ABSTRACT
CONTEXT: Global Leadership Initiative on Malnutrition (GLIM) and Patient-Generated Subjective Global Assessment (PG-SGA) are commonly used nutrition assessment tools, whose performance does not reach a consensus due to different and imperfect reference standards. OBJECTIVE: This study aimed to evaluate and compare the diagnostic accuracy of GLIM and PG-SGA, using a hierarchical Bayesian latent class model, in the absence of a gold standard. DATA SOURCES: A systematic search was undertaken in PubMed, Embase, and Web of Science from inception to October 2022. Diagnostic test studies comparing (1) the GLIM and/or (2) PG-SGA with "semi-gold" standard assessment tools for malnutrition were included. DATA EXTRACTION: Two authors independently extracted data on sensitivity, specificity, and other key characteristics. The methodological quality of each included study was appraised according to the criteria in the Quality Assessment of Diagnostic Accuracy Studies-2. DATA ANALYSIS: A total of 45 studies, comprising 20 876 individuals evaluated for GLIM and 11 575 for PG-SGA, were included. The pooled sensitivity was 0.833 (95% CI 0.744 to 0.896) for GLIM and 0.874 (0.797 to 0.925) for PG-SGA, while the pooled specificity was 0.837 (0.780 to 0.882) for GLIM and 0.778 (0.707 to 0.836) for PG-SGA. GLIM showed slightly better performance than PG-SGA, with a higher diagnostic odds ratio (25.791 vs 24.396). The diagnostic performance of GLIM was most effective in non-cancer patients with an average body mass index (BMI) of <24 kg/m2, followed by non-cancer patients with an average age of ≥60 years. PG-SGA was most powerful in cancer patients with an average age of <60 years, followed by cancer patients with an average BMI of <24 kg/m2. CONCLUSION: Both GLIM and PG-SGA had moderately high diagnostic capabilities. GLIM was most effective in non-cancer patients with a low BMI, while PG-SGA was more applicable in cancer patients. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration No. CRD42022380409.
ABSTRACT
Observational studies of diet-related vitamins and lymphoma risk results were inconsistent. Our study aimed to estimate the causality between dietary vitamin intake and lymphoma through a Mendelian randomisation (MR) study. We enrolled dietary-related retinol, vitamin C, vitamin E, vitamin B6 and vitamin B12 as exposures of interest, with Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL) as the outcome. The causal effects were estimated using inverse variance weighting (IVW), MR-Egger regression analysis and weighted median, supplemented by sensitivity analyses. The results revealed that genetically predicted dietary vitamin B12 intake was associated with a reduced HL risk (OR = 0.22, 95% CI 0.05-0.91, p = 0.036). The Q test did not reveal heterogeneity, the MR-Egger test showed no significant intercepts, and the leave-one-out (LOO) analysis did not discover any SNP that affect the results. No causal relationship about dietary vitamin intake on the NHL risk was observed.
Subject(s)
Lymphoma , Vitamins , Humans , Diet/adverse effects , Nutritional Status , Vitamin A , Vitamin B 12ABSTRACT
Our objective was to identify the optimal method to assess reduced muscle mass (RMM) using the Global Leadership Initiative on Malnutrition (GLIM) approach and investigate the roles of the GLIM approach in nutrition assessment and survival prediction in colorectal cancer (CRC) patients. During a median follow-up period of 4.2 (4.0, 4.4) years, a development cohort of 3612 CRC patients with a mean age of 64.09 ± 12.45 years was observed, as well as an external validation cohort of 875 CRC patients. Kaplan−Meier curves and multivariate Cox regression were adopted to analyze the association between GLIM-diagnosed malnutrition and the overall survival (OS) of CRC patients. A nomogram predicting individualized survival was constructed based on independent prognostic predictors. The concordance index, calibration curve, and decision curve were applied to appraise the discrimination, accuracy, and clinical efficacy of the nomogram, respectively. Patients diagnosed with severe malnutrition based on either the mid-arm muscle circumference (MAMC) or body weight-standardized hand grip strength (HGS/W) method had the highest mortality hazard ratio (HR, 1.51; 95% CI, 1.34−1.70; p < 0.001). GLIM-defined malnutrition was diagnosed in 47.6% of patients. Severe malnutrition was an independent mortality risk factor for OS (HR, 1.25; 95% CI, 1.10−1.42; p < 0.001). The GLIM nomogram showed good performance in predicting the survival of CRC patients and was clinically beneficial. Our findings support the effectiveness of GLIM in diagnosing malnutrition and predicting OS in CRC patients.
Subject(s)
Colorectal Neoplasms , Malnutrition , Humans , Middle Aged , Aged , Hand Strength , East Asian People , Malnutrition/diagnosis , Body Weight , Nutrition Assessment , Muscles , Nutritional StatusABSTRACT
Peanut (Arachis hypogaea L.) is an important source of edible oil and protein for human nutrition. The quality of peanut seed oil is mainly determined by the composition of fatty acids, especially the contents of oleic acid and linoleic acid. Improving the composition of fatty acids in the seed oil is one of the main objectives for peanut breeding globally. To uncover the genetic basis of fatty acids and broaden the genetic variation in future peanut breeding programs, this study used genome-wide association studies (GWAS) to identify loci associated with target traits and developed diagnostic marker. The contents of eight fatty acid components of the Chinese peanut mini-core collection were measured under four environments. Using the phenotypic information and over one hundred thousand single nucleotide polymorphisms (SNPs), GWAS were conducted to investigate the genetics basis of fatty acids under multi-environments. Overall, 75 SNPs were identified significant trait associations with fatty acid components. Nineteen associations were repeatedly identified in multiple environments, and 13 loci were co-associated with two or three traits. Three stable major associated loci were identified, including two loci for oleic acid and linoleic acid on chromosome A09 [mean phenotypic variation explained (PVE): 38.5%, 10.35%] and one for stearic acid on B06 (mean PVE: 23%). According to functional annotations, 21 putative candidate genes related to fatty acid biosynthesis were found underlying the three associations. The allelic effect of SNP A09-114690064 showed that the base variation was highly correlated with the phenotypic variation of oleic acid and linoleic acid contents, and a cost-effective Kompetitive allele-Specific PCR (KASP) diagnostic marker was developed. Furthermore, the SNP A09-114690064 was found to change the cis-element CAAT (-) in the promoter of ahFAD2A to YACT (+), leading dozens of times higher expression level. The enhancer-like activity of ahFAD2A promoter was identified that was valuable for enriching the regulation mechanism of ahFAD2A. This study improved our understanding on the genetic architecture of fatty acid components in peanut, and the new effective diagnostic marker would be useful for marker-assisted selection of high-oleic peanut breeding.
