Geriatric Nutritional Risk Index Combined with Calf Circumference Can be a Good Predictor of Prognosis in Patients Undergoing Surgery for Gastric or Colorectal Cancer.

OBJECTIVES: To explore the effect of combined hematological and physical measurement indicators on the prognosis of patients undergoing surgery for gastric or colorectal cancer and to screen for the best prognostic indicators. INTRODUCTION: Gastric and colorectal cancer is a widespread health concern worldwide and one of the major contributors to cancer-related death. The hematological and physical measurement indicators have been shown to associate with the prognosis of patients undergoing surgery for gastric or colorectal cancer, respectively, but it is still unclear whether the combination of the two can reflect the prognosis more effectively. METHODS: Thirteen hematological indicators and 5 physical measurement indicators were selected in this study, and the most promising ones were screened using LASSO regression. Then, the best prognostic indicators were selected by time-ROC curves. Survival curves were constructed using the Kaplan-Meier method, and the effects of hematological and physical measurement indicators on the prognosis of patients undergoing surgery for gastric or colorectal cancers were evaluated by Cox proportional risk regression analysis. In addition, the relationship between hematological and physical measurement indicators on secondary outcomes, including length of stay, hospitalization costs, intensive care unit (ICU) admission, and patients' subjective global assessment scores (PGSGA), was explored. RESULTS: After initial screening, among the hematological indicators, the geriatric nutritional risk index (GNRI) showed the highest mean area under the curve (AUC) values. Among body measures, calf circumference (CC) showed the highest mean AUC value. Further analyses showed that the combination of combined nutritional prognostic index (GNRI) and calf circumference (CC) (GNRI-CC) had the best performance in predicting the prognosis of patients undergoing surgery for gastric or colorectal cancers. Low GNRI, low CC, and low GNRI-low CC increased the risk of death by 44%, 48%, and 104%, respectively. Sensitivity analyses showed the same trend. In addition, low GNRI-low CC increased the risk of malnutrition by 17%. CONCLUSION: This study emphasizes that a combination of blood measures and body measures is essential to accurately assess the prognosis of patients undergoing surgery for gastric or colorectal cancers. The GNRI-CC is a good prognostic indicator and can also assess the risk of possible malnutrition.

Association of systemic inflammation with the obesity paradox in cancer: results from multi-cohort studies.

AIMS: This study aimed to explore whether the obesity paradox exists in overall and specific cancers and to investigate the role of systemic inflammation in the obesity paradox. METHODS: The Cox proportional hazard model was used to explore the relationship between body mass index (BMI) and all-cause mortality. The mediated effect was used to investigate the proportion of systemic inflammation mediating the relationship between BMI and cancer survival risk. RESULTS: The survival probability showed a step-like increase with an increase in BMI regardless of pathological stage. Approximately 10.8%-24.0% of the overall association between BMI and all-cause mortality in cancer was mediated by inflammation. In the internal validation, we found evidence of the obesity paradox in all body composition obtained using BIA, with inflammation remaining an important mediating factor. Furthermore, we also validated the existence of the obesity paradox of cancer in NHANES. Systemic inflammation remains an important factor in mediating the association between BMI and prognosis in cancer patients. CONCLUSIONS: The obesity paradox is prevalent in most cancers, except for hepatic biliary cancer and breast cancer. Inflammation may be one of the true features of the obesity paradox in cancer.

Remnant cholesterol is an effective biomarker for predicting survival in patients with breast cancer.

BACKGROUND: Breast cancer is the most common malignancy in women worldwide. The relationship between remnant cholesterol (RC) and the prognosis of patients with breast cancer has not been clearly reported. This study investigated the prognostic value of RC in predicting mortality in patients with breast cancer. METHODS: This study prospectively analysed 709 women patients with breast cancer from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) project. Restricted cubic splines were used to analyse the dose-response relationship between RC and breast cancer mortality. The Kaplan-Meier method was used to evaluate the overall survival of patients with breast cancer. A Cox regression analyses was performed to assess the independent association between RC and breast cancer mortality. Inverse probability of treatment weighting (IPTW) using the propensity score was used to reduce confounding. Sensitivity analysis was performed after excluding patients with underlying diseases and survival times shorter than one year. RESULTS: A linear dose-response relationship was identified between RC and the risk of all-cause mortality in patients with breast cancer (p = 0.036). Kaplan-Meier survival analysis and log-rank test showed that patients with high RC levels had poorer survival than those with low RC levels (p = 0.007). Univariate and multivariate Cox regression analyses showed that RC was an independent risk factor for mortality in women patients with breast cancer. IPTW-adjusted analyses and sensitivity analyses showed that CR remained a prognostic factor. CONCLUSIONS: RC is an independent risk factor for the prognosis of patients with breast cancer, and patients with higher RC levels have poorer survival.

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

BACKGROUND: Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients. METHODS: This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients. RESULTS: Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese. CONCLUSIONS: The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

Muscle distribution in relation to all-cause and cause-specific mortality in young and middle-aged adults.

BACKGROUND: The relationship between muscle and prognosis, especially that between muscle distribution across different body parts, and the related prognosis is not well established. OBJECTIVE: To investigate the relationship between muscle distribution and all-cause and cause-specific mortality and their potential modifiers. DESIGN: Longitudinal cohort study. C-index, IDI, and NRI were used to determine the best indicator of prognosis. COX regression analysis was performed to explore the relationship between variables and outcomes. Interaction and subgroup analyses were applied to identify the potential modifiers. PARTICIPANTS: A total of 5052 participants (weighted: 124,841,420) extracted from the NHANES 2003-2006 of median age 45 years and constituting 50.3% men were assessed. For validation, we included 3040 patients from the INSCOC cohort in China. MAIN MEASURES: Muscle mass and distribution. KEY RESULTS: COX regression analysis revealed that upper limbs (HR = 0.41, 95% CI 0.33-0.51), lower limbs (HR = 0.54, 95% CI 0.47-0.64), trunk (HR = 0.71, 95% CI, 0.59-0.85), gynoid (HR = 0.47, 95% CI 0.38-0.58), and total lean mass (HR = 0.55, 95% CI 0.45-0.66) were all associated with the better survival of participants (P trend < 0.001). The changes in the lean mass ratio of the upper and lower limbs and the lean mass ratio of the android and gynoid attenuated the protective effect of lean mass. Age and sex acted as potential modifiers, and the relationship between lean mass and the prognosis was more significant in men and middle-aged participants when compared to that in other age groups. Sensitive analyses depicted that despite lean mass having a long-term impact on prognosis (15 years), it has a more substantial effect on near-term survival (5 years). CONCLUSION: Muscle mass and its distribution affect the prognosis with a more significant impact on the near-term than that on the long-term prognosis. Age and sex acted as vital modifiers.

The value of CRP-albumin-lymphocyte index (CALLY index) as a prognostic biomarker in patients with non-small cell lung cancer.

OBJECTIVE: The C-reactive protein-albumin-lymphocyte (CALLY) index is a new index related to inflammation, immunity, and nutrition. We investigated whether it can predict the prognosis of patients with non-small cell lung cancer (NSCLC) and developed a prognostic model including CALLY index. RESEARCH METHODS AND PROCEDURES: Data from patients with NSCLC who were followed up in the INSCOC database from May 2013 to December 2018 were retrospectively analyzed. Simple random sampling by splitting these patients into training (n = 1307) and validation cohorts (n = 557) resulted in a sample size ratio of 7:3. Using the results of COX regression analysis of the training cohort, a nomogram model for predicting 3- and 5-year overall survival (OS) was established and validated internally. The calibration and clinical decision curve were used to evaluate the prediction accuracy and clinical application ability of the nomogram and compared with the TNM staging system for lung cancer. RESULTS: Sex, TNM stage, surgical treatment, BMI, CALLY, and HGS were independent risk factors for the prognosis of NSCLC patients. The OS of NSCLC patients with a low CALLY index score was significantly worse than that of patients with a high CALLY index (P < 0.001). The CALLY-based nomogram had a good predictive prognostic power, with a C-index of 0.697. Compared with the traditional TNM staging system, our prognostic nomogram had better resolution and accuracy in predicting the 3-year and 5-year OS. Decision curve analysis showed that this prognostic model has a clinical application value. CONCLUSIONS: The CALLY index is a valuable biomarker for evaluating the prognosis of patients with lung cancer. The nomogram based on the CALLY index is highly effective in predicting OS in patients with NSCLC. The results of this study provide a reference tool for clinicians to guide the personalized treatment of patients with lung cancer.

Association between the Dietary Inflammatory Index and All-Cause Mortality in Adults with Obesity.

INTRODUCTION: The dietary inflammatory index (DII) is associated with numerous chronic noncommunicable diseases. Previous studies have shown that the pro-inflammatory DII categories are associated with abdominal and simple obesity. However, the association between DII and mortality in patients with abdominal obesity and simple overweight or obesity remains unclear. METHODS: We used data from the US National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. A DII >0 (positive DII) was defined as a pro-inflammatory diet. A restricted cubic spline curve was used to describe the trend between DII and all-cause mortality. We then examined the association between DII and all-cause mortality in different body types using a Cox regression analysis and investigated the differences between sexes. Finally, the mediating effects of systemic inflammation were explored. RESULTS: A pro-inflammatory diet increased all-cause mortality in adults with abdominal obesity (aHR: 1.31, 95% confidence interval [CI]: 1.11-1.54; p < 0.001) and with simple overweight or obesity (aHR: 1.30, 95% CI: 1.11-1.53; p < 0.001). In addition, the most pro-inflammatory DII increased the risk of mortality by 43% (hazard ratio [HR]: Q4 vs. Q1 = 1.43, 95% CI = 1.14-1.79; p = 0.002; p for trend = 0.003) and 39% (HR: Q4 vs. Q1 = 1.39, 95% CI = 1.13-1.74; p = 0.003; p for trend = 0.009) in participants with abdominal obesity and with simple overweight or obesity, respectively. However, this association was not present in normal-sized participants. Compared with men, women resisted the effects of a pro-inflammatory diet. Mediation analysis showed that white blood cell and neutrophil were mediators of the association between DII and all-cause mortality (p < 0.001). CONCLUSION: A pro-inflammatory diet is associated with all-cause mortality in adults with abdominal obesity and simple overweight or obesity, and this effect differs between men and women. Systemic inflammation may mediate the association between DII and all-cause mortality.

A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study.

BACKGROUND: This study aimed to develop an innovative inflammation-nutrition biomarker score (INS) system to stratify the prognoses of patients with cancer. METHODS: A total of 5,221 patients with cancer from multiple centers in China between June 2010 and December 2017 were enrolled in this prospective cohort study. We compared the commonly used inflammation and nutrition biomarkers and selected the most valuable to develop the novel INS system. Survival curves were assessed using the Kaplan-Meier method and the log-rank test to evaluate the difference in survival rates between groups. The Cox proportional hazards model was used to investigate the association between biomarkers and all-cause mortality. RESULTS: As the risk stratification of INS increased (1 to 5), the rate of death for cancer patients gradually increased (25.43% vs. 37.09% vs. 44.59% vs. 56.21% vs. 61.65%, p < 0.001). The INS system was associated with all-cause mortality in patients with cancer. Patients with both high inflammation and nutrition risk (INS = 5) were estimated to have much worse prognosis than those with neither (HR, 2.606; 95%CI, 2.261-3.003, p < 0.001). Subsequently, the results of randomized internal validation also confirmed that INS system had an ideal effect in identifying adverse outcomes. In addition, the INS system could be used as a supplement to pathological stages in prognosis assessment, and had a higher predictive value in comparison with the constitute biomarkers. Patients with a high INS had less functional ability, reduced quality of life, and were at high risk of malnutrition, cachexia, and poor short-term outcomes. CONCLUSION: The INS system based on inflammation and nutrition biomarkers is a simple and effective prognostic stratification tool for patients with cancer, which can provide a valuable reference for clinical prognosis assessment and treatment strategy formulation.

Prognostic importance of systemic inflammation and insulin resistance in patients with cancer: a prospective multicenter study.

BACKGROUND: Systemic inflammation and insulin resistance (IR) are often associated with poor prognosis in cancer. This study aimed to investigate the prognostic value of surrogate systemic inflammation and IR indices in patients with cancer. METHODS: This multicenter prospective study included 5,221 patients with cancer, with a mean age of 59.41±11.15 years, of whom 3,061 (58.6%) were male. The surrogate IR indices included low-density lipoprotein cholesterol to high-density lipoprotein cholesterol (LHR) ratio, total cholesterol to high-density lipoprotein cholesterol (TC/ HDL-c) ratio, triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio, and fasting triglyceride glucose (TyG). Prognostic receiver operator characteristic (ROC) curves and C-indices were used to select a better surrogate IR index in patients with cancer. The prognostic value of the indicators was evaluated using univariate and multivariate survival analyses. RESULTS: In this study, the median survival time of patients was 44.5 (40.5-51.4) months, and the overall mortality in the 12-month period was 1,115 (53.7%), with 196 mortality events per 1,000 patient-years of patients' follow-up. The prognostic ROC curve and C-index suggested that the prognostic value of LHR was better than that of the other IR indices. The multivariate-adjusted hazard ratios (HRs) for overall survival (OS) were higher in patients with high C-reactive protein (CRP) (HR, 1.51; 95% confidence interval [CI]: 1.38-1.65) and high LHR (HR, 1.20; 95% CI: 1.06-1.37), respectively. The mortality rate of patients with both high CRP and LHR was 1.75-fold higher than that of patients with both low CRP and LHR. CONCLUSION: Both CRP and LHR showed good survival predictions in patients with cancer. CRP combined with LHR can improve the predictive power of patients with cancer.

Lymphocyte to C-reactive protein ratio could better predict the prognosis of patients with stage IV cancer.

BACKGROUND: Systemic inflammation is currently regarded as a hallmark of cancer. This study aimed to accurately clarify the prognostic value of various inflammatory markers in patients with stage IV cancer. METHODS: This study assessed 2,424 patients with cancer diagnosed with cancer in tumor, node, metastasis (TNM) stage IV. After evaluating the predictive value of 13 inflammatory indicators for patient prognosis using the C index, the lymphocyte C-reactive protein ratio (LCR) was selected to elucidate the prognostic and predictive values in patients with stage IV cancer. Kaplan-Meier and Cox proportional hazards regression models were used to analyze long-term survival. RESULTS: A total of 1,457 men (60.1%) and 967 women (39.9%) diagnosed with TNM stage IV cancer were enrolled. A ratio of 2,814 was defined as the optimal cut-off value for the LCR. The LCR was the most accurate prognosis predictor for patients with stage IV cancer among the 13 inflammatory nutritional markers evaluated. The multivariate-adjusted restricted cubic spline plot suggested that LCR had an L-shaped dose-response association with all-cause mortality risk. Patients with lower LCR levels tended to present with worse prognoses. Kaplan-Meier curves and log-rank test results showed that the high LCR groups (LCR ≥ 2,814) exhibited a better prognosis, whereas patients with stage IV cancer of different sex and tumor types (for example, gastrointestinal tumor, non-gastrointestinal tumor, and lung cancer) had a worse survival time. CONCLUSION: The LCR score can be regarded as a stable and useful biomarker to predict prognosis in patients with TNM stage IV compared to other evaluated inflammation indicators.

Comprehensive comparison of the prognostic value of systemic inflammation biomarkers for cancer cachexia: a multicenter prospective study.

AIMS: Systemic inflammation plays an important role in cancer cachexia. However, among the systemic inflammatory biomarkers, it is unclear which has optimal prognostic value for cancer cachexia. METHODS: The Kaplan-Meier method was used and the log-rank analysis was performed to estimate survival differences between groups. Cox proportional hazard regression analyses were conducted to assess independent risk factors for all-cause mortality. RESULTS: The C-reactive protein-to-albumin ratio (CAR) was the optimal prognostic assessment tool for patients with cancer cachexia, with 1-, 3-, and 5-year predictive powers of 0.650, 0.658, and 0.605, respectively. Patients with a high CAR had significantly lower survival rates than those with a low CAR. Moreover, CAR can differentiate the prognoses of patients with the same pathological stage. Cox proportional risk regression analyses showed that a high CAR was an independent risk factor for cancer cachexia. For every standard deviation increase in CAR, the risk of poor prognosis for patients with cancer cachexia was increased by 20% (hazard ratio = 1.200, 95% confidence interval = 1.132-1.273, P < 0.001). CONCLUSIONS: CAR is an effective representative of systemic inflammation and a powerful factor for predicting the life function and clinical outcome of patients with cancer cachexia.

Which anthropometric measurement is better for predicting survival of patients with cancer cachexia?

No relevant studies have yet been conducted to explore which measurement can best predict the survival time of patients with cancer cachexia. This study aimed to identify an anthropometric measurement that could predict the 1-year survival of patients with cancer cachexia. We conducted a nested case-control study using data from a multicentre clinical investigation of cancer from 2013 to 2020. Cachexia was defined using the Fearon criteria. A total of 262 patients who survived less than 1 year and 262 patients who survived more than 1 year were included in this study. Six candidate variables were selected based on clinical experience and previous studies. Five variables, BMI, mid-arm circumference, mid-arm muscle circumference, calf circumference and triceps skin fold (TSF), were selected for inclusion in the multivariable model. In the conditional logistic regression analysis, TSF (P = 0·014) was identified as a significant independent protective factor. A similar result was observed in all patients with cancer cachexia (n 3084). In addition, a significantly stronger positive association between TSF and the 1-year survival of patients with cancer cachexia was observed in participants aged > 65 years (OR: 0·94; 95 % CI 0·89, 0·99) than in those aged ≤ 65 years (OR: 0·96; 95 % CI 0·93, 0·99; Pinteraction = 0·013) and in participants with no chronic disease (OR: 0·92; 95 % CI 0·87, 0·97) than in those with chronic disease (OR: 0·97; 95 % CI 0·94, 1·00; Pinteraction = 0·049). According to this study, TSF might be a good anthropometric measurement for predicting 1-year survival in patients with cancer cachexia.

The prognostic effect of hemoglobin on patients with cancer cachexia: a multicenter retrospective cohort study.

OBJECTIVES: To clarify the influence of hemoglobin on cancer cachexia and to determine whether hemoglobin affects the prognosis or quality of life of patients with cancer cachexia and whether these effects are caused by an interaction between hemoglobin and other factors. MATERIAL AND METHODS: This study was a multicenter cohort of 2715 patients with cancer cachexia diagnosed from June 2012 to December 2019. The primary outcomes and measures were overall survival (OS) time and all-cause mortality. The association between hemoglobin and all-cause mortality was evaluated using hazard ratios (HRs) and the restricted cubic spline model with a two-sided p-value. Optimal stratification was used to determine the threshold value. We also evaluated the cross-classification of hemoglobin and each variable with survival. RESULTS: Among the 2715 participants diagnosed with cancer cachexia, 1592 (58.6%) were male, and the mean (SD) age was 58.8 (11.7) years. The optimal cutoff point for hemoglobin as a predictor of cancer cachexia mortality was 140 g/L for males and 101 g/L for females in our research. The decrease in hemoglobin was positively correlated with all-cause mortality. These associations were consistent across cancer subtypes. In the multivariable analysis, after adjusting for sex, age, TNM stage, tumor type, radiotherapy, chemotherapy, Karnofsky performance status score, and other factors, patients diagnosed with cancer cachexia who had low hemoglobin levels were more likely to have a worse prognosis (HR 2.40; 95% CI, 1.12-1.51). CONCLUSION: Our results suggested that the proposed hemoglobin cutoff point would be valuable for prognostic prediction in patients with cancer cachexia, especially for long-term prognosis.

Efficacy of Global Leadership Initiative on Malnutrition as potential cachexia screening tool for patients with solid cancer.

PURPOSE: Cachexia has a very high prevalence in patients with cancer, and lacks effective screening tools yet. Global Leadership Initiative on Malnutrition (GLIM) is a novel malnutrition assessment tool, with increased important roles in malnutrition diagnosis for patients with cancer. However, whether GLIM can be used as an effective screening tool remains unknown. METHODS: We performed a multicenter cohort study including 8,478 solid tumor patients from 40 clinical centers throughout China. Cachexia was diagnosed based on the 2011 international cancer cachexia consensus. The receiver operating characteristic curves (ROC) and decision curve analysis (DCA) were developed to determine the efficacy and clinical net benefit of GLIM and Patient-Generated Subjective Global Assessment (PG-SGA) in the detection of cancer cachexia, respectively. RESULTS: According to the consensus guidelines, 1,441 (17.0%) cancer patients were diagnosed with cachexia among 8,478 patients in the present study. The sensitivity of one-step GLIM and two-step GLIM for detecting cachexia were 100 and 88.8%, respectively, while that of PG-SGA was 86.2%. The accuracies of one-step GLIM and two-step GLIM reached 67.4 and 91.3%, which were higher than that of PG-SGA (63.1%). The area under the curves (AUCs) of one-step GLIM (0.835) and two-step GLIM (0.910) were higher than PG-SGA (0.778) in patients with cancer. The DCA also revealed that two-step GLIM had better clinical effect than PG-SGA between 20-50% threshold probabilities. CONCLUSION: GLIM could be used as an effective tool in screening cancer cachexia, two-step GLIM criteria show more accurate while one-step GLIM criteria is more sensitive. TRIAL REGISTRATION: ChiCTR1800020329.

Comparative analysis of malnutrition diagnosis methods in lung cancer patients using a Bayesian latent class model.

BACKGROUND AND OBJECTIVES: There are no consensus criteria for malnutrition diagnosis in clinical settings, the Global Leadership Initiative on Malnutrition (GLIM) criteria were developed to facilitate global comparisons of malnutrition prevalence, interventions and outcomes. Validation to assess usefulness in clinical practice is essential, however, the imperfect nature of reference standards used in concurrent validation may result in biased estimates of diagnostic accuracy. The Bayesian latent class model (BLCM) can assess the diagnostic performance when a "gold standard" is absent. This study's objective was to assess the diagnostic performance of the GLIM criteria in comparison with the Nutritional Risk Screening 2002 (NRS-2002) and the Patient Generated Subjective Global Assessment (PG-SGA) in lung cancer patients using a BLCM. We hypothesized that the GLIM criteria are more sensitive and specific for malnutrition diagnosis in lung cancer patients. METHODS AND STUDY DESIGN: 1,384 patient records retrospectively obtained from the "Investigation on Nutrition Status and its clinical outcome of common Cancers" (INSCOC) study were used to determine the prevalence of malnutrition, sensitivity (Se) and specificity (Sp) by applying a BLCM. RESULTS: The prevalence of malnutrition was 0.56. The sensitivity and specificity of the GLIM criteria were Se: 0.85 and Sp: 0.88; Se: 0.74 and Sp: 0.85 for NRS-2002 and Se: 0.96 and Sp: 0.89 for PG-SGA. CONCLUSIONS: Although the GLIM criteria were acceptable for malnutrition diagnosis, PG-SGA is superior for determining cancer-associated malnutrition. Because of its fair sensitivity, NRS-2002 was best equipped to screen out patients not at nutritional risk.

The diagnosis and prognosis values of WNT mRNA expression in colon adenocarcinoma.

WNT family genes have participated in the progression and development of many cancers, however, the association between colon adenocarcinoma (COAD) and WNTs have been rarely reported. This study investigated the significance of WNT genes expression in COAD from the standpoint of diagnosis and prognosis. The RNA-sequencing dataset of COAD was downloaded from The Cancer Genome Atlas and University of California, Santa Cruz Xena browser. The biology functions of WNT genes were investigated by biological analysis. Biological analysis of WNT family genes indicated that WNT genes were noticeably enriched in the complex process of WNT signaling pathway. The Pearson correlation analysis suggested WNT1 and WNT9B had a strong correlation. And receiver operating characteristic curves suggested that most of the genes could serve as a significant diagnostic makers in COAD (P < .05), especially WNT2 and WNT7B had high diagnostic values that the area under curve were 0.997 (95% confidence interval [0.994-1.000]) and 0.961 (95%CI [0.939-0.983]), respectively. And our multivariate survival analysis suggested the downregulated of WNT10B (P < .05) showed a favor prognosis in COAD overall survival. And the risk score model predicted that the upregulated expression of WNT10B might increase the risk of death. The very study we had conducted suggested that WNT genes had a certain connection with the diagnosis and prognosis of COAD. The messenger RNA expression of WNT2 and WNT7B might become potentially diagnostic biomarkers, and WNT10B might serve as an independent prognosis indicator for COAD.

Prognostic value of Glypican family genes in early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy and possible mechanisms.

BACKGROUND: This study explored the prognostic significance of Glypican (GPC) family genes in patients with pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). METHODS: A total of 112 PDAC patients from TCGA and 48 patients from GEO were included in the analysis. The relationship between overall survival and the expression of GPC family genes as well as basic clinical characteristics was analyzed using the Kaplan-Meier method with the log-rank test. Joint effects survival analysis was performed to further examine the relationship between GPC genes and prognosis. A prognosis nomogram was established based on clinical characteristics and prognosis-related genes. Prognosis-related genes were investigated by genome-wide co-expression analysis and gene set enrichment analysis (GSEA) was carried out to identify potential mechanisms of these genes affecting prognosis. RESULTS: In TCGA database, high expression of GPC2, GPC3, and GPC5 was significantly associated with favorable survival (log-rank P = 0.031, 0.021, and 0.028, respectively; adjusted P value = 0.005, 0.022, and 0.020, respectively), and joint effects analysis of these genes was effective for prognosis prediction. The prognosis nomogram was applied to predict the survival probability using the total scores calculated. Genome-wide co-expression and GSEA analysis suggested that the GPC2 may affect prognosis through sequence-specific DNA binding, protein transport, cell differentiation and oncogenic signatures (KRAS, RAF, STK33, and VEGFA). GPC3 may be related to cell adhesion, angiogenesis, inflammatory response, signaling pathways like Ras, Rap1, PI3K-Akt, chemokine, GPCR, and signatures like cyclin D1, p53, PTEN. GPC5 may be involved in transcription factor complex, TFRC1, oncogenic signatures (HOXA9 and BMI1), gene methylation, phospholipid metabolic process, glycerophospholipid metabolism, cell cycle, and EGFR pathway. CONCLUSION: GPC2, GPC3, and GPC5 expression may serve as prognostic indicators in PDAC, and combination of these genes showed a higher efficiency for prognosis prediction.

The prognostic value of combined tumor markers and systemic immune-inflammation index in colorectal cancer patients.

PURPOSE: This study evaluated the significance of combining tumor markers (TM) and systemic immune-inflammation index (SII) for postoperative complications and long-term outcomes in colorectal cancer (CRC) patients. METHODS: CRC patients (662) who underwent surgery between 2012 and 2014 were retrospectively enrolled into our study. Factors affecting postoperative complications were evaluated by logistic regression analysis. Prognostic factors were assessed using Kaplan-Meier and Cox proportional hazards models. Nomograms were constructed to predict the risk of postoperative complications and survival. A consistency index and a calibration curve were used to evaluate the predictive accuracy of nomograms. RESULTS: TM-SII score was established by combining TM and SII. Logistic regression analyses showed that TM-SII score was an important predictor of postoperative complications in CRC patients. Kaplan-Meier analyses showed that TM-SII score was favorable for prognostic risk stratification. In addition, multivariate analyses indicated that TM-SII score was an independent prognostic indicator for disease-free survival and overall survival. TM-SII based nomograms had a moderate prediction accuracy. CONCLUSION: TM-SII score is a good prognostic indicator for CRC patients. It may be used as a useful risk stratification tool for advanced CRC patients. TM-SII-based nomograms could be used to identify CRC patients with poor outcomes.

Inflammaging score as a potential prognostic tool for cancer: A population-based cohort study.

This study aimed to develop a clinically applicable inflammaging score by combining the inflammatory status and age of patients. Kaplan-Meier analysis was used to compare survival differences among patients with different grades of inflammation scores. Cox proportional hazard regression analysis was used to explore the relationship between the inflammaging score and survival. As the age of patients increased, their levels of systemic inflammation gradually increased. A unique inverse relationship was found between the level of inflammation and cancer prognosis during the ageing process. Mediation analysis indicated that systemic inflammation mediates 10.1%-17.8% of the association between ageing and poor prognosis. With an increase in the inflammaging score from grades I to V, the survival rate showed a gradient decline. The inflammation score could effectively stratify the prognosis of patients with lung, bronchial, gastrointestinal, and other types of cancers. Compared with grade I, the hazard ratios for grades II-V were 1.239, 1.604, 1.724, and 2.348, respectively. In the external validation cohort, the inflammaging score remained an independent factor affecting the prognosis of patients with cancer. The inflammaging score, which combines ageing and inflammation, is a robust prognostic assessment tool for cancer patients.