Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

BACKGROUND: Body weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. METHODS: This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight-related indicators and compared their prognostic performance using Harrell's C-index, integrated discrimination improvement, continuous net reclassification improvement and time-dependent C-index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan-Meier analysis and multivariable-adjusted Cox regression models. RESULTS: The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (PRWC < 0.001, Pnon-linear < 0.001). Univariate survival analysis showed that the peridiagnosis RWC groups could represent distinct mortality risk stratifications (P < 0.001). Multivariable survival analysis showed that, compared with the maintenance group (weight change < 5%), the significant (gain >10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5-10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5-10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. CONCLUSIONS: The prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Value of the modified Patient-Generated Subjective Global Assessment in indicating the need for nutrition intervention and predicting overall survival in patients with malignant tumors in at least two organs.

BACKGROUND: Although the Patient-Generated Subjective Global Assessment (PG-SGA) is a reference standard used to assess a patient's nutrition status, it is cumbersome to administer. The aim of the present study was to estimate the value of a simpler and easier-to-use modified PG-SGA (mPG-SGA) to evaluate the nutrition status and need for intervention in patients with malignant tumors present in at least two organs. METHODS: A total of 591 patients (343 male and 248 female) were included from the INSCOC study. A Pearson correlation analysis was conducted to assess the correlation between the mPG-SGA and nutrition-related factors, with the optimal cut-off defined by a receiver operating characteristic curve (ROC). The consistency between the mPG-SGA and PG-SGA was compared in a concordance analysis. A survival analysis was used to determine the effects of nutritional intervention among different nutrition status groups. Univariable and multivariable Cox analyses were applied to evaluate the association of the mPG-SGA with the all-cause mortality. RESULTS: The mPG-SGA showed a negative association with nutrition-related factors. Individuals with an mPG-SGA ≥ 5 (rounded from 4.5) were considered to need nutritional intervention. Among the malnourished patients (mPG-SGA ≥ 5), the overall survival (OS) of those who received nutrition intervention was significantly higher than that of patients who did not. However, the OS was not significantly different in the better-nourished patients (mPG-SGA < 5). CONCLUSION: Our findings support that the mPG-SGA is a feasible tool that can be used to guide nutritional interventions and predict the survival of patients with malignant tumors affecting at least two organs.

Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study.

OBJECTIVES: The concept of possible sarcopenia (PS) was recently introduced to enable timely intervention in settings without the technologies required to make a full diagnosis of sarcopenia. This study aimed to investigate the association between PS and all-cause mortality in patients with solid cancer. DESIGN: Retrospective observational study. SETTING AND PARTICIPANTS: 13,736 patients with 16 types of solid cancer who were ≥18 years old. MEASUREMENTS: The presence of both a low calf circumference (men <34 cm or women <33 cm) and low handgrip strength (men <28 kg or women <18 kg) was considered to indicate PS. Harrell's C-index was used to assess prognostic value and the association of PS with mortality was estimated by calculating multivariable-adjusted hazard ratios (HRs). RESULTS: The study enrolled 7207 men and 6529 women (median age = 57.8 years). During a median follow-up of 43 months, 3150 deaths occurred. PS showed higher Harrell's C-index (0.549, 95%CI = [0.541, 0.557]) than the low calf circumference (0.541, 95%CI = [0.531, 0.551], P = 0.037) or low handgrip strength (0.542, 95%CI = [0.532, 0.552], P = 0.026). PS was associated with increased mortality risk in both univariate (HR = 1.587, 95%CI = [1.476, 1.708]) and multivariable-adjusted models (HR = 1.190, 95%CI = [1.094, 1.293]). Sensitivity analyses showed that the association of PS with mortality was robust in different covariate subgroups, which also held after excluding those patients who died within the first 3 months (HR = 1.162, 95%CI = [1.060, 1.273]), 6 months (HR = 1.150, 95%CI = [1.039, 1.274]) and 12 months (HR = 1.139, 95%CI = [1.002, 1.296]) after enrollment. CONCLUSION: PS could independently and robustly predict all-cause mortality in patients with solid cancer. These findings imply the importance of including PS assessment in routine cancer care to provide significant prognostic information to help mitigate sarcopenia-related premature deaths.

Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study.

BACKGROUND & AIMS: The present study aimed to compare the ability of the GLIM criteria, PG-SGA and mPG-SGA to diagnose malnutrition and predict survival among Chinese lung cancer (LC) patients. METHODS: This was a secondary analysis of a multicenter, prospective, nationwide cohort study, 6697 LC inpatients were enrolled between July 2013 and June 2020. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and quadratic weighted Kappa coefficients were calculated to compare the ability to diagnose malnutrition. There were 754 patients who underwent follow-up for a median duration of 4.5 years. The associations between the nutritional status and survival were analyzed by the Kaplan-Meier method and multivariable Cox proportional hazard regression models. RESULTS: The median age of LC patients was 60 (53, 66), and 4456 (66.5%) were male. There were 617 (9.2%), 752 (11.2%), 1866 (27.9%), and 3462 (51.7%) patients with clinical stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ LC, respectively. Malnutrition was present in 36.1%-54.2% (as evaluated using different tools). Compared with the PG-SGA (used as the diagnostic reference), the sensitivity of the mPG-SGA and GLIM was 93.7% and 48.3%; the specificity was 99.8% and 78.4%; and the AUC was 0.989 and 0.633 (P < 0.001). The weighted Kappa coefficients were 0.41 for the PG-SGA vs. GLIM, 0.44 for the mPG-SGA vs. GLIM, and 0.94 for the mPG-SGA vs PG-SGA in patients with stage Ⅰ-Ⅱ LC. These values were respectively 0.38, 0.39, and 0.93 in patients with stage Ⅲ-Ⅳ of LC. In a multivariable Cox analysis, the mPG-SGA (HR = 1.661, 95%CI = 1.348-2.046, P < 0.001), PG-SGA (HR = 1.701, 95%CI = 1.379-2.097, P < 0.001) and GLIM (HR = 1.657, 95%CI = 1.347-2.038, P < 0.001) showed similar death hazard ratios. CONCLUSIONS: The mPG-SGA provides nearly equivalent power to predict the survival of LC patients as the PG-SGA and the GLIM, indicating that all three tools are applicable for LC patients. The mPG-SGA has the potential to be an alternative replacement for quick nutritional assessment among LC patients.

Triceps skinfold-albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study.

BACKGROUND: The fat mass and nutritional status play important roles in the onset and progression of cancer cachexia. The present study evaluated the joint prognostic value of the fat mass, as indicated by the triceps skinfold thickness (TSF), and the serum albumin level, for mortality in patients with cancer cachexia. METHODS: We performed a multicentre cohort study including 5134 patients with cancer cachexia from January 2013 to April 2019. The sum of the TSF (mm) and serum albumin (g/L) was defined as the triceps skinfold-albumin index (TA). Harrell's C index, a time-dependent receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the prognostic performance of the TA and other indices. Optimal stratification was used to identify the thresholds to define a low TA, and the association of the TA with all-cause mortality was evaluated using Kaplan-Meier analysis and Cox proportional hazard regression models. RESULTS: The study enrolled 2408 women and 2726 men with a median age of 58.6 years and a median follow-up of 44 months. A total of 607 women (TA < 49.9) and 817 men (TA < 45.6) were classified as having a low TA. The TA showed better discrimination performance (C index = 0.621, 95% confidence interval [CI] = 0.607-0.636) to predict mortality in patients with cancer cachexia than the handgrip strength, the nutritional risk index, the prognostic nutritional index, the controlling nutritional status index, the systemic immune-inflammation index, the modified Glasgow prognostic score, and the TSF or albumin alone in the study population (all P < 0.05). The 1-, 3- and 5-year time-dependent ROC analyses (AUC = 0.647, 0.625 and 0.630, respectively) showed that the TA had the highest prognostic value among all indices investigated (all P < 0.05). Univariate analysis showed that a lower TA was associated with an increased death hazard (hazard ratio [HR] = 1.859, 95% CI = 1.677-2.062), regardless of the sex and cancer type. Multivariable survival analysis showed that a lower TA was independently associated with an increased death hazard (HR = 1.381, 95% CI = 1.223-1.560). This association was significantly strengthened in patients who did not receive curative chemotherapy (HR = 1.491, 95% CI = 1.298-1.713), those who had higher serum total protein levels (HR = 1.469, 95% CI = 1.284-1.681) and those with better physical performance (HR = 1.453, 95% CI = 1.271-1.662). CONCLUSIONS: This study defined and evaluated a new prognostic index, the TA, which may improve the selection of intervention strategies to optimize the survival of patients with cancer cachexia.

Kruppel-like Factors 3 Regulates Migration and Invasion of Gastric Cancer Cells Through NF-κB Pathway.

Context: The poorly understood regulatory mechanisms impede gastric cancer therapy. Kruppel-like factors (KLFs) are associated with the development of various tumors, The studies on the role of the KLF transcription factor 13 (KLF13) in gastric cancer progression haven't been studied. Objective: The current study aimed to investigate the role of KLF13 in the migration and invasion of gastric cancer and the regulatory mechanism of KLF13 in gastric cancer progression. Design: The research team performed a laboratory study. Setting: The study took place at the Zengcheng District People's Hospital of Guangzhou in Zengcheng, China. Participants: In addition to using normal gastric cells, GES1, and seven gastric cancer cell lines, the research team compared the fresh, gastric cancer tissues (T) and paired, adjacent, noncancerous gastric tissues (ANT) from eight patients undergoing surgical resection at the hospital. The research team also downloaded the data for 33 gastric cancer tissues and adjacent, normal gastric tissues from the Cancer Genome Atlas' TCGA database. Intervention: The research team used: (1) short hairpin RNAs (shRNAs) to knock down KLF13, (2) wound healing and transwell invasion analyses to determine the effects of KLF13 on the migration and invasion of gastric cancer, and (3) a Luciferase reporter assay to determine the effects of KLF13 on nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activity. Results: KLF13 was upregulated in gastric cancer cells and tissues, and the patients with a high KLF13 expression had poor outcome. Downregulation of KLF13 significantly inhibited the migration and invasion of gastric cancer cells. Mechanistically, downregulation of KLF13 significantly inhibited NF-κB activity, and its targets such as: (1) snail family transcriptional repressor 1 (SNAI1 or Snail), (2) snail family transcriptional repressor 2 (SNAI2 or Slug), (3) zinc finger e-box binding homeobox 1 (ZEB1), (4) Smad interacting protein 1 (Sip1), (5) twist family basic helix-loop-helix (BHLH) transcription factor (Twist), (6) matrix metallopeptidase 2 (MMP2), and (7) MMP9. Tumor necrosis factor alpha (TNF-α) can activate NF-κB. Treating with TNF-α can reverse the effects of KLF13 downregulation on migration and invasion, confirming that KLF13 promotes the migration and invasion of gastric cancer cells through activating the NF-κB pathway. Conclusions: KLF13 promoted the migration and invasion of gastric cancer cells through activating the NF-κB pathway, providing a new target for gastric cancer therapy.

GLIM-defined malnutrition and overall survival in cancer patients: A meta-analysis.

BACKGROUND: Malnutrition defined by the Global Leadership Initiative on Malnutrition (GLIM) has been associated with cancer mortality, but the effect is limited and inconsistent. We performed this meta-analysis aiming to assess this relationship in patients with cancer. METHODS: We systematically searched Embase, PubMed, Web of Science, Cochrane, CINAHL, CNKI, Wanfang, and VIP databases from January 1, 2019, to July 1, 2022. Studies evaluating the prognostic effect of GLIM-defined malnutrition on cancer survival were included. A fixed-effect model was fitted to estimate the combined hazard ratio (HR) with a 95% CI. Heterogeneity of studies was analyzed using the I2 statistic. Quality assessment were performed using the Newcastle-Ottawa Scale (NOS) and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool. RESULTS: The search strategy identified 4378 articles in all databases combined. Nine studies (8829 patients) meeting the inclusion criteria were included for quantitative analysis. Meta-analysis revealed significant associations between GLIM-defined pooled malnutrition (HR = 1.75; 95% CI, 1.43-2.15), moderate malnutrition (HR = 1.44; 95% CI, 1.29-1.62), and severe malnutrition (HR = 1.79; 95% CI, 1.58-2.02) with all-cause mortality. Sensitivity analysis supported the robustness of these associations. The between-study heterogeneity was low (all I2 < 50%), and study quality assessed with NOS was high (all scores > 6). The evidence quality according to the GRADE tool was very low. CONCLUSIONS: Our meta-analysis suggests a significant negative association of malnutrition, as defined by the GLIM, with overall survival in patients with cancer. However, definitive conclusions cannot be made, owing to the low quality of the source data.

Associations between serum glucose, insulin, insulin resistance and the risk of incident primary liver cancer or chronic liver disease mortality: a nested case-control study.

BACKGROUND: To evaluate the associations between pre-diagnostic levels of serum insulin, glucose and insulin resistance (HOMA-IR) and future risk of incident primary liver cancer (PLC) or chronic liver disease (CLD)-related mortality. METHODS: We used a nested case-control design to evaluate subjects over 22 years of follow-up. Glucose, insulin, and three markers of hepatitis B virus (HBV) and hepatitis C virus were measured in fasting baseline serum from 119 incident PLCs, 157 CLD-death cases and 512 matched controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression to estimate the associations between insulin, glucose, HOMA-IR and the risk of PLC or CLD death. RESULTS: Compared with the lowest quartile of insulin, multivariable adjusted models showed that subjects in the highest quartile had elevated odds of developing PLC (ORQ4/Q1 = 2.42, 95% CI = 1.26-4.75, Ptrend = 0.007), particularly in HBV-positive subjects (Pinteraction = 0.040), and of CLD death (ORQ4/Q1 = 1.80, 95% CI = 1.02-3.21, Ptrend = 0.018). For glucose, in the HBV-positive group, subjects in the fourth quartile had an increased risk of PLC (ORQ4/Q1 = 2.18, 95% CI = 1.07-4.60, Ptrend = 0.009), and of CLD mortality (ORQ4/Q1 = 1.75, 95% CI = 0.95-3.28, Ptrend = 0.019). Subjects with the highest HOMA-IR values had a threefold risk of developing PLC (ORQ4/Q1 = 2.94, 95% CI = 1.54-5.87, Ptrend = 0.001), and a twofold risk of CLD death (ORQ4/Q1 = 2.20, 95% CI = 1.25-3.94, Ptrend = 0.005). CONCLUSIONS: We found that serum insulin and HOMA-IR could potentially be risk factors for PLC or CLD death.

Development and validation of an online dynamic nomogram system for predicting cancer cachexia among inpatients: a real-world cohort study in China.

BACKGROUND: Early recognition of cachexia is essential for ensuring the prompt intervention and treatment of cancer patients. However, the diagnosis of cancer cachexia (CC) usually is delayed. This study aimed to establish an accurate and high-efficiency diagnostic system for CC. METHODS: A total of 4834 cancer inpatients were enrolled in the INSCOC project from July 2013 to June 2020. All cancer patients in the study were randomly assigned to a development cohort (n=3384, 70%) and a validation cohort (n=1450, 30%). The least absolute shrinkage and selection operator (LASSO) method and multivariable logistic regression were used to identify the independent predictors for developing the dynamic nomogram. Discrimination and calibration were adopted to evaluate the ability of nomogram. A decision curve analysis (DCA) was used to evaluate clinical use. RESULTS: We combined 5 independent predictive factors (age, NRS2002, PG-SGA, QOL by the QLQ-C30, and cancer categories) to establish the online dynamic nomogram system. The C-index, sensitivity, and specificity of the nomo-system to predict CC was 0.925 (95%CI, 0.916-0.934, P < 0.001), 0.826, and 0.862 in the development set, while the values were 0.923 (95%CI, 0.909-0.937, P < 0.001), 0.854, and 0.829 in the validation set. In addition, the calibration curves of the diagnostic nomogram also presented good agreement with the actual situation. DCA showed that the model is clinically useful and can increase the clinical benefit in cancer patients. CONCLUSIONS: This study developed an online dynamic nomogram system with outstanding accuracy to help clinicians and dieticians estimate the probability of cachexia. This simple-to-use online nomogram can increase the clinical benefit in cancer patients and is expected to be widely adopted.

Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge.

BACKGROUND: Diagnosing cancer cachexia relies extensively on patient-reported historic weight, and failure to accurately recall this information can lead to severe underestimation of cancer cachexia. OBJECTIVES: The present study aimed to develop inexpensive tools to facilitate the identification of cancer cachexia in patients without weight loss information. METHODS: This multicenter cohort study included 12,774 patients with cancer. Cachexia was retrospectively diagnosed using Fearon et al.'s framework. Baseline clinical features, excluding weight loss, were modeled to mimic a situation where the patient is unable to recall their weight history. Multiple machine learning (ML) models were trained using 75% of the study cohort to predict cancer cachexia, with the remaining 25% of the cohort used to assess model performance. RESULTS: The study enrolled 6730 males and 6044 females (median age = 57.5 y). Cachexia was diagnosed in 5261 (41.2%) patients and most diagnoses were made based on the weight loss criterion. A 15-variable logistic regression (LR) model mainly comprising cancer types, gastrointestinal symptoms, tumor stage, and serum biochemistry indexes was selected among the various ML models. The LR model showed good performance for predicting cachexia in the validation data (AUC = 0.763; 95% CI: 0.747, 0.780). The calibration curve of the model demonstrated good agreement between predictions and actual observations (accuracy = 0.714, κ = 0.396, sensitivity = 0.580, specificity = 0.808, positive predictive value = 0.679, negative predictive value = 0.733). Subgroup analyses showed that the model was feasible in patients with different cancer types. The model was deployed as an online calculator and a nomogram, and was exported as predictive model markup language to permit flexible, individualized risk calculation. CONCLUSIONS: We developed an ML model that can facilitate the identification of cancer cachexia in patients without weight loss information, which might improve decision-making and lead to the development of novel management strategies in cancer care. This trial was registered at https://www.chictr.org.cn as ChiCTR1800020329.

De novo Creation and Assessment of a Prognostic Fat-Age-Inflammation Index "FAIN" in Patients With Cancer: A Multicenter Cohort Study.

Background and Aims: Malnutrition is highly prevalent and is related to multiple impaired clinical outcomes in cancer patients. This study aimed to de novo create an objective, nutrition-related index specially for prognostic purposes in oncology populations. Methods: We performed a multicenter cohort study including 14,134 cancer patients. The prognostic impact for each baseline characteristic was estimated by calculating Harrell's C-index. The optimal parameters reflecting the nutritional and inflammatory impact on patients' overall survival were selected to develop the fat-age-inflammation (FAIN) index. The associations of the FAIN with the nutritional status, physical performance, quality of life, short-term outcomes and mortality of patients were comprehensively evaluated. Independent external validation was performed to further assess the prognostic value of the FAIN. Results: The study enrolled 7,468 men and 6,666 women with a median age of 57 years and a median follow-up of 42 months. The FAIN index was defined as: (triceps skinfold thickness + albumin) / [age + 5 × (neutrophil count/lymphocyte count)]. There were significant associations of the FAIN with the nutritional status, physical performance, quality of life and short-term outcomes. The FAIN also showed better discrimination performance than the Nutritional Risk Index, the Prognostic Nutritional Index and the Controlling Nutritional Status index (all P < 0.05). In multivariable-adjusted models, the FAIN was independently associated with a reduced death hazard both as a continuous variable (HR = 0.57, 95%CI = 0.47-0.68) and per one standard deviation (HR = 0.83, 95%CI = 0.78-0.88). External validation in a multicenter lung cancer cohort (n = 227) further confirmed the prognostic value of the FAIN. Conclusions: This study created and assessed the prognostic FAIN index, which might act as a feasible option to monitor the nutritional status and help develop intervention strategies to optimize the survival outcomes of cancer patients.

Accuracy of the GLIM criteria for diagnosing malnutrition: A systematic review and meta-analysis.

BACKGROUND & AIMS: Although malnutrition remains a global public health concern, and has proved to be a major contributor to death and illness, there has been a foundational lack of a gold standard for diagnostic testing for clinical application. The Global Leadership Initiative on Malnutrition (GLIM) criteria were established to normalize the diagnosis of malnutrition, but their use remains controversial. Therefore, we carried out a meta-analysis based on the published literature to assess the accuracy of the GLIM criteria for diagnosing malnutrition. METHODS: We utilized publication databases (including CENTRAL, MEDLINE, and EMBASE) to acquire research studies published from the initial use of the GLIM criteria in 2019 until January 22, 2022 that used the criteria to diagnose malnutrition. We conducted this meta-analysis with reference to the recommendations from the PRISMA-DTA statement. We separately calculated the amalgamated sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and AUC with 95%CI for the GLIM criteria. Then, we aggregated and presented the data by drawing forest plots to assess the real accuracy of the criteria. A subgroup analysis was also carried out to identify the potential sources of heterogeneity. RESULTS: After the initial search of the CENTRAL, EMBASE, and MEDLINE databases, a total of 451 unique studies were identified. Twenty studies met our selection standards and 10,781 total patients were included in the meta-analysis. We noted that 4761 of the 10,781 patients (44.2%) were malnourished. The amalgamated sensitivity of the GLIM criteria was 0.72 (95%CI, 0.64-0.78), the specificity was 0.82 (95%CI, 0.72-0.88), the PLR was 3.9 (95%CI, 2.6-6.1), NLR was 0.35 (95%CI, 0.27-0.44), DOR was 11 (95%CI, 6-20), and AUC was 0.82 (95%CI, 0.79-0.85). Based on the results of a subgroup analysis using the SGA as a reference standard, the GLIM criteria had better diagnostic value (sensitivity, 0.81; specificity, 0.80; DOR, 17; AUC, 0.87). CONCLUSIONS: The GLIM criteria have high diagnostic accuracy for distinguishing patients with malnutrition, and the GLIM criteria seem to have the potential to be used as a gold standard for diagnosing malnutrition in clinical practice. Moreover, the subgroup analysis showed a better diagnostic value for the GLIM criteria compared to the SGA used as a reference standard. Large-scale diagnostic trials and additional refinements to simplify the criteria are urgently needed to increase the clinical utilization of the GLIM criteria in the future.

Relationships between serum iron and liver diseases in nutrition intervention trials: A nested case-control study.

BACKGROUND: Serum iron is associated with the risk of several diseases. However, limited prospective studies have been performed between serum iron and the subsequent risk of chronic liver disease (CLD) and primary liver cancer (PLC) incidence. METHODS: We performed a nested case-control study using data from the Linxian Nutrition Intervention Trials among participants who developed PLC incidence or died from CLD over 22-years of follow-up. We calculated the odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the risk of PLC incidence or CLD death in different quintile of baseline serum iron using logistic regression. RESULTS: Individuals with serum iron in the highest quintile, compared to those in the second quintile (the reference), had an increased risk of CLD mortality (OR=2.02, 95% CI=1.27-3.27, Ptrend=0.011). The association was stronger among HCV-positive participants (Pinteraction=0.005). For PLC incidence, the risk estimates were above one, but not statistically significant (all P > 0.05). CONCLUSIONS: A significant positive association was found between serum iron and the risk of CLD-related mortality, especially in HCV-positive subjects. Our results suggest that serum iron plays a risk role in CLD death but not in PLC incidence.

Several anthropometric measurements and cancer mortality: predictor screening, threshold determination, and joint analysis in a multicenter cohort of 12138 adults.

BACKGROUND: Anthropometric measurements (AMs) are cost-effective surrogates for evaluating body size. This study aimed to identify the optimal prognostic AMs, their thresholds, and their joint associations with cancer mortality. METHODS: We performed an observational cohort study including 12138 patients with cancer at five institutions in China. Information on demographics, disease, nutritional status, and AMs, including the body mass index, mid-arm muscle circumference, mid-arm circumference, handgrip strength, calf circumference (CC), and triceps-skinfold thickness (TSF), was collected and screened as mortality predictors. The optimal stratification was used to determine the thresholds to categorize those prognostic AMs, and their associations with mortality were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HRs). RESULTS: The study included 5744 females and 6394 males with a mean age of 56.9 years. The CC and TSF were identified as better mortality predictors than other AMs. The optimal thresholds were women 30 cm and men 32.8 cm for the CC, and women 21.8 mm and men 13.6 mm for the TSF. Patients in the low CC or low TSF group had a 13% (HR = 1.13, 95% CI = 1.03-1.23) and 22% (HR = 1.22, 95% CI = 1.12-1.32) greater mortality risk compared with their normal CC/TSF counterparties, respectively. Concurrent low CC and low TSF showed potential joint effect on mortality risk (HR = 1.39, 95% CI = 1.25-1.55). CONCLUSIONS: These findings support the importance of assessing the CC and TSF simultaneously in hospitalized cancer patients to guide interventions to optimize their long-term outcomes.

Fat mass assessment using the triceps skinfold thickness enhances the prognostic value of the Global Leadership Initiative on Malnutrition criteria in patients with lung cancer.

The present study evaluated whether fat mass assessment using the triceps skinfold (TSF) thickness provides additional prognostic value to the Global Leadership Initiative on Malnutrition (GLIM) framework in patients with lung cancer (LC). We performed an observational cohort study including 2672 LC patients in China. Comprehensive demographic, disease and nutritional characteristics were collected. Malnutrition was retrospectively defined using the GLIM criteria, and optimal stratification was used to determine the best thresholds for the TSF. The associations of malnutrition and TSF categories with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HR). Malnutrition was identified in 808 (30·2 %) patients, and the best TSF thresholds were 9·5 mm in men and 12 mm in women. Accordingly, 496 (18·6 %) patients were identified as having a low TSF. Patients with concurrent malnutrition and a low TSF had a 54 % (HR = 1·54, 95 % CI = 1·25, 1·88) greater death hazard compared with well-nourished individuals, which was also greater compared with malnourished patients with a normal TSF (HR = 1·23, 95 % CI = 1·06, 1·43) or malnourished patients without TSF assessment (HR = 1·31, 95 % CI = 1·14, 1·50). These associations were concentrated among those patients with adequate muscle mass (as indicated by the calf circumference). Additional fat mass assessment using the TSF enhances the prognostic value of the GLIM criteria. Using the population-derived thresholds for the TSF may provide significant prognostic value when used in combination with the GLIM criteria to guide strategies to optimise the long-term outcomes in patients with LC.

Identification of potential biomarkers for diagnosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has a high mortality rate owing to its complexity. Identification of abnormally expressed genes in HCC tissues compared to those in normal liver tissues is a viable strategy for investigating the mechanisms of HCC tumorigenesis and progression as a means of developing novel treatments. A significant advantage of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) is that the data therein were collected from different independent researchers and may be integrated, allowing for a more robust data analysis. Accordingly, in the present study, the gene expression profiles for HCC and control samples were downloaded from the GEO and TCGA. Functional enrichment analysis was performed using a Metascape dataset, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins (STRING) online database. The prognostic value of mRNA for HCC was assessed using the Kaplan-Meier Plotter, a public online tool. A gene mRNA heatmap and DNA amplification numbers were obtained from cBioPortal. A total of 2,553 upregulated genes were identified. Functional enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly accumulated in metabolism of RNA and the cell cycle. Considering the complexity and heterogeneity of the molecular alterations in HCC, multiple genes for the prognostication of patients with HCC are more reliable than a single gene. Thus, the PPI network and univariate Cox regression analysis were applied to screen candidate genes (small nuclear ribonucleoprotein polypeptide B and B1, nucleoporin 37, Rac GTPase activating protein 1, kinesin family member 20A, minichromosome maintenance 10 replication initiation factor, ubiquitin conjugating enzyme E2 C and hyaluronan mediated motility receptor) that are associated with the overall survival and progression-free survival of patients with HCC. In conclusion, the present study identified a set of genes that are associated with overall survival and progression-free survival of patients with HCC, providing valuable information for the prognosis of HCC.

Low fat mass index outperforms handgrip weakness and GLIM-defined malnutrition in predicting cancer survival: Derivation of cutoff values and joint analysis in an observational cohort.

BACKGROUND & AIMS: The optimal thresholds to define a survival-related low fat mass index (FMI) in Asian oncology populations remains largely unknown. This study sought to derive the sex-specific FMI cutoffs and analyze the independent and joint associations of a low FMI, handgrip weakness, and the Global Leadership Initiative on Malnutrition (GLIM)-defined malnutrition with cancer survival. METHODS: We performed a multicenter cohort study including 2376 patients with cancer. The FMI was measured by bioelectrical impedance analysis and the best thresholds were determined using an optimal stratification (OS) method. Low handgrip strength (HGS) and malnutrition were defined based on the Asian Working Group for Sarcopenia 2019 framework and the GLIM, respectively. The associations of a low FMI, handgrip weakness and malnutrition with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HRs). RESULTS: The study enrolled 1303 women and 1073 men with a mean age of 57.7 years and a median follow-up of 1267 days. The OS-defined FMI cutoffs were <5 kg/m2 in women and <7.7 kg/m2 in men. A low FMI, low HGS and malnutrition were identified in 1188 (50%), 1106 (46.5%) and 910 (38.3%) patients, respectively. A low FMI was adversely associated with the nutritional status, physical performance, quality of life and hospitalization costs. A low FMI (HR = 1.50, 95%CI = 1.16 to 1.92) and malnutrition (HR = 1.31, 95%CI = 1.08 to 1.59) were independently associated with mortality. Overall, the FMI plus GLIM-defined malnutrition showed the maximal joint prognostic impact, and patients with a combined low FMI and malnutrition had the worst survival (HR = 1.93, 95%CI = 1.48 to 2.52). CONCLUSIONS: Low FMI-indicated fat depletion outperforms and strengthens the prognostic value of handgrip weakness and GLIM-defined malnutrition for cancer survival. These findings indicate the importance of including fat mass assessment during routine cancer care to help guide strategies to optimize survival outcomes.

L-carnitine ameliorates the muscle wasting of cancer cachexia through the AKT/FOXO3a/MaFbx axis.

BACKGROUND: Recent studies suggest potential benefits of applying L-carnitine in the treatment of cancer cachexia, but the precise mechanisms underlying these benefits remain unknown. This study was conducted to determine the mechanism by which L-carnitine reduces cancer cachexia. METHODS: C2C12 cells were differentiated into myotubes by growing them in DMEM for 24 h (hrs) and then changing the media to DMEM supplemented with 2% horse serum. Differentiated myotubes were treated for 2 h with TNF-α to establish a muscle atrophy cell model. After treated with L-carnitine, protein expression of MuRF1, MaFbx, FOXO3, p-FOXO3a, Akt, p-Akt, p70S6K and p-p70S6K was determined by Western blotting. Then siRNA-Akt was used to determine that L-carnitine ameliorated cancer cachexia via the Akt/FOXO3/MaFbx. In vivo, the cancer cachexia model was established by subcutaneously transplanting CT26 cells into the left flanks of the BALB/c nude mice. After treated with L-carnitine, serum levels of IL-1, IL-6 and TNF-α, and the skeletal muscle content of MuRF1, MaFbx, FOXO3, p-FOXO3a, Akt, p-Akt, p70S6K and p-p70S6K were measured. RESULTS: L-carnitine increased the gastrocnemius muscle (GM) weight in the CT26-bearing cachexia mouse model and the cross-sectional fiber area of the GM and myotube diameters of C2C12 cells treated with TNF-α. Additionally, L-carnitine reduced the protein expression of MuRF1, MaFbx and FOXO3a, and increased the p-FOXO3a level in vivo and in vitro. Inhibition of Akt, upstream of FOXO3a, reversed the effects of L-carnitine on the FOXO3a/MaFbx pathway and myotube diameters, without affecting FOXO3a/MuRF-1. In addition to regulating the ubiquitination of muscle proteins, L-carnitine also increased the levels of p-p70S6K and p70S6K, which are involved in protein synthesis. Akt inhibition did not reverse the effects of L-carnitine on p70S6K and p-p70S6K. Hence, L-carnitine ameliorated cancer cachexia via the Akt/FOXO3/MaFbx and p70S6K pathways. Moreover, L-carnitine reduced the serum levels of IL-1 and IL-6, factors known to induce cancer cachexia. However, there were minimal effects on TNF-α, another inducer of cachexia, in the in vivo model. CONCLUSION: These results revealed a novel mechanism by which L-carnitine protects muscle cells and reduces inflammation related to cancer cachexia.