scholarly journals The correlation between skeletal muscle index of the L3 vertebral body and malnutrition in patients with advanced lung cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiangliang Liu ◽  
Wei Ji ◽  
Kaiwen Zheng ◽  
Jin Lu ◽  
Lingyu Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Skeletal Muscle ◽  
Nutritional Assessment ◽  
Pearson Correlation ◽  
Statistical Significance ◽  
Advanced Lung Cancer ◽  
Severe Malnutrition ◽  
Forest Plot ◽  
Skeletal Muscle Index ◽  
Moderate Malnutrition

Abstract Background Studies have shown that the skeletal muscle index at the third lumbar vertebra (L3 SMI) had reasonable specificity and sensitivity in nutritional assessment and prognostic prediction in digestive system cancers, but its performance in lung cancer needs further investigation. Methods A retrospective study was performed on 110 patients with advanced lung cancer. The L3 SMI, the Patient-Generated Subjective Global Assessment score (PG-SGA score), body mass index (BMI), and serological indicators were analyzed. According to PG-SGA scores, patients were divided into severe malnutrition (≥9 points), mild to moderate malnutrition (≥3 points and ≤ 8 points), and no malnutrition (≤2 points) groups. Pearson correlation and logistic regression analysis were adopted to find factors related to malnutrition, and a forest plot was drawn. The receiver operating characteristic (ROC) curve was performed to compare the diagnostic values of malnutrition among factors, which were expressed by the area under curve (AUC). Results 1. The age of patients in the severe malnutrition group, the mild to moderate malnutrition group, and the no malnutrition group significantly differed, with mean ages of 63.46 ± 10.01 years, 60.42 ± 8.76 years, and 55.03 ± 10.40 years, respectively (OR = 1.062, 95%CI: 1.008 ~ 1.118, P = 0.024; OR = 1.100, 95%CI: 1.034 ~ 1.170, P = 0.002). Furthermore, the neutrophil to lymphocyte ratio (NLR) of the severe malnutrition group was significantly higher than that of the no malnutrition group, with statistical significance. The difference between the mild to moderate malnutrition group and the no malnutrition group were not statistically significant, with NLR of 4.07 ± 3.34 and 2.47 ± 0.92, respectively (OR = 1.657,95%CI: 1.036 ~ 2.649, P = 0.035). The L3 SMI of patients in the severe malnutrition and mild to moderate malnutrition groups were significantly lower than that of the patients in the no malnutrition group, with statistical significance. The L3 SMI of patients in the severe malnutrition group, mild to moderate malnutrition group, and no malnutrition group were 27.40 ± 4.25 cm2/m2, 38.19 ± 6.17 cm2/m2, and 47.96 ± 5.02 cm2/m2, respectively (OR = 0.600, 95%CI: 0.462 ~ 0.777, P < 0.001; OR = 0.431, 95%CI: 0.320 ~ 0.581, P < 0.001). 2. The Pearson correlation analysis showed that the PG-SGA score positively correlated with age (r = 0.296, P < 0.05) but negatively correlated with L3 SMI (r = − 0.857, P < 0.05). The L3 SMI was also negatively correlated with age (r = − 0.240, P < 0.05). 3. The multivariate analysis showed that the L3 SMI was an independent risk factor for malnutrition (OR = 0.446, 95%CI: 0.258 ~ 0.773, P = 0.004; OR = 0.289, 95%CI: 0.159 ~ 0.524, P < 0.001). Conclusion 1. The differences in the L3 SMI was statistically significant among advanced lung cancer patients with different nutritional statuses. 2. In the nutritional assessment of patients with lung cancer, the L3 SMI was consistent with the PG-SGA. 3. The L3 SMI is an independent predictor of malnutrition in patients with advanced lung cancer.

scholarly journals The Correlation between Skeletal Muscle Index of the L3 Vertebral Body and Malnutrition in Patients with Advanced Lung Cancer

2021 ◽  
Author(s):  
Xiangliang Liu ◽  
Wei Ji ◽  
Kaiwen Zheng ◽  
Jin Lu ◽  
Lingyu Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Pearson Correlation ◽  
Advanced Lung Cancer ◽  
Severe Malnutrition ◽  
Skeletal Muscle Index ◽  
Skeletal Muscle Mass Index ◽  
Moderate Malnutrition

Abstract Background: By analyzing the L3 skeletal muscle index in patients with advanced lung cancer, we determined whether this index could be an independent predictor of malnutrition in such patients and its role in nutritional assessments.Methods: Retrospective analysis was performed on patients with advanced lung cancer who received medical treatment at the Cancer Center of The First Hospital of Jilin University from January 2017 to July 2017, and relevant data were collated and analyzed. Abdominal CT was used to analyze the L3 skeletal muscle index, and PG-SGA score, body mass index (BMI), and serological indicators were analyzed. According to PG-SGA scores, patients were divided into severe malnutrition (≥9 points), mild to moderate malnutrition (≥3 points and ≤8 points), and no malnutrition (≤2 points) groups. Pearson correlation analysis was conducted between the skeletal muscle index and PG-SGA score, BMI, and laboratory test indices. Univariate and multivariate logistic regression analyses were conducted on the factors related to malnutrition, and a forest plot was drawn to identify malnutrition risk and protection factors.Results:1. The age of patients in the severe malnutrition group, the mild to moderate malnutrition group, and the no malnutrition group significantly differed, with mean ages of 63.46±10.01 years, 60.42±8.76 years, and 55.03±10.40 years, respectively. Furthermore, the NLR of the severe malnutrition group was significantly higher than that of the no malnutrition group, with statistical significance. The difference between the mild to moderate malnutrition group and the no malnutrition group were not statistically significant, with NLRs of 4.07±3.34, 3.09±1.47, and 2.47±0.92, respectively. The L3 skeletal muscle mass indices of patients in the severe malnutrition and mild to moderate malnutrition groups were significantly lower than that of the patients in the no malnutrition group, with statistical significance. The L3 skeletal muscle mass index of patients in the severe malnutrition group, mild to moderate malnutrition group, and no malnutrition group were 27.40±4.25 cm2/m2, 38.19±6.17 cm2/m2, and 47.96±5.02 cm2/m2, respectively.2.The multivariate analysis showed that the L3 skeletal muscle index was an independent risk factor for malnutrition (OR=0.627, p=0.000; OR=0.454, p=0.000).3.The Pearson correlation analysis showed that the PG-SGA score positively correlated with age (r=0.296), but negatively correlated with L3 skeletal muscle mass index (r=-0.857) (P≤0.05). The L3 skeletal muscle mass index also negatively correlated with age (r=-0.240) (P≤0.05).Conclusion：1. The differences in the L3 skeletal muscle index, age, PA, and NLR were statistically significant among patients with advanced lung cancer with different nutritional statuses.2. In the nutritional assessment of patients with lung cancer, the L3 skeletal muscle index was consistent with the PG-SGA.3. The L3 skeletal muscle index is an independent predictor of malnutrition in patients with advanced lung cancer.

scholarly journals The relationship between quality of life in sarcopenia and skeletal muscle index in patients with advanced lung cancer

2021 ◽  
Vol 11 (11) ◽  
pp. 100-107
Author(s):  
V. Kechedzhyiev
Keyword(s):  
Quality Of Life ◽  
Lung Cancer ◽  
Skeletal Muscle ◽  
Correlation Analysis ◽  
Advanced Lung Cancer ◽  
Pearson’S Correlation ◽  
Skeletal Muscle Index ◽  
Pearson's Correlation ◽  
The Relationship

Introduction. Today the relevance of sarcopenia is increasing in various types of malignant neoplasms.This syndrome is most common in patients with advanced forms of cancer and can adversely affect survival, treatment outcomes, and functional status. The prevalence of sarcopenia in patients with lung cancer is higher than in other types of malignant tumors. To understand the relationship between sarcopenia and quality of life is especially important for patients with advanced cancer. Aim. To assess the relationship between skeletal muscle index (SMI) and quality of life in sarcopenia in patients with advanced lung cancer. Materials and methods. A prospective analysis was carried out of 28 patients with advanced lung cancer who have applied to the “ONCOLIFE” Medical Center since the beginning of 2021. All patients had sarcopenia on CT scan. Skeletal muscle cross-sectional area analyzed using software ImageJ (National Institutes of Health, Bethesda, MD, USA). To determine the quality of life in sarcopenia a questionnaire SarQoL was used. Pearson's correlation analysis was used to assess the correlation between quality of life and SMI. Results. Pearson's correlation analysis showed a statistically significant positive correlation between quality of life and SMI (r = 0,451, р = 0,016, N=28). Body mass index (BMI) positively correlated with quality of life (r = 0,398, р = 0,036, N=28), and age negatively correlated with SMI (r = -0,391, р = 0,040, N=28). There was no statistically significant correlation between indicators such as BMI and SMI, as well as age and quality of life. Conclusions. Quality of life in sarcopenia statistically significantly correlates with SMI in patients with metastatic lung cancer. Early diagnosis of sarcopenia is essential for timely prescription of treatment aimed at maintaining and better muscle mass, which can improve cancer patients quality of life.

scholarly journals AB0185 PROSPECTIVE PROFILE OF URINE METABOLOME IN RHEUMATOID ARTHRITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1392.2-1392
Author(s):  
M. De Oliveira ◽  
P. V. Alabarse ◽  
M. Farinon ◽  
R. Cavalheiro Do Espírito Santo ◽  
R. Xavier
Keyword(s):  
Rheumatoid Arthritis ◽  
Skeletal Muscle ◽  
Disease Activity ◽  
Pearson Correlation ◽  
Statistical Significance ◽  
Resonance Spectroscopy ◽  
Metabolome Analysis ◽  
Orthogonal Projections ◽  
Urine Metabolome

Background:Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by increased mortality and associated with metabolic disorders. Since the metabolomic profile is known to vary in response to different inflammatory conditions, metabolome analysis could substantially improve diagnosis and prognosis of RA.Objectives:To analyze the urine metabolome profile in RA patients and correlate it with disease activity changes over 12 monthsMethods:Seventy-nine RA patients, according to ACR/EULAR 2010 classification criteria, between 40 and 70 years old, were recruited and followed for 12 months. Metabolome analysis was performed by Nuclear Magnetic Resonance spectroscopy (NMR), resulting in the identification of 93 metabolites in urine collected at the baseline and after 12 months. Frequency analysis, Pearson Correlation and Multivariate data analysis with orthogonal projections to latent structures (OPLS) method were performed and a statistical significance was considered as p<0.05.Results:The study population was characterized by the majority of women (86.7%), mean age of 56 years old, around 80% with positive anti-CCP or Rheumatoid Factor. During the one year of follow-up, there was no substantial variation in the DAS28 measurement (baseline: 3.8, after 12 months: 4.0). There was no significant correlation between the metabolome pattern and DAS28 score (p>0.05) over time. However, multivariate analysis (OPLS-DA) demonstrated an adequate differentiation of the population with 0.92 of accuracy (Q2: 0.72 and R2: 0.89).There was a significant increase of L-cysteine, choline, L-Phenylalanin, creatine, L-histidine, oxalacetic acid and xanthine, and a decrease of L-threonine, taurine, butyric and gluconic acid (p<0.05) during the follow-up, metabolites that are involved in the skeletal muscle metabolism.Conclusion:The observed biomarkers indicate,as expected, that the RA metabolic profile is associated with inflammation injury and skeletal muscle amino acid metabolism. Correlations with disease activity changes was compromised by the stable disease status during the 12 months. More studies evaluating correlations with skeletal muscle function and mass are underway.Acknowledgments:Disclosure of interest: Marianne Oliveira: None declared, Rafaela Santo: None declared, Mirian Farinon: None declared, Ricardo Xavier Consultant of: Abbvie, Pfizer, Novartis, Janssen, Lilly, RocheDisclosure of Interests:Marianne de Oliveira: None declared, Paulo Vinicius Alabarse: None declared, Mirian Farinon: None declared, Rafaela Cavalheiro do Espírito Santo: None declared, Ricardo Xavier Consultant of: AbbVie, Pfizer, Novartis, Janssen, Eli Lilly, Roche

Changes in skeletal muscle mass during palliative chemotherapy in patients with advanced lung cancer

2014 ◽  
Vol 54 (3) ◽  
pp. 340-348 ◽  
Author(s):  
Guro B. Stene ◽  
Jorunn L. Helbostad ◽  
Tore Amundsen ◽  
Sveinung Sørhaug ◽  
Harald Hjelde ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Palliative Chemotherapy ◽  
Advanced Lung Cancer

Serum IGFBP2 Level Is a New Candidate Biomarker of Severe Malnutrition in Advanced Lung Cancer

2019 ◽  
Vol 72 (5) ◽  
pp. 858-863
Author(s):  
Jie Dong ◽  
Yaqi Zeng ◽  
Ping Zhang ◽  
Chunlei Li ◽  
Yajun Chen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Advanced Lung Cancer ◽  
Severe Malnutrition

scholarly journals Skeletal muscle index is a useful tool for the nutritional assessment of patients with pancreatic and hepatobiliary cancer

HPB ◽  
2019 ◽  
Vol 21 ◽  
pp. S875-S876
Author(s):  
I. Lidoriki ◽  
D. Schizas ◽  
E. Mpaili ◽  
A. Michalinos ◽  
M. Vailas ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Nutritional Assessment ◽  
Skeletal Muscle Index ◽  
Hepatobiliary Cancer

scholarly journals Association of Body Composition and Sarcopenia with NASH in Obese Patients

2021 ◽  
Vol 10 (15) ◽  
pp. 3445
Author(s):  
Sophia Marie-Therese Schmitz ◽  
Lena Schooren ◽  
Andreas Kroh ◽  
Alexander Koch ◽  
Christine Stier ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Body Composition ◽  
Fat Mass ◽  
Inflammatory Diseases ◽  
Statistical Significance ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Obese Patients ◽  
Skeletal Muscle Index ◽  
P Values

Obese patients often suffer from sarcopenia or sarcopenic obesity (SO) that can trigger inflammatory diseases including non-alcoholic steatohepatitis (NASH). Sarcopenia and SO can be diagnosed through measuring parameters of body composition such as skeletal muscle mass (SMM), skeletal muscle index (SMI) and fat mass (FM) obtained by bioelectrical impedance analysis (BIA). The aim of this study was to assess the relationship of body composition and NASH in patients with obesity. A total of 138 patients with obesity that underwent bariatric surgery were included in this study. BIA was used to estimate body composition. A liver biopsy was taken intraoperatively and histological assessment of NASH was performed. A total of 23 patients (17%) were classified as NASH and 65 patients (47%) met the criteria for borderline NASH. Body mass index (BMI) was significantly higher in patients with NASH compared to borderline NASH and no NASH (56.3 kg/m2 vs. 51.6 kg/m2 vs. 48.6 kg/m2, p = 0.004). Concerning body composition, FM, but also SMM and SMI were significantly higher in patients with NASH (p-values 0.011, 0.005 and 0.006, resp.). Fat mass index (FMI) and weight-adjusted skeletal muscle index (SMI_weight) failed to reach statistical significance (p-values 0.067 and 0.661). In patients with obesity, higher FM were associated with NASH. Contrary to expectations, SMM and SMI were also higher in patients with NASH. Therefore, higher body fat, rather than sarcopenia and SO, might be decisive for development of NASH in patients with obesity.

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