The quality of life impacting factors in malnourished patients with gastric cancer.

Introduction: Malnutrition is prevalent among individuals with gastric cancer and notably decreases their quality of life (QOL). However, the factors impacting QOL are yet to be clearly defined. This study aimed to identify essential factors impacting QOL in malnourished patients suffering from gastric cancer. Methods: By using the Patient-Generated Subjective Global Assessment (PG-SGA) to assess the nutritional status (≥4 defined malnutrition) of hospitalized cancer patients, 4,586 gastric cancer patients were ultimately defined as malnourished. Spearman method was used to calculate the relationship between clinical features and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Then, univariate and multivariate logistic regression were used to observe which factors affected QOL, and subgroup analysis was performed in young and old population respectively. In addition, we used univariate and multivariate logistic regression to explore whether and how self-reported frequent symptoms in the last 2 weeks of the PG-SGA score affected QOL. Results: In multivariate logistic regression analysis of clinical features of patients with malnourished gastric cancer, women, stage II, stage IV, WL had an independent correlation with a low global QOL scores. However, BMI, secondary education, higher education, surgery, chemotherapy, HGS had an independent correlation with a high global QOL scores. In multivariate logistic regression analysis of symptoms in self-reported PG-SGA scores in patients with malnourished gastric cancer, having no problem eating had an independent correlation with a high global QOL scores. However, they have no appetite, nausea, vomiting, constipation and pain had an independent correlation with a lower global QOL scores. The p values of the above statistical results are both < 0.05. Conclusion: This study demonstrates that QOL in malnourished patients with gastric cancer is determined by female sex, stage II, stage IV, BMI, secondary and higher education or above, surgery, chemotherapy, WL, and HGS. Patients' self-reported symptoms of nearly 2 weeks, obtained by using PG-SGA, are also further predictive of malnourished gastric cancer patients. Detecting preliminary indicators of low QOL could aid in identifying patients who might benefit from an early referral to palliative care and assisted nursing.

Anthropometrics and cancer prognosis: a multicenter cohort study.

BACKGROUND: Anthropometric indicators have been shown to be associated with the prognosis of patients with cancer. However, any single anthropometric index has limitation in predicting the prognosis. OBJECTIVES: This study aimed to observe the predictive role of 7 anthropometric indicators based on body size on the prognosis of patients with cancer. METHODS: A principal component analysis (PCA) on 7 anthropometric measurements: height, weight, BMI, hand grip strength (HGS), triceps skinfold thickness (TSF), mid-upper arm circumference (MAC), and calf circumference (CAC) was conducted. Principal components (PCs) were derived from this analysis. Cox regression analysis was used to investigate the association between the prognosis of patients with cancer and the PCs. Subgroups and sensitivity analyses were also conducted. RESULTS: Through PCA, 4 distinct PCs were identified, collectively explaining 88.3% of the variance. PC1, primarily characterized by general obesity, exhibited a significant inverse association with risk of cancer-related death (adjusted hazard ratio [HR]: 0.86; 95% confidence interval [CI]: 0.83, 0.88). PC2 (short stature with high TSF) was not significantly associated with cancer prognosis. PC3 (high BMI coupled with low HGS) demonstrated a significant increase with risk of cancer-related death (adjusted HR: 1.08; 95% CI: 1.05, 1.11). PC4 (tall stature with high TSF) exhibited a significant association with increased cancer risk (adjusted HR: 1.05; 95% CI: 1.02, 1.07). These associations varied across different cancer stages. The stability of the results was confirmed through sensitivity analyses. CONCLUSIONS: Different body sizes are associated with distinct prognostic outcomes in patients with cancer. The impact of BMI on prognosis is influenced by both HGS and subcutaneous fat. This finding may influence the clinical care of cancer and improve the survival of cancer patients.

Phase angle: A robust predictor of malnutrition and poor prognosis in gastrointestinal cancer.

OBJECTIVES: The aim of this study was to investigate the relationship among phase angle (PA), malnutrition, and prognosis in patients with gastrointestinal cancer. METHODS: In total, 870 patients with gastrointestinal cancer were enrolled. Kaplan-Meier curves and Cox proportional hazards models were used to evaluate the association between PA and survival risk. Restricted cubic spline regression was used for flexibility analysis to explore sex-specific associations between PA and survival. Logistic regression was used to assess the relationships among PA, malnutrition, and cachexia. RESULTS: Low PA was closely associated with poor physical conditions, diminished quality of life, and malnutrition. Patients with low PA had a significantly worse prognosis than those with high PA (60.6% versus 72.8%; log-rank P < 0.001). PA was suitable for the prognostic assessment of patients with advanced-stage tumors. Regardless of sex, patients with lower PA showed significantly poorer survival rates. Cox proportional hazards models identified PA as an independent predictor of prognosis in patients with gastrointestinal cancer (hazard ratio (HR)=0.534; 95% confidence interval (CI)=0.409-0.696, P < 0.001). Subgroup analysis indicated that a high PA was an independent risk factor affecting the prognoses of patients with esophageal, liver, and intrahepatic bile duct cancers. Interestingly, variations in PA had a more significant prognostic effect on survival in men than in women. The logistic regression model confirmed that PA is a valuable indicator for assessing malnutrition and cachexia in patients with gastrointestinal cancer. Among all body composition indicators, PA demonstrated the highest accuracy for prognostic prediction. CONCLUSIONS: PA was identified as a robust predictor of malnutrition and poor prognosis in patients with gastrointestinal cancer.

Obesity-associated metabolic inflammation promotes triple-negative breast cancer progression through the interleukin-6/STAT3/pentraxin 3/matrix metalloproteinase 7 axis.

BACKGROUND: This study aimed to investigate the regulatory mechanism of the adipose factor interleukin (IL)-6 in promoting pentraxin 3 (PTX3) expression in triple-negative breast cancer (TNBC). METHODS: We established an in vitro coculture model of mature adipocytes and TNBC cells using a Transwell system. Cell scratch, Transwell migration, and matrix invasion assays were used to evaluate the migration and invasion abilities of TNBC cells cocultured with adipocytes. Next, we used lentivirus-mediated functional depletion experiments to study PTX3's role in the adipocyte-dependent migration of TNBC cells. RESULTS: After coculturing TNBC cells with adipocytes, PTX3 expression was upregulated, which accompanied enhanced cell migration and invasion. Using GEO data and RNA-seq analysis, we identified PTX3 as a key target gene influenced by the adipose TNBC microenvironment. IL-6 upregulation in the conditioned medium of mature adipocytes and in the serum of high-fat diet mice was associated with this effect, and the recombinant protein IL-6 significantly promoted the migration and invasion of TNBC cells along with the phosphorylation of intracellular STAT3 and the upregulation of PTX3. PTX3 knockdown inhibited TNBC cell migration and eliminated the enhanced migration caused by coculturing with adipocytes. Furthermore, in vivo experiments confirmed that the PTX3 knockdown reduced obesity-induced lung metastasis. Subsequent experiments with cytokines and drug inhibitors confirmed that adipocyte-derived IL-6 promoted PTX3 expression by activating the STAT3 signaling pathway. Additionally, bioinformatic analysis indicated that PTX3 promotes TNBC metastasis by regulating the matrix metalloproteinase (MMP) family. CONCLUSION: Our study elucidated Obesity-related metabolic inflammation promotes the progression via the IL-6/STAT3/PTX3/MMP7 axis.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

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.

The relationship between different fatty acids intake and the depressive symptoms: A population-based study.

BACKGROUND: Depression is a common psychological disorder worldwide, affecting mental and physical health. Previous studies have explored the benefits of polyunsaturated fatty acids (PUFAs) intake in depressive symptoms; however, few studies have focused on the association between all types of fatty acids intake and depressive symptoms. Therefore, we explored the relationship between the intake of different fatty acids intake and the risk of depressive symptoms. METHODS: The study was based on the data from the 2005-2018 National Health and Nutrition Examination Survey (NHANES), a large US-based database. We used a nutrient residual model and multi-nutrient density model for the analysis. We calculated the nutrient density and residual in men and women separately, and the fatty acids intake was divided into quartiles based on the sex distribution. The relationship between the depressive symptoms and the intake of different fatty acids was examined using logistic regression; furthermore, we explored the relationships separately in men and women. RESULTS: The intake of monounsaturated fatty acids (MUFAs) and PUFAs, particularly n-3 and n-6 PUFAs, were associated with reduced odds ratios for depressive symptoms. The inverse relationship between the intake of MUFAs, PUFAs, n-3, and n-6 PUFAs and depressive symptoms was stronger in women. The inverse relationship between total fatty acid (TFAs) intake and depressive symptoms existed only in a single model. In contrast, saturated fatty acid (SFAs) intake was not related to depressive symptoms. CONCLUSION: Consuming MUFAs and PUFAs can counteract the depressive symptoms, especially in women.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer.

BACKGROUND: Ferroptosis has recently been associated with multiple degenerative diseases. Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases. However, the association of iron proliferation-related genes with prognosis in HER2+ breast cancer (BC) patients is unclear. AIM: To identify and evaluate fresh ferroptosis-related biomarkers for HER2+ BC. METHODS: First, we obtained the mRNA expression profiles and clinical information of HER2+ BC patients from the TCGA and METABRIC public databases. A four-gene prediction model comprising PROM2, SLC7A11, FANCD2, and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort. Patients were stratified into high-risk and low-risk groups based on their median risk score, an independent predictor of overall survival (OS). Based on these findings, immune infiltration, mutations, and medication sensitivity were analyzed in various risk groupings. Additionally, we assessed patient prognosis by combining the tumor mutation burden (TMB) with risk score. Finally, we evaluated the expression of critical genes by analyzing single-cell RNA sequencing (scRNA-seq) data from malignant vs normal epithelial cells. RESULTS: We found that the higher the risk score was, the worse the prognosis was (P < 0.05). We also found that the immune cell infiltration, mutation, and drug sensitivity were different between the different risk groups. The high-risk subgroup was associated with lower immune scores and high TMB. Moreover, we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses. HRisk-HTMB patients had the worst prognosis, whereas LRisk-LTMB patients had the best prognosis (P < 0.0001). Analysis of the scRNA-seq data showed that PROM2, SLC7A11, and FANCD2 were significantly differentially expressed, whereas FH was not, suggesting that these genes are expressed mainly in cancer epithelial cells (P < 0.01). CONCLUSION: Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Processes and mechanisms in remediation of aqueous chromium contamination by sulfidated nano-scale zerovalent iron (S-nZVI): Experimental and computational investigations.

Sulfidated nano-scale zerovalent iron (S-nZVI) has emerged as an advanced functional nanomaterial for efficiently remediating Cr(VI) contamination in aqueous environments. However, there is an insufficient understanding of its coherent process, removal pathway, and hydrochemical reactive mechanisms, presenting potential challenges for its future environmental applications. To address this gap, this study successfully synthesized S-nZVI through a chemical precipitation method and effectively applied it for the removal of Cr(VI). Additional characterization revealed that the removal of Cr(VI) followed a sequence of rapid chemisorption and intraparticle diffusion processes, concomitant with an increase in pH and a decrease in oxidation-reduction potential. The remediation mechanism encompassed a synergistic reduction of Cr(VI) to Cr(III) and simultaneous immobilization via Cr2FeO4 coprecipitation. The highest Cr(VI) removal capacity of 75 mg/g was attained during dynamic removal experiments in the sand column packed with S-nZVI. Further computational analysis, employing density functional theory calculations based on the experimental data, revealed the involvement of multiple molecular orbitals of Cr(VI) in the removal process. It also elucidated a step-by-step reduction pathway for Cr(VI) characterized by decreasing free energy. These findings provide evidence-based insights into Cr(VI) remediation using S-nZVI and can serve as valuable technical support for future environmental management of heavy metals.

Evaluation and validation of neutrophil to albumin ratio as a promising prognostic marker for all-cause mortality in patients with cancer: a multicenter cohort study.

OBJECTIVES: The practicality and effectiveness of using the prognostic value of the neutrophil-to-albumin ratio (NAR) in evaluating patients with cancer remain unclear, and research is needed to fully understand its potential application in the cancer population. METHODS: The Kaplan-Meier method was used for survival analysis, and the log-rank test was employed for comparison. Univariate and multivariate Cox proportional hazards models were used to determine the prognostic biomarkers, and Logistic regression analysis was conducted to investigate the relationship between NAR and 90-day outcomes and cachexia. RESULTS: The study included 14 682 patients with cancer, divided into discovery (6592 patients), internal validation (2820 patients), and external validation groups (5270 patients). Patients with high NAR had higher all-cause mortality than those with low NAR in the discovery (50.15% versus 69.29%, P < 0.001), internal validation (54.18% versus 70.91%, P < 0.001), and external validation cohorts (40.60% versus 66.68%, P < 0.001). In the discovery cohort, high NAR was observed to be independently associated with all-cause mortality in patients (HR 1.16, 95% CI 1.12-1.19; P < 0.001). Moreover, we validated the promising prognostic value of NAR as a predictor of survival in patients with cancer through internal validation (HR 1.21, 95% CI 1.16-1.27, P < 0.001) and external validation cohorts (HR 1.27, 95% CI 1.21-1.34, P < 0.001). Additionally, in the subgroup analysis by tumor type, high NAR was identified as a risk factor for most cancers, except for breast cancer. CONCLUSIONS: This study showed that NAR is a feasible and promising biomarker for predicting prognosis and cancer cachexia in cancer patients.

Age Differences in the Association of Sleep Duration Trajectory With Cancer Risk and Cancer-Specific Mortality: Prospective Cohort Study.

BACKGROUND: Baseline sleep duration is associated with cancer risk and cancer-specific mortality; however, the association between longitudinal patterns of sleep duration and these risks remains unknown. OBJECTIVE: This study aimed to elucidate the association between sleep duration trajectory and cancer risk and cancer-specific mortality. METHODS: The participants recruited in this study were from the Kailuan cohort, with all participants aged between 18 and 98 years and without cancer at baseline. The sleep duration of participants was continuously recorded in 2006, 2008, and 2010. Latent mixture modeling was used to identify shared sleep duration trajectories. Furthermore, the Cox proportional risk model was used to examine the association of sleep duration trajectory with cancer risk and cancer-specific mortality. RESULTS: A total of 53,273 participants were included in the present study, of whom 40,909 (76.79%) were men and 12,364 (23.21%) were women. The average age of the participants was 49.03 (SD 11.76) years. During a median follow-up of 10.99 (IQR 10.27-11.15) years, 2705 participants developed cancers. Three sleep duration trajectories were identified: normal-stable (44,844/53,273, 84.18%), median-stable (5877/53,273, 11.03%), and decreasing low-stable (2552/53,273, 4.79%). Compared with the normal-stable group, the decreasing low-stable group had increased cancer risk (hazard ratio [HR] 1.39, 95% CI 1.16-1.65) and cancer-specific mortality (HR 1.54, 95% CI 1.18-2.06). Dividing the participants by an age cutoff of 45 years revealed an increase in cancer risk (HR 1.88, 95% CI 1.30-2.71) and cancer-specific mortality (HR 2.52, 95% CI 1.22-5.19) only in participants younger than 45 years, rather than middle-aged or older participants. Joint analysis revealed that compared with participants who had a stable sleep duration within the normal range and did not snore, those with a shortened sleep duration and snoring had the highest cancer risk (HR 2.62, 95% CI 1.46-4.70). CONCLUSIONS: Sleep duration trajectories and quality are closely associated with cancer risk and cancer-specific mortality. However, these associations differ with age and are more pronounced in individuals aged <45 years. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-TNRC-11001489; http://tinyurl.com/2u89hrhx.

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.

Carbon dot enhanced peroxidase-like activity of platinum nanozymes.

As one of the most intriguing nanozymes, the platinum (Pt) nanozyme has attracted tremendous research interest due to its various catalytic activities but its application is still limited by its poor colloidal stability and low affinity to substrates. Here, we design a highly stable Pt@carbon dot (Pt@CD) hybrid nanozyme with enhanced peroxidase (POD)-like activity (specific activity of 1877 U mg-1). The Pt@CDs catalyze the decomposition of hydrogen peroxide (H2O2) to produce singlet oxygen and hydroxyl radicals and exhibit high affinity to H2O2 and high specificity to 3,3',5,5'-tetramethyl-benzidine. We reveal that both the hydroxyl and carbonyl groups of CDs could coordinate with Pt2+ and then regulate the charge state of the Pt nanozyme, facilitating the formation of Pt@CDs and improving the POD-like activity of Pt@CDs. Colorimetric detection assays based on Pt@CDs for H2O2, dopamine, and glucose with a satisfactory detection performance are achieved. Moreover, the Pt@CDs show a H2O2-involving antibacterial effect by destroying the cell membrane. Our findings provide new opportunities for designing hybrid nanozymes with desirable stability and catalytic performance by using CDs as nucleating templates and stabilizers.

Temporal relationship between inflammation and metabolic disorders and their impact on cancer risk.

Background: Inflammation and metabolic disorders are closely associated with cancer. Whether inflammation leads to metabolic disorders or vice versa during cancer initiation remains unclear. In this study, we explored this temporal relationship and the co-exposure effect on cancer risk. Methods: This prospective study had two phases. Initially, we examined the temporal relationship between inflammation (high-sensitivity C-reactive protein (CRP)) and metabolic disorders (metabolic syndrome severity Z-score (MetS-Z)) using a 3.98-year survey and cross-lagged analysis. Subsequently, we assessed the connection of co-exposure to inflammation and metabolic disorders, and the risks of overall cancer, as well as specific obesity-related, non-obesity-related, digestive system, lung, and other cancers using an 11.04-year survey and Cox proportional hazard models. Results: The cross-lagged analysis revealed that the path coefficient from baseline CRP to follow-up MetS-Z (ß2 = 0.032; 95% confidence interval (CI) = 0.026, 0.046) was more significant than the path coefficient from baseline MetS-Z to follow-up CRP (ß1 = 0.009; 95% CI = -0.001, 0.019). During the follow-up, 2304 cases of cancer occurred. Compared with the risk of cancer of patients with low average cumulative CRP and MetS-Z, patients with high value had a significantly increased risk (hazard ratio = 1.54, 95% CI = 1.30, 1.83). The mediation analysis showed that MetS-Z mediated the association between CRP levels and overall cancer (12.67%), digestive system cancer (10.16%), and obesity-related cancer risk (13.87%). Conclusions: Inflammation had a greater impact on metabolic disorders than vice versa. Co-exposure to inflammation and metabolic disorders significantly increased the risk of cancer, particularly digestive system and obesity-related cancers. Registration: Chinese Clinical Trial Registry: ChiCTR-TNRC-11001489.

Systemic inflammation and insulin resistance-related indicator predicts poor outcome in patients with cancer cachexia.

BACKGROUND: The C-reactive protein (CRP)-triglyceride-glucose (TyG) index (CTI), which is a measure representing the level of inflammation and insulin resistance (IR), is related to poor cancer prognosis; however, the CTI has not been validated in patients with cancer cachexia. Thus, this study aimed to explore the potential clinical value of the CTI in patients with cancer cachexia. METHODS: In this study, our prospective multicenter cohort included 1411 patients with cancer cachexia (mean age 59.45 ± 11.38, 63.3% male), which was a combined analysis of multiple cancer types. We randomly selected 30% of the patients for the internal test cohort (mean age 58.90 ± 11.22% 61.4% male). Additionally, we included 307 patients with cancer cachexia in the external validation cohort (mean age 61.16 ± 11, 58.5% male). Receiver operating characteristic (ROC) and calibration curves were performed to investigate the prognostic value of CTI. The prognostic value of the CTI was also investigated performing univariate and multivariate survival analyses. RESULTS: The survival curve indicated that the CTI showed a significant prognostic value in the total, internal, and external validation cohorts. Prognostic ROC curves and calibration curves revealed that the CTI showed good consistency in predicting the survival of patients with cancer cachexia. Multivariate survival analysis showed that an elevated CTI increased the risk of death by 22% (total cohort, 95% confidence interval [CI] = 1.13-1.33), 34% (internal test cohort, 95%CI = 1.11-1.62), and 35% (external validation cohort, 95%CI = 1.14-1.59) for each increase in the standard deviation of CTI. High CTI reliably predicted shorter survival (total cohort, hazard ratio [HR] = 1.45, 95%CI = 1.22-1.71; internal test cohort, HR = 1.62, 95%CI = 1.12-2.36; external validation cohort, HR = 1.61, 95%CI = 1.15-2.26). High CTI significantly predicted shorter survival in different tumor subgroups, such as esophageal [HR = 2.11, 95%CI = 1.05-4.21] and colorectal cancer [HR = 2.29, 95%CI = 1.42-3.71]. The mediating effects analysis found that the mediating proportions of PGSGA, ECOG PS, and EORTC QLQ-C30 on the direct effects of CTI were 21.72%, 19.63%, and 11.61%, respectively We found that there was a significant positive correlation between the CTI and 90-day [HR = 2.48, 95%CI = 1.52-4.14] and 180-day mortality [HR = 1.77,95%CI = 1.24-2.55] in patients with cancer cachexia. CONCLUSION: The CTI can predict the short- and long-term survival of patients with cancer cachexia and provide a useful prognostic tool for clinical practice.

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.

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.

Predicted lean body mass trajectories, and cancer risk and cancer-specific and all-cause mortality: A prospective cohort study.

BACKGROUND: Although many studies have investigated the association between body composition, cancer risk and mortality, predicting these risks through a single body composition measurement undoubtedly increases the limitations of the study. Few studies have explored the association between the trajectory of changes in body composition and the risk of cancer and death. We aimed to explore the association of predicted lean mass trajectories with cancer risk, cancer-specific mortality and all-cause mortality. METHODS: The participants in this study were all from the Kailuan cohort, a prospective, periodic, resurvey cohort study initiated in 2006. Latent mixture modelling was used to identify predicted lean mass trajectories for 2006-2010. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) of the Cox proportional hazard models were used to describe the association between predicted lean mass trajectories and cancer risk and cancer-specific and all-cause mortality during follow-up (2010-2021). RESULTS: A total of 44 374 participants (average age, 53.01 ± 11.41 years, 78.99% men and 21.01% women) were enrolled in this study. Five distinct trajectories were identified: low-stable (n = 12 060), low-increasing (n = 8027), moderately stable-decreasing (n = 4725), moderately stable-increasing (n = 8053) and high-stable (n = 11 509). During the 11-year follow-up period, 2183 cancer events were recorded. After adjusting for age, predicted fat mass in 2010, sex, BMI, sedentary, physical activity, smoke, alcohol use, salt consumption, high-fat diet, high-sensitivity C-reactive protein, serum creatinine, family history of tumour, hypertension, diabetes mellitus, compared with the low-stable group, participants in the low-increasing group (HR = 0.851, 95% CI, 0.748-0.969), moderately stable-increasing group (HR = 0.803, 95% CI, 0.697-0.925) and high-stable group (HR = 0.770, 95% CI, 0.659-0.901) had a lower cancer risk, but not in the moderately stable-decreasing group (HR = 0.864, 95% CI, 0.735-1.015). Compared with the low-stable group, the risk of cancer-specific mortality was reduced by 25.4% (8.8-38.9%), 36.5% (20.3-49.4%) and 35.4% (17.9-49.2%), and the risk of all-cause mortality was reduced by 24.2% (16.9-30.8%), 37.0% (30.0-43.2%) and 47.4% (41.0-53.1%) in the low-increasing, moderately stable-increasing group and high-stable groups, respectively. CONCLUSIONS: Predicted lean mass trajectories may be closely associated with cancer risk and cancer-specific and all-cause mortality. Regular monitoring of body composition is necessary.

Individualized threshold of the involuntary weight loss in prognostic assessment of cancer.

BACKGROUND: Involuntary weight loss (WL) is a common symptom in cancer patients and is associated with poor outcomes. However, there is no standardized definition of WL, and it is unclear what magnitude of weight loss should be considered significant for prognostic purposes. This study aimed to determine an individualized threshold for WL that can be used for prognostic assessment in cancer patients. METHODS: Univariate and multivariate analyses of overall survival (OS) were performed using Cox proportional hazard models. The Kaplan-Meier method was performed to estimate the survival distribution of different WL levels. Logistic regression analysis was used to determine the relationship between WL and 90-day outcomes. Restricted cubic splines with three knots were used to examine the effects of WL on survival under different body mass index (BMI) conditions. RESULTS: Among the 8806 enrolled patients with cancer, median survival time declined as WL increased, from 25.1 to 20.1, 17.8 and 16.4 months at <2%, 2-5%, 5-10% and ≥10% WL, respectively (P < 0.001). Multivariate adjusted Cox regression analysis showed that the risk of adverse prognosis increased by 18.1% based on the SD of WL (5.45 U) (HR: 1.181, 95% CI: 1.144-1.219, P < 0.001). Similarly, categorical WL was independently associated with OS in patients with cancer. With the worsening of WL, the risk of a poor prognosis in patients increases stepwise. Compared with <2% WL, all-cause mortalities were 15.1%, 37% and 64.2% higher in 2-5%, 5-10%, and ≥10% WL, respectively. WL can effectively stratify the prognosis of both overall and site-specific cancers. The clinical prognostic thresholds for WL based on different BMI levels were 4.21% (underweight), 5.03% (normal), 6.33% (overweight), and 7.60% (obese). Multivariate logistic regression analysis showed that WL was independently associated with 90-day outcomes in patients with cancer. Compared with patients with <2% WL, those with ≥10% WL had more than twice the risk of 90-day outcomes (OR: 3.277, 95% CI: 2.287-4.694, P < 0.001). Systemic inflammation was a cause of WL deterioration. WL mediates 6.3-10.3% of the overall association between systemic inflammation and poor prognoses in patients with cancer. CONCLUSIONS: An individualized threshold for WL based on baseline BMI can be used for prognostic assessment in cancer patients. WL and BMI should be evaluated simultaneously in treatment decision-making, nutritional intervention, and prognosis discussions of patients with cancer.

Prognostic value of systemic inflammation and for patients with colorectal cancer cachexia.

BACKGROUND: The development and progression of cancer cachexia are connected to systemic inflammation and physical performance. However, few relevant studies have reported the survival outcomes prediction of systemic inflammation and physical performance in patients with colorectal cancer (CRC) cachexia. This study investigated the prognostic prediction value of systemic inflammation and performance status in patients with CRC cachexia. METHODS: This multicentre cohort study prospectively collected 905 patients with CRC (58.3% males, 59.3 ± 11.5 years old). Cancer cachexia was diagnosed according to the 2011 Fearon Cachexia Diagnostic Consensus. The prognostic value of systematic inflammatory indicators was determined using the area under the curve, concordance index, and multivariate survival analysis. Performance status was evaluated with Eastern Coopertive Oncology Group performance score (ECOG-PS). Survival data were analysed using univariate and multivariate Cox regression analyses. RESULTS: The area under the curve, concordance index and survival analysis showed that C-reactive protein (CRP), lymphocyte to CRP ratio (LCR) and CRP to albumin ratio (CAR) were more stable and consistent with the survival of patients with CRC, both in non-cachexia and cachexia populations. Among patients with CRC cachexia, high inflammation [low LCR, hazard ratio (HR) 95% confidence interval (95% CI) = 3.33 (2.08-5.32); high CAR, HR (95% CI) = 2.92 (1.88-4.55); high CRP, HR (95% CI) = 3.12 (2.08-4.67)] indicated a worse prognosis, compared with non-cachexia patients [low LCR, HR (95% CI) = 2.28 (1.65-3.16); high CAR, HR (95% CI) = 2.36 (1.71-3.25); high CRP, HR (95% CI) = 2.58 (1.85-3.60)]. Similarly, among patients with CRC cachexia, high PS [ECOG-PS 2, HR (95% CI) = 1.61 (1.04-2.50); ECOG-PS 3/4, HR (95% CI) = 2.91 (1.69-5.00]) indicated a worse prognosis, compared with patients with CRC without cachexia [ECOG-PS 2, HR (95% CI) = 1.28 (0.90-1.81); ECOG-PS 3/4, HR (95% CI) = 2.41 (1.32-4.39]). Patients with CRC cachexia with an ECOG-PS score of 2 or 3-4 and a high inflammation had a shorter median survival time, compared with patients with an ECOG-PS score of 0/1 and a low inflammation. CONCLUSIONS: The systemic inflammatory markers LCR, CAR and CRP have stable prognostic values in patients with CRC. The ECOG-PS may be an independent risk factor for CRC. Combined evaluation of systemic inflammation and ECOG-PS in patients with CRC cachexia could provide a simple survival prediction.