 BMI d 17.44 ±0.7 19.16 ±0.73 21.32 ±0.42 <0.001 GLIM d 2.6 ±0.15 2.13 ±0.18 1.7 ±0.09 <0.001 Abbreviations: SE, standard error; TP, total protein; TLC, total lymphocyte count; GLIM-global leadership initiative malnutrition. Note: P < 0.05, significant; data are expressed as mean ±SE; values bearing different superscripts a, b, c, d, represent units a, g/dl; b, mg/dl; c, cells/mm³; d, kg/m² Clinical features conducted to longitudinal data analysis After three weeks, unintentional weight loss and appetite loss rose significantly (p < 0.0001; p = 0.002), globulin dropped significantly, while rises in hypoalbuminemia and declines in hypoproteinemia and creatinine were non-significant (see Table 5). Table 5 . Longitudinal Paired Samples t-Test Results of Clinical, Biochemical, Hematological, and Anthropometric Variables in Breast Cancer Patients. Parameters Time contacted mean difference P-value 1st visited = mean ±SD 2nd visited= mean ±SD mean ±SD UIWL 3.30 ±.83 1.60 ±1.2 1.70 ±1.5 <0.001 LOA 1.53 ±.50 1.16 ±.37 .36 ±.49 <0.001 Alb 2.79 ±.94 3.24 ±.80 -.44 ±.88 0.009 Cr 0.507 ±.11 0.501 ±.09 .006 ±.10 0.7 TP 5.12 ±1.77 6.13 ±1.36 -1.01 ±1.6 0.003 CG 2.38 ±.83 2.89 ±.70 -.50 ±.76 0.001 TLC 1343.63 ±523 1019.98 ±453 323 ±454 0.001 BMI 19.98 ±4.01 19.58 ±4.09 .40 ±3.07 0.4 Abbreviations: UIWL- unintentional weight loss; LOA- loss of appetite; Alb- albumin; Cr- creatinine; TP- total protein; CG- calculated globulin; TLC- total lymphocyte count; BMI- body mass index. Note: *P value < 0.05 is statistically significant; data are expressed as mean and standard deviation. Correlation of biochemical markers (albumin, creatinine, total protein, and globulin), hematological (TLC) level, and GLIM stage of malnutrition The relationships between GLIM stage and selected nutritional markers were examined using bivariate Pearson product-moment correlation analysis. BMI, plasma albumin, creatinine, total protein, and total lymphocyte count (TLC) all demonstrated statistically significant negative linear correlations with GLIM stage, indicating that higher GLIM stages were associated with lower levels of these markers. Among these, BMI showed a strong significant correlation with GLIM stage, whereas TLC, total protein, and creatinine exhibited weak but significant correlations. No significant correlation was observed between plasma globulin and GLIM stage (see Table 6). Bivariate Pearson’s correlation analysis Table 6. Negative correlations between GLIM tool and biochemical, hematological, and anthropometric Parameters GLIM Tool Parameters Pearson Correlations (r) P-value BMI ­0.8 <0.001 Albumin -0.3 <0.003 Creatinine -0.2 <0.02 TLC -0.2 <0.02 TP -0.2 <0.03 CG -0.1 <0.5 Abbreviations: BMI, body mass index; TLC, total lymphocyte count; TP, total protein; CG, calculate globulin. In addition, in the correlation analysis, albumin, total protein, and globulin were strongly and positively correlated with one another, while creatinine demonstrated only weak correlations with these biochemical parameters (Figure 5). Discussion Despite the novel insights provided by this study into nutritional status and its correlation with GLIM criteria among breast cancer patients in Northern Ethiopia, several limitations should be acknowledged. First, the study population was confined to patients from Northern Ethiopia, where specific genetic backgrounds, dietary practices, lifestyle factors, and socio-economic determinants may differ from other regions, potentially limiting the generalizability of our findings to broader populations. Second, the longitudinal component faced logistical constraints, resulting in incomplete follow-up data at the intended two time points, which may have influenced temporal assessments of nutritional change. Third, the absence of baseline data from chemotherapy-naive patients prior to surgery means that pre-treatment nutritional trajectories could not be fully delineated. Additionally, we did not collect detailed dietary intake information for either the patient or control groups; this limits our ability to contextualize biochemical and anthropometric findings within actual nutritional performances. Finally, to our knowledge, no prior studies in Ethiopia have directly compared chemotherapy-naive and chemotherapy-experienced breast cancer patients using the GLIM tool, which constrained our ability to standard or contextualize the present results within local research. These limitations should be considered when interpreting the applicability of our findings and underscore the need for larger, multi-center studies with comprehensive nutritional and longitudinal data. The current data suggest a significant prevalence of breast cancer among young and middle-aged individuals, with a mean age of 45.29 for experienced patients and 44.86 for naïve patients, resulting in a combined mean age of 45.075. The current finding aligns with previous studies conducted in East Africa. 21 Similar to research conducted in developing countries, 22 the current study also found a significant delay in seeking care after noticing symptoms. Our results show that among chemotherapy-experienced patients, 48 (77.5%) presented at an advanced stage of the disease, while among chemotherapy-naive patients, 34 (81%) presented at an advanced stage. When considering the combination of both groups, 82 (79%) patients presented with an advanced stage (III and IV) of the disease. Our findings are consistent with previous studies that have shown that across 17 sub-Saharan African countries, 77% of all staged cases were stage III/IV at diagnosis. 1 In contrast, this is slightly lower than the percentage reported by Melak Aynalem et al. in Northern Ethiopia (85.57%). 23 This late-stage diagnosis may also be one of the factors for the poor prognosis of breast cancer in the country, as reported by Kedida. 24 About 87.5% of breast cancer patients delayed seeking care for over a month, correlating significantly with advanced disease stage. Similar patterns emerge in both developed and developing health systems. 25 Over two-thirds of patients had low socioeconomic status; malnutrition was linked to poverty, limited resources, and absence of dieticians in cancer care. 18 According to the GLIM tool and biochemical markers, a total of 136 breast cancer patients were grouped into malnourished and well-nourished categories, based on the GLIM tool, which has been validated and employed in breast cancer patients. 26-28 In the current study, the prevalence of malnutrition according to the GLIM tool was found in 58.1% of chemotherapy patients and 71.4% of naïve patients. In contrast, the study by Cafer et al., which utilized the GLIM criteria in treatment-naive patients, reported a malnutrition prevalence slightly lower than that found in the current study (60.3% versus 71.4%), depending on factors such as treatment time and the combination of PG-SGA criteria used. 26 In addition, the prevalence of malnutrition in the current study was low as compared to the findings by Victoria et al. and Przecop et al., who reported a prevalence of malnutrition in cancer inpatients of 72.2%-80% 29 and 94%, 27 respectively. This discrepancy with the Malaga, study may be due to the high number of advanced clinical stages (92.9%, stage III 17.7%, and stage IV 75.2%), with a mean age of 60.4. Similarly, the divergence from the Basel, Switzerland study may be due to a mean age of 63 years, and the type of cancer was head and neck cancer. Moreover, the study demonstrated a significant association between the diagnosis of malnutrition based on the GLIM tool and plasma albumin, corresponding to 63.5% and 61.5%, respectively. This analysis supports the theory of GLIM criteria. 13,19,27 However, there is no evidence in opposition to the current findings regarding breast cancer. There was a significant decrease in the mean value of albumin in breast cancer patients compared to controls, a finding that is consistent with the results of two previous studies. 30,31 The result of hypoalbuminemia in breast cancer patients could be attributed to several factors. Breast cancer itself can induce inflammation in the body, leading to the release of cytokines, such as TNF-α, IL-2, and interleukin 6 (IL-6). These cytokines can decrease albumin production in the liver and increase its breakdown in the body, further contributing to decreased serum albumin levels. 30,32-34 Additionally, the mean level of serum albumin was lower in patients with malnutrition (2.908 ± 0.154 g/dl for experienced patients and 2.959 ± 0.303 g/dl for naive patients) than in well-nourished patients (3.375 ± 0.127 g/dl for experienced patients and 3.777 ± 0.616 g/dl for naive patients), and this difference was statistically significant (Table-2). This finding is consistent with a study conducted in Jimma, Ethiopia. 17 One conceivable due to the increased uptake of serum albumin by highly proliferating cancer cells through the induction of albumin-binding proteins (ABP), leading to an increase in vascular permeability and albumin flux across the capillary wall towards the extravascular compartment. This may be due to the release of tumor necrosis factor, which may increase microvascular permeability, resulting in hypoalbuminemia. 35 Another possible explanation for cancer-associated malnutrition could be nutrient deprivation and inflammation, which downregulate serum albumin gene expression, leading to the inhibition of albumin synthesis. 32 Lastly, the observed reduced albumin level in chemotherapy-experienced breast cancer patients may be due to certain chemotherapeutic drugs causing liver toxicity, leading to impaired liver function and decreased albumin synthesis. Additionally, albumin acts as an extracellular antioxidant scavenger, and a disproportionate increase in albumin degradation without a corresponding increase in synthesis can contribute to hypoalbuminemia. 32,36,37 Moreover, our study found that approximately 56.5% of chemotherapy-experienced patients and 69% of chemotherapy-naive patients had hypoalbuminemia, resulting in an overall prevalence of hypoalbuminemia of approximately 62.8% among breast cancer patients. However, the prevalence of hypoalbuminemia in our study was higher than that reported in Addis Ababa, Ethiopia (32%), 31 Nigeria (37.8%), 38 Santamaria, Brazil (56%), 39 and Jimma, Ethiopia (49.4%). 17 In contrast, the current study showed a lower prevalence of hypoalbuminemia compared to the study conducted at the University of Pelotas, Brazil (68.9%), 40 while similar to the prevalence observed in the current chemotherapy-naive study. One conceivable explanation for our results could be the higher percentage of stage IV cases, at 48.3% and 34.3% in chemotherapy-naïve and-experienced patients, respectively. Additionally, the divergence from studies in Nigeria (45 samples), Addis Ababa (50 samples), the Ivory Coast (53 samples), and Santamaria, Brazil (60 samples) might be attributed to our relatively small sample size. Another possible explanation is that most of our patients at risk of malnutrition had advanced cancer (stages III and IV). This suggests that cachexia is more prevalent in patients with advanced disease and is associated with poor quality of life and prognosis. Additionally, malnutrition has been implicated in promoting tumor growth and metastasis as well as altering the immune system and tumor cell microenvironment. 41 In the current study, a significantly lower mean plasma total protein level was observed in the patient group than in the control group Figure 1. One possible explanation for hypoproteinemia is that total protein (TP) is composed of albumin and globulin; 42 thus, hypoalbuminemia can significantly affect TP levels, as observed in 62.9% of chemotherapy-experienced and 57.1% of chemotherapy-naive patients in this study. Another potential explanation is that hypoproteinemia may result from a poor nutritional status, increased degradation of proteins for tissue protein synthesis, and its antioxidant role. Additionally, nutrient deprivation can alter protein homeostasis by inhibiting protein synthesis. 43 The findings of our study are higher compared to studies conducted in Jimma, Ethiopia 34.1%, 17 Algeria 31.1%, 44 Taif, Saudi Arabia 22.2%. 45 Taif, Saudi Arabia 22.2%.42 This discrepancy might be due to the majority of participants in our study having a low socioeconomic status. Increased protein intake (1.2–1.5 g/kg/day) enhances muscle protein synthesis via mTORC1 activation but may also stimulate tumor growth, potentially lowering total protein levels. In contrast to a previous study conducted in Ethiopia, 31 Total protein levels differed significantly between chemotherapy-experienced and naïve patients; cancer’s high metabolic demand may lower protein, suggesting factors beyond nutrition or degradation influence hypoproteinemia (Table 2). 42 Moreover, our current study showed that the mean value of total protein in chemotherapy-experienced breast cancer patients is lower than that in chemotherapy-naive breast cancer patients Figure 1. The possible reason for experienced hypoproteinemia could be as follows: chemotherapy metabolism leads to increased inflammation and compromised hepatocytes in terms of number, volume, and function, resulting in decreased protein synthesis. Additionally, mTOR inhibitors are used as anti-cancer drugs. 46 In addition, Chemotherapy drugs can damage the gastrointestinal tract, impairing the absorption of nutrients, including proteins. Malabsorption can result in decreased levels of total proteins in the bloodstream. 47 Furthermore, the differences in total protein levels between chemotherapy-experienced and chemotherapy-naive patients suggest that chemotherapy-related factors may contribute to hypoproteinemia. Chemotherapy-induced inflammation, compromised hepatocytes, mTOR inhibitor use, and gastrointestinal tract damage leading to malabsorption are some of the proposed mechanisms. In summary, the reduced total protein levels in patients with breast cancer may stem from a complex interplay of factors, including hypoalbuminemia, poor nutritional status, increased protein degradation, and chemotherapy-related effects. Further investigation is warranted to fully understand these mechanisms and their implications in patient management. A significantly lower mean serum creatinine level was observed in the study group than in the control group Figure 1. One possible explanation for this reduction in serum creatinine level might be that chemotherapy often causes side effects such as nausea, vomiting, and loss of appetite, which can result in reduced food intake. Creatinine is derived from dietary protein sources, particularly from meat, fish, and other animal products. Decreased protein intake can lead to reduced creatinine production and subsequently lower serum creatinine levels. This could be attributed to muscle mass wasting in patients with breast cancer. In addition, a large proportion of breast cancer patients in this study were in advanced stages (stages III and IV), which could have resulted in muscle mass loss due to increased breakdown of muscle protein to provide essential amino acids required for protein synthesis and energy metabolism, including gluconeogenesis for the tumor cells. 48,49 The current data demonstrate a lower mean serum creatinine level in chemotherapy-experienced patients compared to chemotherapy-naïve patients as well as control groups. One conceivable explanation is that chemotherapy can suppress metabolic processes, including muscle tissue breakdown. As creatinine is produced from the breakdown of muscle, chemotherapy-induced inhibition of muscle breakdown can contribute to decreased creatinine production and lower serum levels. 48 Lower serum creatinine in advanced breast cancer may reflect malnutrition and muscle wasting, with possible contributions from metastasis-related kidney effects. 50,51 Moreover, the presence of a tumor increases the muscle catabolic rate, resulting in a negative nitrogen balance in the muscle owing to the translocation of nitrogen from the host to the tumor. Breast cancer patients showed lower total lymphocyte counts, likely due to disease- and chemotherapy-related malnutrition impairing immune function. 52,53 Furthermore, the mean TLC value was found to decrease during chemotherapy compared to chemotherapy-naïve breast cancer patients. This may be because chemotherapy drugs induce programmed cell death (apoptosis) in rapidly dividing cells, including lymphocytes. Increased apoptosis of lymphocytes can contribute to decreased TLC levels during chemotherapy. 54 Another factor to consider is that chemotherapy drugs commonly used in breast cancer treatment can suppress bone marrow function, leading to decreased production of white blood cells, including lymphocytes. Since lymphocytes are white blood cells produced in the bone marrow, their levels may decline as a result of chemotherapy-induced bone marrow suppression. 53 Malnutrition prevalence was high (≈89–91%), likely due to advanced-stage disease and tumor-related bone marrow suppression affecting lymphocyte production. 52,55 The mean value of calculated globulin was reduced for chemotherapy experienced relative to naïve breast cancer as well as control groups. 56 This might be due to chemotherapy and cancer itself, which can lead to increased breakdown (catabolism) of proteins in the body, including globulins. This increased catabolism can result from the body's response to stress, inflammation, and the metabolic demands of cancer cells. Another explanation is that chemotherapy often suppresses the immune system as a side effect that can affect the production and activity of certain globulins, particularly immunoglobulins. Immunoglobulins are a type of globulin involved in immune responses including antibody production. Reduced immune function during chemotherapy can lead to lower levels of immunoglobulins in the bloodstream. 53 A significant prevalence of malnutrition was observed in the patient group with hypogammaglobulinemia, comprising 21% of experienced and 19% of naïve patients, while 16.7% were naïve patients. Since diagnostic delay is associated with increased infectious burden and disease complications, adding laboratory comments to highlight to the clinician that these low calculated globulins may be associated with low immunoglobulin concentrations may potentially aid in the earlier diagnosis of antibody deficiency. 56 Hypogammaglobulinemia is characterized by a decrease in the γ component. It is observed to be associated with corticosteroid and chemotherapy treatments The results demonstrated a statistically significant decrease in the mean BMI among patients with breast cancer compared to that in normal subjects. Consistent with our findings, previous studies have reported similar results. 39,57 In the present study, the mean BMI showed a statistically significant difference between malnourished (17.890 ± .303 kg/m², p < 0.001 for chemotherapy-experienced and 17.840 ± .365 kg/m², p < 0.001 for chemotherapy-naïve) and well-nourished (24.420 ± .616 kg/m² for chemotherapy-experienced and 22.420 ± .616 kg/m² for chemotherapy-naïve) patients with breast cancer. A plausible explanation is that BMI may decrease in patients with breast cancer owing to the effects of the disease itself. Breast cancer and its associated symptoms, such as loss of appetite, nausea, vomiting, and metabolic alterations, can lead to weight loss and malnutrition even before chemotherapy commences. 58 The results showed that the mean BMI was lower in chemotherapy-naïve patients with breast cancer than in experienced patients. A likely explanation is that, after completing chemotherapy, patients may enter a recovery period during which they gradually regain strength, appetite, and weight. This can lead to improvements in BMI as the body recovers from the effects of treatment. 59 In contrast, previous studies have highlighted a problem in diagnosing malnutrition among cancer patients based on BMI. 17 This is because BMI measures the whole body and does not differentiate between muscle and fat mass. However, in our study, we followed BMI based on the GLIM criteria. The GLIM framework was proposed to address this urgent need, and over 200 studies have been conducted using the GLIM since its publication in 2019. 10 Finally, according to a longitudinal study that enrolled 32 patients, After three weeks, most patients experienced weight loss and reduced appetite, likely due to chemotherapy-induced nausea, taste changes, and fatigue. 58 Cancer-related weight loss is driven by inflammation and catabolic mediators, contributing to cachexia. 60 Loss of appetite rose from 44% to 81%, likely due to chemotherapy side effects and emotional stress. 61 Weight loss and appetite loss in breast cancer are driven by inflammation, cachexia, and chemotherapy effects, highlighting the need for supportive care; biomarker levels may rise post-chemotherapy due to recovery and acute-phase responses. Conclusion This study shows that the programmed GLIM tool combined with blood biomarkers reliably diagnoses malnutrition in breast cancer patients. Malnutrition prevalence was high based on GLIM criteria, biochemical markers (albumin, TP, CG, creatinine), TLC, and BMI, with greater prevalence in chemotherapy-naive versus chemotherapy-experienced patients. Plasma albumin and BMI correlated strongly with GLIM criteria, while TP showed a weaker association. Low albumin and TP likely reflect impaired protein synthesis. Breast cancer progression was associated with lower creatinine and lymphocyte counts, indicating muscle wasting and immune depletion. Independent risk factors included delayed care, low socioeconomic status, reduced food intake, weight loss, and advanced stage. Given limitations of individual markers, combining blood biomarkers with GLIM criteria is recommended for nutritional assessment. These findings underscore the need for early evaluation, diagnosis, and nutritional intervention in breast cancer patients. Abbreviations ACSH: Ayder comprehensive specialized hospital APP: Acute phase protein APR: Acute protein response BC: Breast cancer BCP: Breast cancer patients BCG: Bromocresol green method BMI: Body mass index CG: Calculated globulin CMF: Cyclophosphamide, Methotrexate and Fluorouracil CT: Chemotherapy FAA: Free amino acid GLIM: Global leadership initiative on malnutrition IF: Interferon IL: Interleukin MPA: Medroxyprogesterone acetate MST: Malnutrition screening tool mTOR: Mechanistic target of rapamycin PEM: Protein-energy malnutrition PFAA: Plasma free amino acid PG-SGA: Patient generated subjective global assessment REE: Resting energy expenditure SGA: subjective global assessment SOP: standard operator procedure SPSS: Statistical package for the social sciences STAT3: Signal transducers and activators of transcription 3 TLC: Total lymphocyte count TNF: Tumor necrosis factor TP: Total protein UCP: Uncoupling protein Declarations Ethics approval and consent to participate: Before commencing data collection and preliminary study, an ethical clearance letter with reference number MU-IRB 1970/2022 was obtained from the Institutional Review Board of the College of Health Sciences, Mekelle University. The full information was briefly clarified and explained to each participant before enrolling any eligible study participants. Samples and data were collected only after informed consent had been obtained from the study participants. Confidentiality of records obtained from subjects was ensured by limiting access to the data and by replacing patient identification with code numbers. The findings of the study will be disseminated by publishing in reputable international journals. Additionally, they will be shared via conferences and distributed to concerned bodies in the region to better focus on caring for breast cancer patients. Consent for publication : Not applicable Availability of data and materials: The data that support the findings of this study are available from Mekelle University, College of Health Sciences; however, restrictions apply to their availability as they were used under license for the current study and are not publicly accessible. Data may be made available by the authors upon reasonable request and with permission from Mekelle University. Requests should be directed to corresponding author Samuel Asifiha (email: [email protected] ). Acknowledgements: I would like to express my sincere gratitude to the staff members of the Department of Oncology (outpatient and inpatient), Ayder Comprehensive Specialized Hospital who have given support during data collection. Also, I am greatly thankful for the study participants who were willing to give blood samples, fill out questionnaires, and provide me with invaluable data. Competing Interests: The authors declare that they have no competing interest. Funding: The authors received no specific funding for this work. 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Support Care Cancer. 2017;25(8):2581-91. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8506598","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594383466,"identity":"0b3bb208-15b7-441e-890a-2befdc04c532","order_by":0,"name":"Samuel Asifiha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYNCCAgYDNoYEBuaff2yAPMbGA4S1GEC1MDakgbQ0EKeFAaLlMJiPV4t8++k0iQ8GtcZ87MnPHhfuOG+3tv0w0JYam2ic5p/J3SY5w+C4GRvPM3PjmWduJ287kwjUciwttwGnk3K3SfMYHLNhk0gwk+Bhu51sdgCoBehCnFrk+99uk/4D1pL+DajlXLLZ+Yf4tTDcANrCYFBjxiaRYybN23bAzuwGAVsMbrzdbNljcMCYjedNmeSMM8kJZjeAtiTg8Yt8f+7GGz8q6gznt6dvk/hQYWdvdj794YMPNTa4HQYBh+GsRLDKBPzKQaAOzrInrHgUjIJRMApGGgAAxgtkAKYp1JMAAAAASUVORK5CYII=","orcid":"","institution":"Mekelle Hospital","correspondingAuthor":true,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Asifiha","suffix":""},{"id":594383467,"identity":"b43ad1b6-0a35-4570-8291-1f58c612aa51","order_by":1,"name":"Abraha Gebreselama","email":"","orcid":"","institution":"Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Abraha","middleName":"","lastName":"Gebreselama","suffix":""},{"id":594383468,"identity":"ef1b144f-d19d-451b-844a-7c3825346277","order_by":2,"name":"Gidey Gebremeskel","email":"","orcid":"","institution":"Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Gidey","middleName":"","lastName":"Gebremeskel","suffix":""},{"id":594383469,"identity":"68238c3a-d347-4259-9c62-c3d59a5d452c","order_by":3,"name":"Mulugeta Hiruy","email":"","orcid":"","institution":"Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Mulugeta","middleName":"","lastName":"Hiruy","suffix":""},{"id":594383470,"identity":"5705b0f3-4b00-4f25-b6ce-b60d00d8b5d5","order_by":4,"name":"Hagos Amare","email":"","orcid":"","institution":"Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Hagos","middleName":"","lastName":"Amare","suffix":""},{"id":594383471,"identity":"14a336d4-810f-4931-9cdd-0e9647b95927","order_by":5,"name":"Halefom Berhe","email":"","orcid":"","institution":"University of Minnesota","correspondingAuthor":false,"prefix":"","firstName":"Halefom","middleName":"","lastName":"Berhe","suffix":""},{"id":594383472,"identity":"4ca4c0b0-c28b-44f8-a1f0-c22115aa4980","order_by":6,"name":"Desta Mulu","email":"","orcid":"","institution":"Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Desta","middleName":"","lastName":"Mulu","suffix":""}],"badges":[],"createdAt":"2026-01-03 11:38:17","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8506598/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8506598/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103199472,"identity":"a888830d-fd60-407b-8855-a66b0f618ff7","added_by":"auto","created_at":"2026-02-23 05:36:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56864,"visible":true,"origin":"","legend":"\u003cp\u003eComparison mean value of albumin, total protein, creatinine, calculate globulin, total lymphocyte and body mass index among chemotherapy experienced, chemotherapy naïve and control groups\u003c/p\u003e\n\u003cp\u003eNote: albumin in g/dl, albumin in gram per deciliter; TP g/dl, \u0026nbsp;total protein in gram per deciliter; Cr mg/dl, Creatinine in milligram per deciliter; globulin g/dl, globulin in gram per deciliter; TLC C/mm\u003csup\u003e3\u003c/sup\u003e, Total lymphocyte count times 10\u003csup\u003e3\u003c/sup\u003e cells per millimeter cubic; BMI kg/m\u003csup\u003e2\u003c/sup\u003e, body mass index times 10\u003csup\u003e1 \u003c/sup\u003ekilogram per meter square.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8506598/v1/04560937127cc67904060553.png"},{"id":103199473,"identity":"1734ff50-099c-48bb-a37c-340997787247","added_by":"auto","created_at":"2026-02-23 05:36:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":148266,"visible":true,"origin":"","legend":"\u003cp\u003eComparative prevalence of malnutrition among chemotherapy-naïve, experienced, \u0026amp; control groups.\u003c/p\u003e\n\u003cp\u003eAbbreviations: ALB, albumin; TP, total protein; Cr, creatinine; CG, calculate globulin; TLC, total lymphocyte count; BMI, body mass index; GLIM, Global Leadership Initiative on Malnutrition.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8506598/v1/9a04c173c38bbdc634a2c487.png"},{"id":103199475,"identity":"a84c887b-84e7-4e65-be42-cabec12ac11b","added_by":"auto","created_at":"2026-02-23 05:36:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":31401,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Malnutrition Among Chemotherapy-Experienced Advanced Breast Cancer Patients Based on GLIM Tool, Biochemical, and Anthropometric Parameters.\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI: body mass index; TLC; total lymphocyte count; TP: total protein; GLIM: Global Leadership Initiative on Malnutrition\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8506598/v1/8b4bbe58b391589d54238b04.png"},{"id":103199476,"identity":"394958dc-d058-48fb-91a4-72f32766a21a","added_by":"auto","created_at":"2026-02-23 05:36:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":30132,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Malnutrition Among Chemotherapy-Naïve Advanced Breast Cancer Patients Based on GLIM Tool, Biochemical, and Anthropometric Parameters.\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; TLC, total lymphocyte count; TP, total protein; GLIM, Global Leadership Initiative on Malnutrition\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8506598/v1/ae3f7aa2a87fa6c1e0e3a8b5.png"},{"id":103199474,"identity":"7a093219-5649-4924-b81f-a909cd9ab16e","added_by":"auto","created_at":"2026-02-23 05:36:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":141627,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between albumin and total protein, total protein and calculate globulin, albumin and calculate globulin, albumin and creatinine.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8506598/v1/85d6a9779a63564ca22e56c0.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Malnutrition among Chemotherapy Naïve and Experienced Breast Cancer Patients: A Comparative Cross- sectional and longitudinal","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer (BC) is the most frequently diagnosed malignancy and a leading cause of cancer‑related death among women worldwide, with 2,261,419 new cases reported in 2020 and accounting for approximately one quarter of all female cancers.\u003csup\u003e1,2\u003c/sup\u003e Although incidence rates are highest in Western Europe and North America, BC is increasingly common in developing countries, driven by rising life expectancy, urbanization, and lifestyle changes.\u003csup\u003e1,3\u003c/sup\u003e Improvements in early detection, surgery, and adjuvant treatment have markedly increased survival in high‑income settings; however, many patients in sub‑Saharan Africa continue to present at advanced stages due to limited awareness, reduced access to healthcare, and the absence of organized screening and diagnostic programs.\u003csup\u003e4-6\u003c/sup\u003e A recently published study on cancer prevalence in Addis Ababa found BC to be the most common type among females, constituting 31% of all cases. The age-standardized incidence rate for BC was 40.6 per 100,000 females.\u003csup\u003e7,8\u0026nbsp;\u003c/sup\u003eSimilarly, in Tigray, northern Ethiopia, the seven-year average prevalence of breast cancer was 26.9%.\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eMalnutrition frequently occurs in cancer patients. The global prevalence of malnutrition in patients with neoplasia has been reported to range from about 40% to 80%.\u003csup\u003e10,11\u003c/sup\u003e However, nearly 20% of cancer patient deaths are attributed to malnutrition and its complications rather than the malignancy itself.\u003csup\u003e12-15\u003c/sup\u003e A study conducted in southern Ethiopia reported that 61.4% of cancer patients were malnourished, and a study in central Ethiopia found a malnutrition prevalence of 58.4% among individuals with cancer. In Ethiopia overall, cancer accounts for approximately 5.8% of total national mortality, with a high proportion of deaths occurring in women and breast cancer among the most common fatal cancers.\u003csup\u003e16-18\u003c/sup\u003e Despite its recognized clinical importance, malnutrition in breast cancer patients remains under-evaluated in many low-resource settings, and standardized methods for its diagnosis and monitoring are not routinely implemented.\u003c/p\u003e\n\u003cp\u003eThe Global Leadership Initiative on Malnutrition (GLIM) criteria were developed to standardize malnutrition diagnosis by combining phenotypic and etiologic components, facilitating global comparisons and guiding clinical decision‑making.\u003csup\u003e13,19\u003c/sup\u003e In addition to GLIM, biochemical markers such as plasma albumin, globulin, total protein, creatinine, total lymphocyte count (TLC), and body mass index (BMI) have been proposed as practical tools for nutritional assessment and monitoring. However, evidence on the prevalence and profile of malnutrition using these criteria and biomarkers among breast cancer patients in Ethiopia is limited. Moreover, differences in nutritional status between chemotherapy‑naïve and chemotherapy‑experienced patients have not been well characterized in this context, leaving a critical gap in understanding how treatment exposure influences nutritional deterioration and associated risks.\u003c/p\u003e\n\u003cp\u003eThis study aimed to address these gaps by assessing the nutritional status of chemotherapy‑naïve and chemotherapy‑experienced female breast cancer patients using GLIM criteria alongside key biochemical, hematological, and anthropometric measures at Ayder Comprehensive Specialized Hospital in Northern Ethiopia. By elucidating the magnitude and characteristics of malnutrition in this population, the findings are expected to inform targeted nutritional interventions, support evidence‑based clinical practice, and guide health policy efforts to integrate nutritional care into comprehensive cancer management.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003e\u003cstrong\u003eStudy setting and period\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was conducted at Mekelle University, Ayder Comprehensive Specialized Hospital (ACSH), over a one-year period from June 5, 2022, to June 13, 2023. ACSH is situated in Mekelle, the capital city of the Tigray region in Northern Ethiopia. Serving as a training center for both postgraduate and undergraduate students in medical and health sciences at the College of Health Sciences, Mekelle University, the hospital is the largest referral center in the region. It caters to a population of up to 8 million across the Tigray region and neighboring areas, boasting 500 inpatient beds across all departments and additional special centers (Oncology, Cardiac, and Psychiatry centers), with ongoing construction. Trained laboratory professionals and investigators conducted sample collection and analysis at the central and emergency laboratories of the hospital. Subsequently, sample storage took place in the inpatient oncology unit of the ACSH for a duration of nine months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA hospital-based comparative cross-sectional study with a longitudinal follow-up component was conducted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population and participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population comprised women with pathologically confirmed breast cancer who were scheduled to receive chemotherapy at Ayder Comprehensive Specialized Hospital during the study period. Eligible participants were recruited using convenience sampling from patients attending the oncology unit for chemotherapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWomen aged 25–64 years with pathologically confirmed breast cancer who were receiving chemotherapy and/or hormonal therapy during the study period were eligible for inclusion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWomen aged ≥65 years; those with chronic co-morbid conditions, including renal disease, liver disease, HIV/AIDS, or tuberculosis; patients undergoing dialysis or receiving immunosuppressive therapy; and individuals unwilling or unable to provide written informed consent were excluded from the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size determination and sampling technique \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was determined based on the prevalence of malnutrition among breast cancer patients in Ethiopia 56.8%.\u003csup\u003e16\u003c/sup\u003e A formula for comparing two population proportions was applied to detect differences between cases and controls, assuming a specified confidence level and statistical power. Given the finite population of breast cancer patients in the study area N= 4,630,\u003csup\u003e9\u003c/sup\u003e a finite population correction was applied. The final sample size was 166 participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNutritional status\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent variables:\u0026nbsp;\u003c/strong\u003eThe independent variables included age, duration of delay between symptom onset and first medical consultation, appetite status, unintentional weight loss, type and duration of chemotherapy, mode of feeding, clinical stage of breast cancer, and socioeconomic status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection and handling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt each sampling point, 6 mL of venous blood was collected into EDTA and serum separator tubes. Serum samples were stored at ≤ –20 °C and analyzed for biochemical parameters, including albumin and total protein, after a storage period of up to nine months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlobal Leadership Initiative on Malnutrition (GLIM) Tool\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMalnutrition was diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) criteria, requiring at least one phenotypic criterion (unintentional weight loss ≥5%, low BMI, or reduced muscle mass) and one etiologic criterion (reduced food intake or inflammation). Malnutrition severity was classified as moderate (BMI \u0026lt;20 kg/m²) or severe (BMI \u0026lt;18.5 kg/m²) among participants aged \u0026lt;65 years\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData quality control and management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used a clear, daily-updated form to collect questionnaire data. We ran blood tests on a COBAS 6000 machine following its quality checks and lab rules. A trained technician ran blood cell counts daily on a Hemax 330, after checking quality. I coded, entered, checked, and cleaned all the data carefully.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection and statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMalnutrition was diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) criteria, requiring at least one phenotypic criterion (unintentional weight loss ≥5%, low BMI, or reduced muscle mass) and one etiologic criterion (reduced food intake or inflammation). Malnutrition severity was classified as moderate (BMI \u0026lt;20 kg/m²) or severe (BMI \u0026lt;18.5 kg/m²) among participants aged \u0026lt;65 years.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003eSocio-demographic, behavioral, and clinical characteristics\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eComparative cross-sectional and longitudinal study: 166 women (62 experienced, 42 na\u0026iuml;ve, 32 longitudinal, 30 controls) aged 25\u0026ndash;65. Mean ages: 45.3, 44.9, 42.4 years. Most were married, premenopausal, urban, low-income; minimal alcohol or smoking. Delays over a year occurred in ~45% are presented in (see Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Socio-demographic, behavioral, and clinical characteristics of the chemotherapy-nave, chemotherapy-experienced, and control groups\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eVariables \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Chemotherapy-na\u0026iuml;ve \u0026nbsp; \u0026nbsp;Chemotherapy-experienced \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (n = 42 ) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (n = 62) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (n = 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eAge, mean (SE) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;44.86 (\u0026plusmn;1.6) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;45.29 (\u0026plusmn;1.4) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 42.43 (\u0026plusmn;1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eMarital status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Married \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;29 (69.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;41 (66.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 11(36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Single \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5 (11.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;9 (14.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;16 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Divorced \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5 (11.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;9 (14.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Widowed \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3 (7.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3 (4.8) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eMenopausal status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Pre-menopausal \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 26 (61.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;28 (45.2) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 22 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Post-menopausal \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 16 (38.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;34 (54.8) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;8 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eResidential area, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Urban \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 26 (61.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 45 (72.6) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Rural \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 16 (38.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17 (27.4) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 13 (43.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eEconomic status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Low \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 34 (81) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;41 (66.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 16 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Middle \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 8 (19) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;21 (33.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 14 (46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Higher \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eApproximately how long did you have health concerns before contacting a doctor, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Less than a month \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5 (11.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 8 (12.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1 -5 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 9 (21.4) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 11 (17.7) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6 \u0026ndash; 12 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 11 (26.2) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 13 (21) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; More than a year \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17 (40.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;30 (48.4) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eExperienced loss of appetite, n (%)?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Yes \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6 (14.3) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;24 (38.7) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;36 (85.7) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;38 (61.3) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eMode of feeding, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Self-fed \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;32 (76.2) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 38 (61.3) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Self-fed with difficulty \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 7 (16.7) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;21 (33.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No self-fed \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3 (7.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3 (4.8) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eUnintentional weight loss from the start of illness in kg, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;5 kg lost in 3 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;9 (21.4) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;12 (19.3) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;10 kg lost in 6 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;4 (9.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;19 (30.6) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No change \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 29 (69) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 31 (50) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003ePresence of severe concomitant disease and comedication (name, dose, etc.), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Yes \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; NO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;42 (100) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 62 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eTNM stage of the tumor, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage I \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2 (3.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage II \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;8 (19) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;12 (19.4) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage III \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17 (40.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;28 (45.2) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Stage IV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17 (40.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;20 (32.3) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eHave you ever had surgery done previously, n (%)?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Yes \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 25 (59.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;52 (83.9) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17 (40.5) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;10 (16.1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eWhich type of surgery had done, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Mastectomy \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 21 (84) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 45 (84.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Breast-conserving \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;4 (16) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 8 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003eChemotherapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; AC + Taxane \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 7 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; AC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;19 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; C/G/P \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;12 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Tamoxifen \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 22 (35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Anastrozole \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No chemotherapy \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;42 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e1st line chemotherapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; New \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;42 (100) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1 \u0026ndash; 3 cycles \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;11 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 4 \u0026ndash; 6 cycles \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;11 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Completed 1st line \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 (0) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;26 (54.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e2nd line chemotherapy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; New for 2nd chemotherapy \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _ \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1 \u0026ndash; 3 cycles \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_ \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;9 (64.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 4 \u0026ndash; 6 cycles \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;_ \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 624px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Completed 2nd line \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; _ \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviation: AC, andromycin (doxorubicin) + cyclophosphamide; C/G/P, Carboplatin, Gemcitabine, Paclitaxel; TNM, tumor, node, and metastasis.\u003c/p\u003e\n\u003cp\u003eNote: \u003csup\u003ea\u0026nbsp;\u003c/sup\u003eAge, a continuous variable, is expressed as mean \u0026plusmn; standard error; \u003csup\u003eb\u003c/sup\u003e for the rest of the variables, qualitative; the numbers are in percentage out of the total 62- experienced, 42- naive, and 30- controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLevels of Biochemical and BMI Characteristics among study participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAssessment of malnutrition among breast cancer patients (experienced and naive), and age matched controls was performed using anthropometric techniques and biochemical tests using standard kits. The results for the three groups are shown in (see Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of malnutrition in breast cancer patients (experienced, and naive), and control groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGLIM-defined malnutrition: 63.4% overall (28.8% moderate, 34.6% severe). Higher in chemo-na\u0026iuml;ve (71.4%) than experienced patients (58.1%). Biochemical and anthropometric markers (e.g., albumin, protein, BMI, lymphocytes, creatinine) all indicated significantly more malnutrition in patients versus controls in Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of malnutrition among advanced breast cancer patients based on GLIM tool, biochemical and anthropometry parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificantly, the prevalence of malnutrition in patients with advanced breast cancer was assessed using various markers, including the GLIM tool (80.5% and 76.6%), albumin (88.5% and 83%), total protein (TP) (82% and 79%), creatinine (74% and 84%), globulin (71.5% and 80%), TLC (76.5% and 87.5%), and BMI (85% and 82%), for chemotherapy-experienced and chemotherapy-na\u0026iuml;ve patients, respectively Figure 3 and Figure 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of plasma albumin, TP, and BMI between well-nourished and malnourished breast cancer patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 104 breast cancer patients, 36.5% were well-nourished and 63.5% malnourished. Malnourished patients had significantly lower albumin, total protein, and BMI (p \u0026lt; 0.001), though albumin and TP were higher in malnourished chemotherapy-na\u0026iuml;ve individuals, as shown in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Comparison of mean level of biochemical and anthropometric between well-nourished and malnourished by independent sample t-test among study groups.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eVariables \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Well-nourished \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Malnourished \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; P-value \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;(n= 38 (36.5%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;( n= 66 (63.5%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eAlbumin, mean and standard error \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chemotherapy-na\u0026iuml;ve \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3.777 \u0026plusmn;.162 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.959 \u0026plusmn;.259 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chemotherapy-experienced \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3.375 \u0026plusmn;.127 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.908 \u0026plusmn;.154 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTotal protein, mean and standard error\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chemotherapy-na\u0026iuml;ve \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6.850 \u0026plusmn;.900 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5.673 \u0026plusmn;.328 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chemotherapy-experienced \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3.777 \u0026plusmn;.162 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.959 \u0026plusmn;.259 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.007 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eBody mass index, mean and standard error\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chemotherapy-na\u0026iuml;ve \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 22.533 \u0026plusmn;.570 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17.840 \u0026plusmn;.365 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chemotherapy-experienced \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;24.420 \u0026plusmn;.616 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;17.890 \u0026plusmn;.303 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: \u0026bull;\u0026bull;statistically significant at p \u0026lt;0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompare clinical features, and biochemical, hematological, anthropometric, GLIM tool conducted to independent t-test\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eand one-way ANOVA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of appetite status on blood biochemical and nutritional parameters was assessed using an independent t-test. There was a statistically significant difference between the mean values of plasma albumin, plasma total protein, and GLIM and the appetite status of patients with breast cancer. However, the non-statistically significant differences in serum creatinine, plasma globulin, TLC, and BMI (see Table 3). Unintentional weight loss was also assessed using a one-way ANOVA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was a strong statistically significant difference observed in the mean values of BMI and the GLIM tool (p \u0026lt;0.001) among breast cancer patients experiencing unintentional weight loss. In addition to plasma albumin (p = 0.003) and plasma total protein (p = 0.008), statistically significant associations were found with unintentional weight loss in patients with breast cancer. However, there were no statistically significant differences in serum creatinine, globulin, or TLC (see Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Independent Samples t-Test of the Effect of Appetite Status on Biochemical, Hematological, BMI Parameters, and GLIM Tool Scores in Breast Cancer Patients.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eParameters \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Loss of appetite \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;No loss of appetite \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; P- value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (n= 30 (28.8%)) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (n= 74 (71.2%))\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003ePlasma albumin \u003csup\u003ea\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.648 \u0026plusmn;.190 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3.340 \u0026plusmn;0.081 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eSerum creatinine \u003csup\u003eb\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.548 \u0026plusmn;0.03 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.583 \u0026plusmn;0.014 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003ePlasma TP \u003csup\u003ea\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5.175 \u0026plusmn;.353 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6.173 \u0026plusmn;.149 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003ePlasma globulin \u003csup\u003ea\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.516 \u0026plusmn;.178 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.832 \u0026plusmn;.090 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eBlood TLC \u003csup\u003ec\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1197.01 \u0026plusmn;107.7 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1420.43 \u0026plusmn;117 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eBMI \u003csup\u003ed\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 19.175 \u0026plusmn;.863 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;20.396 \u0026plusmn;.366 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eGLIM tool \u003csup\u003ed\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.30 \u0026plusmn;.16 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1.85 \u0026plusmn;.80 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: SE, standard error; TP, total protein; TLC, total lymphocyte count; GLIM-global leadership initiative malnutrition.\u003c/p\u003e\n\u003cp\u003eNote: P \u0026lt; 0.05, significant; data are expressed as mean \u0026plusmn;SE; values bearing different superscripts a, b, c, d, represent units a, g/dl; b, mg/dl; c, cells/mm\u0026sup3;; d, kg/m\u0026sup2;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e One-Way ANOVA of the Effect of Unintentional Weight Loss on Biochemical, Hematological, BMI Parameters, and GLIM Tool Scores in Breast Cancer Patients.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eParameters \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;last 3 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;last 6 months \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No changed \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;p-value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;lost 5% - 10% \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;lost 10% - 20% \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; n= 20 (19.2%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;n= 23 (22.1%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;n=61 (58.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eAlbumin \u003csup\u003ea\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.73 \u0026plusmn;0.19 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3.16 \u0026plusmn;0.22 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3.30 \u0026plusmn;0.08 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTotal protein \u003csup\u003ea\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5.26 \u0026plusmn;0.36 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5.86 \u0026plusmn;0.39 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6.16 \u0026plusmn;0.16 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eGlobulin \u003csup\u003ea\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.51 \u0026plusmn;0.19 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.69 \u0026plusmn;0.20 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.86 \u0026plusmn;0.09 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.08 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eCreatinine \u003csup\u003eb\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.55 \u0026plusmn;0.02 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.57 \u0026plusmn;0.03 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.58 \u0026plusmn;0.01 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.5 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTLC \u003csup\u003ec\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1174.1 \u0026plusmn;142 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1683.6 \u0026plusmn;351 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1296.8 \u0026plusmn;59 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.2 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eBMI \u003csup\u003ed\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 17.44 \u0026plusmn;0.7 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;19.16 \u0026plusmn;0.73 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;21.32 \u0026plusmn;0.42 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;0.001 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eGLIM \u003csup\u003ed\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2.6 \u0026plusmn;0.15 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.13 \u0026plusmn;0.18 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.7 \u0026plusmn;0.09 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;0.001 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: SE, standard error; TP, total protein; TLC, total lymphocyte count; GLIM-global leadership initiative malnutrition.\u003c/p\u003e\n\u003cp\u003eNote: P \u0026lt; 0.05, significant; data are expressed as mean \u0026plusmn;SE; values bearing different superscripts a, b, c, d, represent units a, g/dl; b, mg/dl; c, cells/mm\u0026sup3;; d, kg/m\u0026sup2;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical features conducted to longitudinal data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter three weeks, unintentional weight loss and appetite loss rose significantly (p \u0026lt; 0.0001; p = 0.002), globulin dropped significantly, while rises in hypoalbuminemia and declines in hypoproteinemia and creatinine were non-significant (see Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e. Longitudinal Paired Samples t-Test Results of Clinical, Biochemical, Hematological, and Anthropometric Variables in Breast Cancer Patients.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eParameters \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Time contacted \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;mean difference \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;P-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1st visited = mean \u0026plusmn;SD \u0026nbsp; 2nd visited= mean \u0026plusmn;SD \u0026nbsp; \u0026nbsp; mean \u0026plusmn;SD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eUIWL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3.30 \u0026plusmn;.83 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.60 \u0026plusmn;1.2 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.70 \u0026plusmn;1.5 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;0.001 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eLOA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.53 \u0026plusmn;.50 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.16 \u0026plusmn;.37 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;.36 \u0026plusmn;.49 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eAlb \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.79 \u0026plusmn;.94 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 3.24 \u0026plusmn;.80 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-.44 \u0026plusmn;.88 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.009 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eCr \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.507 \u0026plusmn;.11 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.501 \u0026plusmn;.09 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; .006 \u0026plusmn;.10 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5.12 \u0026plusmn;1.77 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6.13 \u0026plusmn;1.36 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -1.01 \u0026plusmn;1.6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eCG \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.38 \u0026plusmn;.83 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2.89 \u0026plusmn;.70 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -.50 \u0026plusmn;.76 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eTLC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1343.63 \u0026plusmn;523 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1019.98 \u0026plusmn;453 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 323 \u0026plusmn;454 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003eBMI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 19.98 \u0026plusmn;4.01 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 19.58 \u0026plusmn;4.09 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;.40 \u0026plusmn;3.07 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: UIWL- unintentional weight loss; LOA- loss of appetite; Alb- albumin; Cr- creatinine; TP- total protein; CG- calculated globulin; TLC- total lymphocyte count; BMI- body mass index.\u003c/p\u003e\n\u003cp\u003eNote: *P value \u0026lt; 0.05 is statistically significant; data are expressed as mean and standard deviation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation of biochemical markers (albumin, creatinine, total protein, and globulin), hematological (TLC) level, and GLIM stage of malnutrition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationships between GLIM stage and selected nutritional markers were examined using bivariate Pearson product-moment correlation analysis. BMI, plasma albumin, creatinine, total protein, and total lymphocyte count (TLC) all demonstrated statistically significant negative linear correlations with GLIM stage, indicating that higher GLIM stages were associated with lower levels of these markers. Among these, BMI showed a strong significant correlation with GLIM stage, whereas TLC, total protein, and creatinine exhibited weak but significant correlations. No significant correlation was observed between plasma globulin and GLIM stage (see Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBivariate Pearson\u0026rsquo;s correlation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003eNegative correlations between GLIM tool and biochemical, hematological, and anthropometric Parameters\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLIM Tool\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePearson Correlations (r)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026shy;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eCreatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTLC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; TLC, total lymphocyte count; TP, total protein; CG, calculate globulin.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, in the correlation analysis, albumin, total protein, and globulin were strongly and positively correlated with one another, while creatinine demonstrated only weak correlations with these biochemical parameters (Figure 5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite the novel insights provided by this study into nutritional status and its correlation with GLIM criteria among breast cancer patients in Northern Ethiopia, several limitations should be acknowledged. \u0026nbsp;First, the study population was confined to patients from Northern Ethiopia, where specific genetic backgrounds, dietary practices, lifestyle factors, and socio-economic determinants may differ from other regions, potentially limiting the generalizability of our findings to broader populations.\u003c/p\u003e\n\u003cp\u003eSecond, the longitudinal component faced logistical constraints, resulting in incomplete follow-up data at the intended two time points, which may have influenced temporal assessments of nutritional change.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThird, the absence of baseline data from chemotherapy-naive patients prior to surgery means that pre-treatment nutritional trajectories could not be fully delineated. Additionally, we did not collect detailed dietary intake information for either the patient or control groups; this limits our ability to contextualize biochemical and anthropometric findings within actual nutritional performances.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, to our knowledge, no prior studies in Ethiopia have directly compared chemotherapy-naive and chemotherapy-experienced breast cancer patients using the GLIM tool, which constrained our ability to standard or contextualize the present results within local research. These limitations should be considered when interpreting the applicability of our findings and underscore the need for larger, multi-center studies with comprehensive nutritional and longitudinal data.\u003c/p\u003e\n\u003cp\u003eThe current data suggest a significant prevalence of breast cancer among young and middle-aged individuals, with a mean age of 45.29 for experienced patients and 44.86 for naïve patients, resulting in a combined mean age of 45.075. The current finding aligns with previous studies conducted in East Africa.\u003csup\u003e21\u003c/sup\u003e Similar to research conducted in developing countries,\u003csup\u003e22\u003c/sup\u003e the current study also found a significant delay in seeking care after noticing symptoms. Our results show that among chemotherapy-experienced patients, 48 (77.5%) presented at an advanced stage of the disease, while among chemotherapy-naive patients, 34 (81%) presented at an advanced stage. When considering the combination of both groups, 82 (79%) patients presented with an advanced stage (III and IV) of the disease. Our findings are consistent with previous studies that have shown that across 17 sub-Saharan African countries, 77% of all staged cases were stage III/IV at diagnosis.\u003csup\u003e1\u003c/sup\u003e In contrast, this is slightly lower than the percentage reported by Melak Aynalem et al. in Northern Ethiopia (85.57%).\u003csup\u003e23\u003c/sup\u003e This late-stage diagnosis may also be one of the factors for the poor prognosis of breast cancer in the country, as reported by Kedida.\u003csup\u003e24\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbout 87.5% of breast cancer patients delayed seeking care for over a month, correlating significantly with advanced disease stage. Similar patterns emerge in both developed and developing health systems.\u003csup\u003e25\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOver two-thirds of patients had low socioeconomic status; malnutrition was linked to poverty, limited resources, and absence of dieticians in cancer care.\u003csup\u003e18\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to the GLIM tool and biochemical markers, a total of 136 breast cancer patients were grouped into malnourished and well-nourished categories, based on the GLIM tool, which has been validated and employed in breast cancer patients.\u003csup\u003e26-28\u003c/sup\u003e In the current study, the prevalence of malnutrition according to the GLIM tool was found in 58.1% of chemotherapy patients and 71.4% of naïve patients. In contrast, the study by Cafer et al., which utilized the GLIM criteria in treatment-naive patients, reported a malnutrition prevalence slightly lower than that found in the current study (60.3% versus 71.4%), depending on factors such as treatment time and the combination of PG-SGA criteria used.\u003csup\u003e26\u003c/sup\u003e In addition, the prevalence of malnutrition in the current study was low as compared to the findings by Victoria et al. and Przecop et al., who reported a prevalence of malnutrition in cancer inpatients of 72.2%-80%\u003csup\u003e29\u0026nbsp;\u003c/sup\u003eand 94%,\u003csup\u003e27\u003c/sup\u003e respectively. This discrepancy with the Malaga, study may be due to the high number of advanced clinical stages (92.9%, stage III 17.7%, and stage IV 75.2%), with a mean age of 60.4. Similarly, the divergence from the Basel, Switzerland study may be due to a mean age of 63 years, and the type of cancer was head and neck cancer. Moreover, the study demonstrated a significant association between the diagnosis of malnutrition based on the GLIM tool and plasma albumin, corresponding to 63.5% and 61.5%, respectively. This analysis supports the theory of GLIM criteria.\u003csup\u003e13,19,27\u003c/sup\u003e However, there is no evidence in opposition to the current findings regarding breast cancer.\u003c/p\u003e\n\u003cp\u003eThere was a significant decrease in the mean value of albumin in breast cancer patients compared to controls, a finding that is consistent with the results of two previous studies.\u003csup\u003e30,31\u003c/sup\u003e The result of hypoalbuminemia in breast cancer patients could be attributed to several factors. Breast cancer itself can induce inflammation in the body, leading to the release of cytokines, such as TNF-α, IL-2, and interleukin 6 (IL-6). These cytokines can decrease albumin production in the liver and increase its breakdown in the body, further contributing to decreased serum albumin levels.\u003csup\u003e30,32-34\u003c/sup\u003e Additionally, the mean level of serum albumin was lower in patients with malnutrition (2.908 ± 0.154 g/dl for experienced patients and 2.959 ± 0.303 g/dl for naive patients) than in well-nourished patients (3.375 ± 0.127 g/dl for experienced patients and 3.777 ± 0.616 g/dl for naive patients), and this difference was statistically significant (Table-2). This finding is consistent with a study conducted in Jimma, Ethiopia.\u003csup\u003e17\u003c/sup\u003e One conceivable due to the increased uptake of serum albumin by highly proliferating cancer cells through the induction of albumin-binding proteins (ABP), leading to an increase in vascular permeability and albumin flux across the capillary wall towards the extravascular compartment. This may be due to the release of tumor necrosis factor, which may increase microvascular permeability, resulting in hypoalbuminemia.\u003csup\u003e35\u003c/sup\u003e Another possible explanation for cancer-associated malnutrition could be nutrient deprivation and inflammation, which downregulate serum albumin gene expression, leading to the inhibition of albumin synthesis.\u003csup\u003e32\u003c/sup\u003e Lastly, the observed reduced albumin level in chemotherapy-experienced breast cancer patients may be due to certain chemotherapeutic drugs causing liver toxicity, leading to impaired liver function and decreased albumin synthesis. Additionally, albumin acts as an extracellular antioxidant scavenger, and a disproportionate increase in albumin degradation without a corresponding increase in synthesis can contribute to hypoalbuminemia.\u003csup\u003e32,36,37\u003c/sup\u003e Moreover, our study found that approximately 56.5% of chemotherapy-experienced patients and 69% of chemotherapy-naive patients had hypoalbuminemia, resulting in an overall prevalence of hypoalbuminemia of approximately 62.8% among breast cancer patients. However, the prevalence of hypoalbuminemia in our study was higher than that reported in Addis Ababa, Ethiopia (32%),\u003csup\u003e31\u0026nbsp;\u003c/sup\u003eNigeria (37.8%),\u003csup\u003e38\u003c/sup\u003e Santamaria, Brazil (56%),\u003csup\u003e39\u003c/sup\u003e and Jimma, Ethiopia (49.4%).\u003csup\u003e17\u003c/sup\u003e In contrast, the current study showed a lower prevalence of hypoalbuminemia compared to the study conducted at the University of Pelotas, Brazil (68.9%),\u003csup\u003e40\u003c/sup\u003e while similar to the prevalence observed in the current chemotherapy-naive study. One conceivable explanation for our results could be the higher percentage of stage IV cases, at 48.3% and 34.3% in chemotherapy-naïve and-experienced patients, respectively. Additionally, the divergence from studies in Nigeria (45 samples), Addis Ababa (50 samples), the Ivory Coast (53 samples), and Santamaria, Brazil (60 samples) might be attributed to our relatively small sample size. Another possible explanation is that most of our patients at risk of malnutrition had advanced cancer (stages III and IV). This suggests that cachexia is more prevalent in patients with advanced disease and is associated with poor quality of life and prognosis. Additionally, malnutrition has been implicated in promoting tumor growth and metastasis as well as altering the immune system and tumor cell microenvironment.\u003csup\u003e41\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the current study, a significantly lower mean plasma total protein level was observed in the patient group than in the control group Figure 1. One possible explanation for hypoproteinemia is that total protein (TP) is composed of albumin and globulin;\u003csup\u003e42\u003c/sup\u003e thus, hypoalbuminemia can significantly affect TP levels, as observed in 62.9% of chemotherapy-experienced and 57.1% of chemotherapy-naive patients in this study. Another potential explanation is that hypoproteinemia may result from a poor nutritional status, increased degradation of proteins for tissue protein synthesis, and its antioxidant role. Additionally, nutrient deprivation can alter protein homeostasis by inhibiting protein synthesis.\u003csup\u003e43\u003c/sup\u003e The findings of our study are higher compared to studies conducted in Jimma, Ethiopia 34.1%,\u003csup\u003e17\u003c/sup\u003e Algeria 31.1%,\u003csup\u003e44\u003c/sup\u003e Taif, Saudi Arabia 22.2%.\u003csup\u003e45\u003c/sup\u003e Taif, Saudi Arabia 22.2%.42 This discrepancy might be due to the majority of participants in our study having a low socioeconomic status. Increased protein intake (1.2–1.5 g/kg/day) enhances muscle protein synthesis via mTORC1 activation but may also stimulate tumor growth, potentially lowering total protein levels. In contrast to a previous study conducted in Ethiopia,\u003csup\u003e31\u003c/sup\u003e Total protein levels differed significantly between chemotherapy-experienced and naïve patients; cancer’s high metabolic demand may lower protein, suggesting factors beyond nutrition or degradation influence hypoproteinemia (Table 2).\u003csup\u003e42\u003c/sup\u003e Moreover, our current study showed that the mean value of total protein in chemotherapy-experienced breast cancer patients is lower than that in chemotherapy-naive breast cancer patients Figure 1.\u0026nbsp;The possible reason for experienced hypoproteinemia could be as follows: chemotherapy metabolism leads to increased inflammation and compromised hepatocytes in terms of number, volume, and function, resulting in decreased protein synthesis. Additionally, mTOR inhibitors are used as anti-cancer drugs.\u003csup\u003e46\u003c/sup\u003e In addition, Chemotherapy drugs can damage the gastrointestinal tract, impairing the absorption of nutrients, including proteins. Malabsorption can result in decreased levels of total proteins in the bloodstream.\u003csup\u003e47\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, the differences in total protein levels between chemotherapy-experienced and chemotherapy-naive patients suggest that chemotherapy-related factors may contribute to hypoproteinemia. Chemotherapy-induced inflammation, compromised hepatocytes, mTOR inhibitor use, and gastrointestinal tract damage leading to malabsorption are some of the proposed mechanisms. In summary, the reduced total protein levels in patients with breast cancer may stem from a complex interplay of factors, including hypoalbuminemia, poor nutritional status, increased protein degradation, and chemotherapy-related effects. Further investigation is warranted to fully understand these mechanisms and their implications in patient management.\u003c/p\u003e\n\u003cp\u003eA significantly lower mean serum creatinine level was observed in the study group than in the control group Figure 1. One possible explanation for this reduction in serum creatinine level might be that chemotherapy often causes side effects such as nausea, vomiting, and loss of appetite, which can result in reduced food intake. Creatinine is derived from dietary protein sources, particularly from meat, fish, and other animal products. Decreased protein intake can lead to reduced creatinine production and subsequently lower serum creatinine levels. This could be attributed to muscle mass wasting in patients with breast cancer. In addition, a large proportion of breast cancer patients in this study were in advanced stages (stages III and IV), which could have resulted in muscle mass loss due to increased breakdown of muscle protein to provide essential amino acids required for protein synthesis and energy metabolism, including gluconeogenesis for the tumor cells.\u003csup\u003e48,49\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe current data demonstrate a lower mean serum creatinine level in chemotherapy-experienced patients compared to chemotherapy-naïve patients as well as control groups. One conceivable explanation is that chemotherapy can suppress metabolic processes, including muscle tissue breakdown. As creatinine is produced from the breakdown of muscle, chemotherapy-induced inhibition of muscle breakdown can contribute to decreased creatinine production and lower serum levels.\u003csup\u003e48\u003c/sup\u003e\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLower serum creatinine in advanced breast cancer may reflect malnutrition and muscle wasting, with possible contributions from metastasis-related kidney effects.\u003csup\u003e50,51\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMoreover, the presence of a tumor increases the muscle catabolic rate, resulting in a negative nitrogen balance in the muscle owing to the translocation of nitrogen from the host to the tumor.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBreast cancer patients showed lower total lymphocyte counts, likely due to disease- and chemotherapy-related malnutrition impairing immune function.\u003csup\u003e52,53\u003c/sup\u003e Furthermore, the mean TLC value was found to decrease during chemotherapy compared to chemotherapy-naïve breast cancer patients. This may be because chemotherapy drugs induce programmed cell death (apoptosis) in rapidly dividing cells, including lymphocytes. Increased apoptosis of lymphocytes can contribute to decreased TLC levels during chemotherapy.\u003csup\u003e54\u003c/sup\u003e Another factor to consider is that chemotherapy drugs commonly used in breast cancer treatment can suppress bone marrow function, leading to decreased production of white blood cells, including lymphocytes. Since lymphocytes are white blood cells produced in the bone marrow, their levels may decline as a result of chemotherapy-induced bone marrow suppression.\u003csup\u003e53\u003c/sup\u003e Malnutrition prevalence was high (≈89–91%), likely due to advanced-stage disease and tumor-related bone marrow suppression affecting lymphocyte production.\u003csup\u003e52,55\u003c/sup\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mean value of calculated globulin was reduced for chemotherapy experienced relative to naïve breast cancer as well as control groups.\u003csup\u003e56\u003c/sup\u003e This might be due to chemotherapy and cancer itself, which can lead to increased breakdown (catabolism) of proteins in the body, including globulins. This increased catabolism can result from the body's response to stress, inflammation, and the metabolic demands of cancer cells. Another explanation is that chemotherapy often suppresses the immune system as a side effect that can affect the production and activity of certain globulins, particularly immunoglobulins. Immunoglobulins are a type of globulin involved in immune responses including antibody production. Reduced immune function during chemotherapy can lead to lower levels of immunoglobulins in the bloodstream.\u003csup\u003e53\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA significant prevalence of malnutrition was observed in the patient group with hypogammaglobulinemia, comprising 21% of experienced and 19% of naïve patients, while 16.7% were naïve patients. Since diagnostic delay is associated with increased infectious burden and disease complications, adding laboratory comments to highlight to the clinician that these low calculated globulins may be associated with low immunoglobulin concentrations may potentially aid in the earlier diagnosis of antibody deficiency.\u003csup\u003e56\u003c/sup\u003e Hypogammaglobulinemia is characterized by a decrease in the γ component. It is observed to be associated with corticosteroid and chemotherapy treatments\u003c/p\u003e\n\u003cp\u003eThe results demonstrated a statistically significant decrease in the mean BMI among patients with breast cancer compared to that in normal subjects. Consistent with our findings, previous studies have reported similar results.\u003csup\u003e39,57\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the present study, the mean BMI showed a statistically significant difference between malnourished (17.890 ± .303 kg/m², p \u0026lt; 0.001 for chemotherapy-experienced and 17.840 ± .365 kg/m², p \u0026lt; 0.001 for chemotherapy-naïve) and well-nourished (24.420 ± .616 kg/m² for chemotherapy-experienced and 22.420 ± .616 kg/m² for chemotherapy-naïve) patients with breast cancer. A plausible explanation is that BMI may decrease in patients with breast cancer owing to the effects of the disease itself. Breast cancer and its associated symptoms, such as loss of appetite, nausea, vomiting, and metabolic alterations, can lead to weight loss and malnutrition even before chemotherapy commences.\u003csup\u003e58\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results showed that the mean BMI was lower in chemotherapy-naïve patients with breast cancer than in experienced patients. A likely explanation is that, after completing chemotherapy, patients may enter a recovery period during which they gradually regain strength, appetite, and weight. This can lead to improvements in BMI as the body recovers from the effects of treatment.\u003csup\u003e59\u003c/sup\u003e In contrast, previous studies have highlighted a problem in diagnosing malnutrition among cancer patients based on BMI.\u003csup\u003e17\u003c/sup\u003e This is because BMI measures the whole body and does not differentiate between muscle and fat mass. However, in our study, we followed BMI based on the GLIM criteria. The GLIM framework was proposed to address this urgent need, and over 200 studies have been conducted using the GLIM since its publication in 2019.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eFinally, according to a longitudinal study that enrolled 32 patients, After three weeks, most patients experienced weight loss and reduced appetite, likely due to chemotherapy-induced nausea, taste changes, and fatigue.\u003csup\u003e58\u0026nbsp;\u003c/sup\u003e Cancer-related weight loss is driven by inflammation and catabolic mediators, contributing to cachexia.\u003csup\u003e60\u003c/sup\u003e Loss of appetite rose from 44% to 81%, likely due to chemotherapy side effects and emotional stress.\u003csup\u003e61\u003c/sup\u003e Weight loss and appetite loss in breast cancer are driven by inflammation, cachexia, and chemotherapy effects, highlighting the need for supportive care; biomarker levels may rise post-chemotherapy due to recovery and acute-phase responses.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study shows that the programmed GLIM tool combined with blood biomarkers reliably diagnoses malnutrition in breast cancer patients. Malnutrition prevalence was high based on GLIM criteria, biochemical markers (albumin, TP, CG, creatinine), TLC, and BMI, with greater prevalence in chemotherapy-naive versus chemotherapy-experienced patients. Plasma albumin and BMI correlated strongly with GLIM criteria, while TP showed a weaker association. Low albumin and TP likely reflect impaired protein synthesis. Breast cancer progression was associated with lower creatinine and lymphocyte counts, indicating muscle wasting and immune depletion. Independent risk factors included delayed care, low socioeconomic status, reduced food intake, weight loss, and advanced stage. Given limitations of individual markers, combining blood biomarkers with GLIM criteria is recommended for nutritional assessment. These findings underscore the need for early evaluation, diagnosis, and nutritional intervention in breast cancer patients.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACSH: Ayder comprehensive specialized hospital\u003c/p\u003e\n\u003cp\u003eAPP: Acute phase protein\u003c/p\u003e\n\u003cp\u003eAPR: Acute protein response\u003c/p\u003e\n\u003cp\u003eBC: Breast cancer\u003c/p\u003e\n\u003cp\u003eBCP: Breast cancer patients\u003c/p\u003e\n\u003cp\u003eBCG: Bromocresol green method\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI: Body mass index\u003c/p\u003e\n\u003cp\u003eCG: Calculated globulin\u003c/p\u003e\n\u003cp\u003eCMF: Cyclophosphamide, Methotrexate and Fluorouracil\u003c/p\u003e\n\u003cp\u003eCT: Chemotherapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFAA: Free amino acid\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGLIM: Global leadership initiative on malnutrition\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIF: Interferon\u003c/p\u003e\n\u003cp\u003eIL: Interleukin\u003c/p\u003e\n\u003cp\u003eMPA: Medroxyprogesterone acetate\u003c/p\u003e\n\u003cp\u003eMST: Malnutrition screening tool\u003c/p\u003e\n\u003cp\u003emTOR: Mechanistic target of rapamycin\u003c/p\u003e\n\u003cp\u003ePEM: Protein-energy malnutrition\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePFAA: Plasma free amino acid\u003c/p\u003e\n\u003cp\u003ePG-SGA: Patient generated subjective global assessment\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eREE: Resting energy expenditure\u003c/p\u003e\n\u003cp\u003eSGA: subjective global assessment\u003c/p\u003e\n\u003cp\u003eSOP: standard operator procedure\u003c/p\u003e\n\u003cp\u003eSPSS: Statistical package for the social sciences\u003c/p\u003e\n\u003cp\u003eSTAT3: Signal transducers and activators of transcription 3\u003c/p\u003e\n\u003cp\u003eTLC: Total lymphocyte count\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTNF: Tumor necrosis factor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTP: Total protein\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUCP: Uncoupling protein\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore commencing data collection and preliminary study, an ethical clearance letter with reference number MU-IRB 1970/2022 was obtained from the Institutional Review Board of the College of Health Sciences, Mekelle University. The full information was briefly clarified and explained to each participant before enrolling any eligible study participants. Samples and data were collected only after informed consent had been obtained from the study participants. Confidentiality of records obtained from subjects was ensured by limiting access to the data and by replacing patient identification with code numbers. The findings of the study will be disseminated by publishing in reputable international journals. Additionally, they will be shared via conferences and distributed to concerned bodies in the region to better focus on caring for breast cancer patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from Mekelle University, College of Health Sciences; however, restrictions apply to their availability as they were used under license for the current study and are not publicly accessible. Data may be made available by the authors upon reasonable request and with permission from Mekelle University. Requests should be directed to corresponding author Samuel Asifiha (email:\u0026nbsp;[email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eI would like to express my sincere gratitude to the staff members of the Department of Oncology (outpatient and inpatient), Ayder Comprehensive Specialized Hospital who have given support during data collection. Also, I am greatly thankful for the study participants who were willing to give blood samples, fill out questionnaires, and provide me with invaluable data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions:\u0026nbsp;\u003c/strong\u003eConceptualization: SA, AG; Methodology: SA, AG, HA; Validation: SA, GG, MH; Investigation: SA; Writing Original Draft: SA, HB, DM; Writing Review \u0026amp; Editing: SA, AG, GG, MH, HA; Visualization: SA, AG, HA, DM; Supervision: AG, GG, HA, MH\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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Nutrients. 2021 Apr 5;13(4):1196.\u003c/li\u003e\n\u003cli\u003ede Vries YC, van den Berg M, de Vries JHM, Boesveldt S, de Kruif J, Buist N, et al. Differences in dietary intake during chemotherapy in breast cancer patients compared to women without cancer. Support Care Cancer. 2017;25(8):2581-91.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8506598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8506598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background: Malnutrition is prevalent in cancer patients and is associated with a poor response to treatment. Thus, the early assessment of malnutrition is crucial for successful chemotherapy. This study aimed to assess malnutrition status among chemotherapy-naïve and experienced female breast cancer patients using Global Leadership Initiative on Malnutrition (GLIM) tools, blood biomarkers, and body mass index (BMI) at Ayder Comprehensive Specialized Hospital (ACSH), Northern Ethiopia.\nMethods: A hospital-based comparative cross-sectional and longitudinal study was conducted at the ACSH from June 5, 2022, to June 13, 2023. This study included 166 female study subjects who were selected via convenience sampling and surveyed using a structured questionnaire at an oncology center. Briefly, 6 mL of venous blood was drawn and analyzed using a Cobas®6000 chemistry analyzer and Hemax®330 hematology analyzer. Independent t-test, chi-square test, Pearson’s correlation coefficient (r), and one-way ANOVA were used for analysis.\nResults: Among the cases, 77.5% and 81% were at an advanced cancer stage, with mean ages of 45.3 and 44.9 years for the chemotherapy-experienced and chemotherapy-naïve groups, respectively. The prevalence of malnutrition, as determined by GLIM, was 58.1% and 71.4% for chemotherapy-experienced and chemotherapy-naïve patients, respectively. Malnutrition prevalence was significantly higher among chemotherapy-naïve patients (p \u003c 0.001), with a decrease in albumin, total protein (TP), and BMI.\nConclusions: The high prevalence and risk of malnutrition among patients with breast cancer suggests that blood biomarkers and GLIM criteria can be used as alternative tools for the prompt detection of chemotherapy-related malnutrition levels and for guiding personalized cancer treatment plans.","manuscriptTitle":"Assessment of Malnutrition among Chemotherapy Naïve and Experienced Breast Cancer Patients: A Comparative Cross- sectional and longitudinal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 05:35:57","doi":"10.21203/rs.3.rs-8506598/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0283787-f797-4e8b-bfd4-6b2fd7e6f89f","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T05:35:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 05:35:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8506598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8506598","identity":"rs-8506598","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}