Abbreviatures: BMI: body mass index; FFMI: fat-free mass index; FMI: fat mass index; p: percentile; SMM: skeletal muscle mass. Adapted from: Peine S, et al. Int J Body Composition Res. 2013;11(3):67–76 (22).

Dietary intake assessment

Trained nutritionists conducted three 24 hour recalls to all participants on non-consecutive and random days. The recalls were applied with an interval of three to four days. Two 24 hour recalls were applied on weekdays and one during the weekend(24).

The recalls collected data related to food preparation and portion sizes. To calculate energy and protein intake, the tables from the Mexican Equivalent Food System were used(25). Energy and protein intake were calculated, and individualized requirement calculations were conducted following the recommendations of the ESPEN practical guidelines for clinical nutrition in cancer(4).

Socioeconomic questionnaire

The socioeconomic levels index of the Mexican Association of Market Intelligence and Opinion Agencies (AMAI) was used. The households of the evaluated individuals were categorized into one of seven levels according to their capacity to meet the needs using the “NSE 2022 Rule.” The socioeconomic levels indicated by AMAI are as follows: A/B and C+: upper class; C: upper middle class; C-: middle class; D+: lower middle class; D: lower class; E: very low class(26).

Artificial intelligence

The authors declare the use of ChatGPT in the translation of the manuscript.

Statistical analysis

Descriptive statistics included percentages, medians, and confidence intervals. Normality analysis was conducted on quantitative variables using the Shapiro-Wilk test. The association between study groups was assessed using the chi-square test for qualitative variables. For quantitative variables, analysis of covariance was performed, adjusting anthropometric indicators for age and sex, and biochemical parameters for socioeconomic level. Pearson correlation was used to determine the confounding variables. The comparison of dietary intake and requirements between groups was conducted using the independent t-test for independent variables, and the paired t-test was used to compare intake and energy and protein requirements within the same group. A significance level of p <0.05 was used. Statistical analysis was performed using SPSS version 29 (IBM Corp., Armonk, NY, USA).

RESULTS

As part of the general characteristics, 50.00 % of the population with CRC were women, with the same characteristics maintained in the individuals without cancer. The average age in the CRC group was 59.50 years, and in the non-cancer group was 60 years. Significant differences were observed in occupation between both groups. Patients with CRC were mainly dedicated to housework (42.90 %), engaged in agriculture (21.40 %),
or were unemployed (21.40 %); whereas the majority of individuals without cancer were dedicated to housework (28.60 %), were retired (21.40 %), were office employees (14.30 %) or teachers (14.30 %). In the patients with CRC, the tumor was located in the colon in most patients (64.30 %), and 64.30 % required a colostomy after tumor resection. Almost 60.00 % of the patients with CRC were diagnosed at late stages (16.70 %
in stage III and 41.70 % in stage IV).

According to the PG-SGA, 78.60 % of the patients with CRC had some degree of undernutrition (42.90 %
moderate, 35.70 % severe), compared to the non-cancer group, where only 7.10 % of the population was detected with altered nutritional status (p <0.001). As shown in Table 2, 38.40 % of CRC patients were overweight or obese based on their BMI. Moreover, 75.00 % of CRC patients had a low PA compared to 28.60 % of the individuals without cancer (p = 0.001). Handgrip strength was also lower (p = 0.031) in CRC patients (91.70 %) compared to the non-cancer group (69.20 %). However, body composition indicators did not show significant differences between groups. The prevalence of sarcopenia was 58.00 % in CRC patients and 46.00 % in individuals without cancer, but they were not significantly different (p = 0.666).

More than half of the patients with CRC had anemia (Table 3), compared with the non-cancer group where no cases were found (p <0.001). Also, CRC patients had significantly lower concentrations of cholesterol (p = 0.005), total proteins (p <0.001), and albumin (p <0.001) compared to the individuals without cancer.

Table 2. Comparison of body composition indicators between CRC patients and individuals without cancer

Abbreviatures: BMI: body mass index; CI: Confidence interval; CRC: colorectal cancer patients; FFMI: fat-free mass index; FMI: fat mass index; HGS: handgrip strength; PA: phase angle; SMM: skeletal muscle mass. *Analysis of covariance adjusted for age and sex. Elaborated by the authors.

Table 3. Comparison of biochemical parameters related to nutritional status

Abbreviatures: CI: confidence interval; CRC: colorectal cancer. Reference values: hemoglobin: 12 g/dL (♀) and 13 g/dL (♂)(27); hematocrit: 37%-47% (♀) and 42%-52% (♂)(27). Platelets: >150-<450 × 103/mm3 (27); total lymphocyte count: adequate >2000 cells/mm3, mild depletion 1200-2000 cells/mm3 and moderate to severe depletion <1200 cells/mm3(28); glucose: <100 mg/dL(29); urea: 14,90-40,00 mg/dL(29); blood urea nitrogen (BUN): 6-20 mg/dL(29); creatinine: 0,60-1,10 mg/dL(29); total cholesterol: <200 mg/dL(30), hypocholesterolemia <160 mg/dL(31); triglycerides: >50, <150 mg/dL(31); total proteins: ≥ 6 g/dL(31); albumin: adequate >3,50 g/dL, mild depletion de 3-3,40 g/dL and moderate to severe depletion <3 g/dL(32). *Analysis of covariance adjusted for socioeconomic level. Elaborated by the authors.

For the dietary analysis, a comparison was made between the energy and protein intake of each group and their corresponding requirements, as well as a comparison of energy and protein intake between cancer patients and individuals without cancer. These results are shown in Table 4. CRC patients exhibit a significantly lower intake of energy and protein compared to their corresponding requirements. Additionally, CRC patients had a significantly lower energy intake compared to patients without cancer.

Table 4. Comparison between energy and protein intake with the recommended requirements for each group

Abbreviatures: CI: confidence interval; CRC: colorectal cancer; kcal: kilocalorie. Reference values: energy: cancer patients 25-30 kcal/kg(4), healthy adults <65 years 25 kcal/kg(33), older adults >65 years 30 kcal/kg(34); protein: cancer patients 1.0-1.5 kcal/kg(4); healthy adults <65 years 0.8-1.0 g/kg(33), older adults >65 years 1.0-1.2 g/kg(34). *Paired t-test. Comparison of variables within the same group. **Independent t-test. Comparison between groups. Elaborated by the authors.

DISCUSSION

In this study, patients with CRC had undernutrition at the time of their diagnosis, according to PG-SGA, PA, handgrip strength, and biochemical indicators. Additionally, a low intake of energy and protein was observed in this group. Patients with malignant tumors in the digestive tract are often particularly susceptible to undernutrition due to the symptoms associated with these neoplasms(6). Therefore, an early comprehensive nutritional assessment, together with medical treatment, is crucial for these patients(4, 5).

The high prevalence of undernutrition, found in approximately 80.00 % of CRC patients according to the PG-SGA at the time of their diagnosis, contrasts significantly with the low prevalence observed in the non-cancer group, which was 7.00 %. These findings are higher than those reported in previous studies. For example, Souza et al.(35) reported that 31.20 % of CRC patients were identified with nutritional deficiencies according to the PG-SGA; however, the population studied by these researchers corresponded to patients in different stages of oncological treatment.

According to the anthropometric and body composition assessment, it was observed that 38.40 % of CRC patients were overweight or obese based on their BMI. This finding is consistent with previous studies reporting prevalence of obesity ranging from 41.00 %(6) to 62.00 %(35) among CRC patients(35). According to Arends et al.(5), obesity is a prevalent condition in patients with various types of cancer, including CRC. In the present study, BMI only detected 15.40 % of patients with undernutrition. Gillis et al.(6) observed that, based solely on BMI, only 2.00 % of CRC patients were diagnosed with undernutrition. Therefore, since BMI does not account for the body composition of individuals, it is considered to be a tool for diagnosing undernutrition in cancer patients with low sensitivity. Hence, other assessment methods such as BIA, PA, or even handgrip strength have been proposed(5, 12).

No significant differences between CRC patients and individuals without cancer were observed in the body composition assessment by BIA. However, both groups had low values for FFMI, FMI, and SMM. Additionally, they showed low handgrip strength, resulting in a high prevalence of sarcopenia in both groups. Sarcopenia is a condition characterized by changes in skeletal muscle, primarily affecting strength, and also includes a decrease in muscle mass(23). In the non-cancer group, the presence of sarcopenia could be related to the age of the individuals evaluated. It has been observed that handgrip strength significantly declines from the fifth decade of life onwards(36). In the case of CRC patients, sarcopenia is likely secondary to the disease itself and the undernutrition they experience, in addition to age and a sedentary lifestyle(23). Sarcopenia, in both groups, increases the risk of falls and a lower quality of life. In addition, it also represents a higher risk of treatment toxicity for the CRC patients(37).

To our knowledge, there are no established cut-off points to determine undernutrition in CRC patients using PA. Souza et al.(35) observed that the PA was useful as a predictor of muscle alterations, with good diagnostic accuracy for detecting decreased muscular function and low muscle mass. A low PA indicates poor cellular membrane status, alterations in muscle composition and function, and cellular death(38). Additionally, a decrease in PA in patients with advanced cancer has been associated with decreased survival after adjusting for cancer type, weight loss, and inflammatory markers(39). According to Gupta et al.(20), a PA ≤ 5.57 ° in CRC patients is equivalent to a median survival of 8.6 months, while patients with PA >5.57 ° have a median survival of 40.40 months.

Barao et al.(40) observed that a PA >5 ° in elderly patients with CRC was associated with a decreased mortality risk. In the present study, 75.00 % of CRC patients had a PA below the established ranges for the disease, indicating cell membrane damage and cell death. A low PA brings as consequences muscle damage, lower functional status, decreased quality of life, and increased postoperative infections, complications that contribute to an increase in hospitalization time, morbidity, and low survival rate(38, 41, 42). Thus, PA may be considered an important indicator of nutritional status in patients with cancer that is more sensitive than BMI(12, 13). In addition, measuring PA is a practical, minimally invasive, and easily transportable method that allows for the detection of at-risk patients and monitoring of their progress throughout nutritional treatment. More studies are needed to determine potential cut-off points using PA for undernutrition diagnosis. Also, considering that these results were obtained right after the diagnosis of CRC and before the start of chemotherapy, it is crucial to carry out nutritional intervention from the time of diagnosis, as indicated by the corresponding guidelines(4).

The prevalence of anemia among the CRC patients that participated in the present study was high. Similar to our results, Ristescu et al.(43) found anemia in the 82.30 % of patients with CRC post-operation. Anemia is common in these patients due to gastrointestinal bleeding and to the characteristics of the tumor itself(44). The presence of anemia in CRC patients increases the risk of complications and mortality during the postoperative period and a higher risk of cancer recurrence, making its treatment vital from the moment of diagnosis(43).

The total lymphocyte count in blood has been used as a biomarker of nutritional status and as a prognostic factor in various clinical conditions, including cancer. Therefore, a decrease in the total lymphocyte count should be considered a risk factor in oncology(45). In this study, 85.70 % of CRC patients had a low total lymphocyte count. According to a previous study in hospitalized patients with cardiovascular disease and several types of cancer, a low total lymphocyte count may signify a higher risk of complications related to nutritional status(45). Additionally, this indicator is related to other biochemical parameters of nutritional status, such as plasma lipid concentration and hemoglobin, as well as inflammatory markers like albumin(45). For instance, in the case of the patients evaluated in this study, more than 80.00 % had low levels of cholesterol and total proteins. Additionally, a meta-analysis by Zhang et al.(31) observed that blood markers such as hemoglobin, cholesterol, and total proteins are useful biochemical indicators of undernutrition, even in the presence of inflammation.

In the case of CRC patients, the prevalence of hypoalbuminemia was high. Albumin allows the assessment of underlying inflammation, and since inflammation is associated with an increase in basal metabolism, albumin could be considered an indicator of nutritional risk(46). Therefore, analyzing different biochemical markers related to nutritional status increases the specificity and sensitivity when providing a nutritional diagnosis(31).

The energy and protein intake of CRC patients was found to be below their requirements. Furthermore, a low energy intake was observed in CRC patients when compared to healthy subjects. These results are similar to those observed in CRC patients in Portugal, where an approximate intake of 1335 kcal/day was reported(47). The low energy and protein intake may partially explain the undernutrition observed in the population and the loss of muscle mass, leading to increased susceptibility to infections, treatment interruptions, and prolonged hospital stays(47). Therefore, increasing energy and protein intake should be a priority for the successful medical treatment of these patients.

The present study has some limitations. First, the sample size is small, and due to the conditions of some patients, it was not possible to collect anthropometric, body composition, and dietary data completely. However, significant differences were detected in most study variables, including PA, and it was possible to demonstrate that patients recently diagnosed with CRC have undernutrition compared to a non-cancer group, which will allow for specific recommendations to be made for their treatment. To the best of our knowledge, this is the first study in patients with newly diagnosed CRC that evaluates the use of PA as an indicator of nutritional status, together with anthropometric, biochemical, and dietary parameters.

CONCLUSIONS

Compared to individuals without cancer, the proportion of undernutrition was higher in patients with CRC at the time of diagnosis. Also, PA detected more cases of undernutrition compared to BMI. The PG-SGA, PA, handgrip strength, biochemical, and dietary markers allowed for the detection of more than 70.00 % of cases of undernutrition compared to using BMI alone and compared to individuals without cancer. Therefore, in oncology, complete nutrition interventions that include follow-up using PA, together with medical treatment, are crucial so that patients with nutritional deficiencies or those at risk can be identified early and receive medical-nutritional treatment according to their requirements.

Declaration of authorship

Conception and design of the research, B.MR., OP.G. and JL.R.; data acquisition, B.MR., KM.GN., and R.HO.; data analysis and interpretation, B.MR., KM.GN.,and MC.C.; funding acquisition, OP.G. and KM.GN.; drafted the manuscript, B.MR. and OP.G.

Conflict of interest

The authors declare no conflicts of interest.

Acknowledgments

The authors would like to thank the patients who consented to participate in this study, the Director of HGQ, Dr. Leopoldo Francisco Espinoza Feregrino, the Head of Teaching and Research at HGQ, Dr. Arturo García Balderas, and Genoveva Castañeda, the Head of the Nutrition Department at HGQ, LN. Rigoberto Luna Hernández, as well as the entire team of nutritionists, oncological surgeons, and medical oncologists at HGQ. Special thanks to Dr. Roberto Esquivel García and Dr. Miriam Aracely Anaya Loyola from the Universidad Autónoma de Querétaro for their support from their respective areas.

Funding

This study was funded by the Special Projects Fund of the Rectorate (FOPER-222- FCN03102) and the Fund for the Development of Knowledge (FONDEC) of the Universidad Autónoma de Querétaro (FNN-2022-05).

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