Association between dietary quality and accelerated aging: a cross-sectional study of two cohorts.

Background: Diet quality significantly influences aging processes and age-related health outcomes. This study aims to explore the association between dietary quality and accelerated aging in two large cohorts. Methods: This study collected data from the Kailuan and National Health and Nutrition Examination Survey (NHANES) cohorts; participants' dietary quality was evaluated using the American Heart Association (AHA) dietary score and Healthy Eating Index-2015 (HEI-2015), respectively. Accelerated aging in participants was determined by calculating the difference between phenotypic age and chronological age. Logistic regression models were used to explore the association between dietary quality scores and accelerated aging. Additionally, variations in this association across different subgroups were investigated. To minimize the influence of excessive aging, individuals aged 75 and above were excluded in sensitivity analyses. Results: In this study, we included 33 701 participants (27.3% female, mean age 57.29 ± 11.88) from the Kailuan study and 9285 participants (50.6% female, mean age 49.83 ± 17.62) from NHANES. In the Kailuan cohort, individuals with dietary scores ranging from 3 to 5 exhibited a 22% lower risk of accelerated aging compared to those scoring between 0 and 2 (OR = 0.78, 95% CI = 0.72-0.85). Similarly, in the NHANES cohort, participants in the highest quartile of HEI-2015 experienced a 34% reduction in the risk of accelerated aging compared to those in the lowest quartile (OR = 0.66, 95% CI = 0.52-0.84). Subgroup analyses underscored a more pronounced association between dietary quality and accelerated aging among males and individuals with unhealthy lifestyles. Sensitivity analyses confirmed the robustness of the association between dietary quality and accelerated aging. Conclusion: In summary, our study found a significant association between dietary quality and accelerated aging. Better dietary quality was associated with a reduced risk of accelerated aging, particularly among males, smokers, and participants with unhealthy lifestyles.

The effect of hyperlipidemia on overall survival in patients with cancer was differentiated by BMI and hyperlipidemia type.

BACKGROUND AND AIMS: The impact of lipids on the overall survival (OS) of patients with malignancy has not yet been clarified. This study aimed to evaluate the effect of hyperlipidemia on the OS among Chinese patients based on Body Mass Index (BMI) stratifications and hyperlipidemia types. METHOD: The patients in this study were derived from the Investigation of the Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) trial. Kaplan-Meier was used to draw the survival curve, and the log-rank test was used to estimate the survival rates between each group. Cox proportional hazards regression models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI). RESULTS: A total of 9054 patients were included in the final study, with a median age of 59 years, and 55.3% (5004) of them were males. Regarding types of hyperlipidemia, only low high-density lipoprotein was an independent risk factor for the prognosis of all patients (HR = 1.35, 95% CI: 1.25-1.45, P < 0.001), while high total cholesterol (HR = 1.01, 95% CI: 0.90-1.15, P = 0.839) and high low-density lipoprotein (HR = 1.03, 95%CI: 0.91-1.16, P = 0.680) were not. In terms of BMI stratification, the effect of triglycerides on prognosis varied; high triglycerides were an independent risk factor for the prognosis of underweight patients (HR = 1.56, 95% CI:1.05-2.32, P = 0.027) and a protective factor for overweight patients (HR = 0.75, 95% CI: 0.63-0.89, P = 0.001). However, for normal-weight patients, there was no significant statistical difference (HR = 0.88, 95%CI: 0.75-1.03, P = 0.108). CONCLUSIONS: The impact of hyperlipidemia on the OS among patients with cancer varied by different BMI and hyperlipidemia types. BMI and hyperlipidemia type ought to be considered in combination to estimate the prognosis of patients with malignancy.

Performance of anthropometry-based and bio-electrical impedance-based muscle-mass indicators in the Global Leadership Initiative on Malnutrition criteria for predicting prognosis in patients with cancer.

BACKGROUND: Reduced muscle mass is a criterion for diagnosing malnutrition using the Global Leadership Initiative on Malnutrition (GLIM) criteria; however, the choice of muscle-mass indicators within the GLIM criteria remains contentious. This study aimed to establish muscle-measurement-based GLIM criteria using data from bio-electrical impedance analysis (BIA) and anthropometric evaluations and evaluate their ability to predict overall survival (OS), short-term outcomes, and healthcare burden in patients with cancer. METHODS: This was a multicenter, prospective study that commenced in 2013 and enrolled participants from various clinical centers across China. We constructed GLIM criteria based on various muscle measurements, including fat-free mass index (FFMI), skeletal muscle index (SMI), calf circumference (CC), midarm circumference (MAC), midarm muscle circumference (MAMC), and midarm muscle area (MAMA). Survival was estimated using the Kaplan-Meier method and survival curves were compared using the log-rank test. Cox proportional hazards regression was used to assess the independent association between the GLIM criteria and OS. The discriminatory performance of different muscle-measurement-based GLIM criteria for mortality was evaluated using Harrell's concordance index (C-index). Logistic regression was used to evaluate the association of the GLIM criteria with short-term outcomes and healthcare burden. RESULTS: A total of 4769 patients were included in the analysis, of whom 1659 (34.8%) died during the study period. The Kaplan-Meier curves demonstrated that all muscle-measurement-based GLIM criteria significantly predicted survival in patients with cancer (all p < 0.001). The survival rate of malnourished patients was approximately 10% lower than that of non-malnourished patients. Cox proportional hazards regression showed that all the muscle-measurement-based GLIM could independently predict the OS of patients (all p < 0.001). The prognostic discrimination was as follows: MAMC (Chi-square: 79.61) > MAMA (Chi-square: 79.10) > MAC (Chi-square: 64.09) > FFMI (Chi-square: 62.33) > CC (Chi-square: 58.62) > ASMI (Chi-square: 57.29). In comparison to the FFMI-based GLIM criteria, the ASMI-based criteria (-0.002, 95% CI: -0.006 to 0.002, p = 0.334) and CC-based criteria (-0.003, 95% CI: -0.007 to 0.002, p = 0.227) did not exhibit a significant advantage. However, the MAC-based criteria (0.001, 95% CI: -0.003 to 0.004, p = 0.776), MAMA-based criteria (0.004, 95% CI: 0.000-0.007, p = 0.035), and MAMC-based criteria (0.005, 95% CI: 0.000-0.007, p = 0.030) outperformed the FFMI-based GLIM criteria. Logistic regression showed that muscle measurement-based GLIM criteria predicted short-term outcomes and length of hospital stay in patients with cancer. CONCLUSION: All muscle measurement-based GLIM criteria can effectively predict OS, short-term outcomes, and healthcare burden in patients with cancer. Anthropometric measurement-based GLIM criteria have potential for clinical application as an alternative to BIA-based measurement.

Development and validation of an inflammatory biomarkers model to predict gastric cancer prognosis: a multi-center cohort study in China.

BACKGROUND: Inflammatory factors have increasingly become a more cost-effective prognostic indicator for gastric cancer (GC). The goal of this study was to develop a prognostic score system for gastric cancer patients based on inflammatory indicators. METHODS: Patients' baseline characteristics and anthropometric measures were used as predictors, and independently screened by multiple machine learning(ML) algorithms. We constructed risk scores to predict overall survival in the training cohort and tested risk scores in the validation. The predictors selected by the model were used in multivariate Cox regression analysis and developed a nomogram to predict the individual survival of GC patients. RESULTS: A 13-variable adaptive boost machine (ADA) model mainly comprising tumor stage and inflammation indices was selected in a wide variety of machine learning models. The ADA model performed well in predicting survival in the validation set (AUC = 0.751; 95% CI: 0.698, 0.803). Patients in the study were split into two sets - "high-risk" and "low-risk" based on 0.42, the cut-off value of the risk score. We plotted the survival curves using Kaplan-Meier analysis. CONCLUSION: The proposed model performed well in predicting the prognosis of GC patients and could help clinicians apply management strategies for better prognostic outcomes for patients.

Sarcopenic Obesity and Outcomes for Patients With Cancer.

Importance: The European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) have recently proposed a consensus definition and diagnostic criteria for sarcopenic obesity (SO). Objective: To implement the ESPEN-EASO diagnostic algorithm to investigate the prevalence of SO and its association with outcomes in patients with solid tumor cancers, with particular regard to associations among SO, overall survival (OS), and patient quality of life (QoL). Design, Setting, and Participants: This prospective cohort study included patients diagnosed with solid tumor starting in May 7, 2013, with the last follow-up on June 30, 2022. Patients with solid tumors were categorized into SO and non-SO groups according to ESPEN-EASO criteria. The primary outcome was OS and the secondary outcomes included patient QoL and risk of intensive care unit (ICU) admission. Data were analyzed from June to December 2023. Results: A total of 6790 patients were included in the study (mean [SD] age, 59.64 [10.77] years; 3489 were female [51.4%]). The prevalence of SO was 4.36% (296 of 6790) in the whole cohort and 14.98% (296 of 1976) in the subgroup with obesity. SO prevalence increased with age. During a median (IQR) follow-up period of 6.83 (5.67-7.04) years, 2103 patients died. Cox regression analysis indicated that SO was independently associated with lower OS (hazard ratio [HR], 1.54; 95% CI, 1.23-1.92), which was observed in both men (HR, 1.51; 95% CI, 1.09-2.10) and women (HR, 1.53; 95% CI, 1.12-2.07). SO was also associated with poorer QoL and higher risk of ICU admission (odds ratio, 2.39; 95% CI, 1.06-5.29). Among the diagnostic components of SO, low hand grip strength (HGS) was the only SO component associated with poor OS (HR, 1.15; 95% CI, 1.04-1.28). Conclusions and Relevance: This cohort study of SO found that SO was significantly associated with lower OS, poorer QoL, and higher risk of ICU admission. Weak HGS, 1 of the diagnostic conditions, was the only component of SO associated with OS. The ESPEN-EASO algorithm appears to be an applicable tool to identify cancer-associated SO, which represents a major clinical complication and factor associated with risk for poor outcomes in these patients.

Ginsenoside Rb3 alleviates the formation of osteoclasts induced by periodontal ligament fibroblasts in the periodontitis microenvironment through the STAT3 pathway.

This study explores the potential role and mechanism of Ginsenoside Rb3 (Rb3) in modulating osteoclastogenesis induced by human periodontal ligament fibroblasts (hPLFs) within the periodontitis microenvironment. We investigated the anti-inflammatory effects of Rb3 on hPLFs stimulated with Porphyromonas gingivalis lipopolysaccharide (P.g-LPS) utilizing quantitative polymerase chain reaction (qPCR) and enzyme-linked immunosorbent assay techniques. Moreover, the functional role of Rb3 in hPLFs-induced osteoclast formation was assessed by treating human bone marrow-derived macrophages (hBMMs) with conditioned medium from hPLFs, followed by analyses through qPCR, western blot analysis, and staining for tartrate-resistant acid phosphatase (TRAP) and phalloidin. The impact of Rb3 on the activation of the STAT3 signaling pathway was determined via western blot analysis. Results indicated that Rb3 treatment significantly suppressed the upregulation of pro-inflammatory cytokines (TNF-α, IL-1ß, IL-6, MCP-1, and IL-18) at both gene and protein levels in hPLFs induced by P.g-LPS. Furthermore, conditioned medium from Rb3 plus P.g-LPS treated hPLFs notably decreased the number of TRAP-positive cells, actin ring formations, and the expression of osteoclast marker genes (including CTSK, NFATC1, and ACP5). Rb3 also inhibited the P.g-LPS-induced activation of the STAT3 pathway, with the activation of STAT3 partially reversing the effects of Rb3 on inflammation and osteoclast differentiation. Collectively, Rb3 ameliorates inflammation in P.g-LPS-stimulated hPLFs and reduces hPLFs-induced osteoclastogenesis by inhibiting the STAT3 signaling pathway, suggesting its potential as a therapeutic agent for periodontitis.

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.

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.

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.

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.

Early-onset and later-onset cancer: trends, risk factors, and prevention in Northern China.

The characteristics of early-onset (onset age <50 years) and later-onset (onset age ≽ 50 years) cancers differ significantly. Identifying novel risk factors for both types of cancer is crucial for increasing awareness of cancer prevention and for reducing its burden. This study aimed to analyze the trends in incidence and risk factors for early-onset and late-onset cancers. We conducted a prospective study by drawing data from the Kailuan Study. This study included 6,741 participants with cancer (624 with early-onset cancer and 6,117 with later-onset cancer) and 6,780 matched controls among the 186,249 participants who underwent Kailuan health examinations from 2006 to 2019. The primary outcomes were cancer incidence rates, and associated risk factors for early- and later-onset cancer. Weighted Cox regression was used to calculate hazard ratios and 95% confidence intervals of each exposure factor for early- and later-onset cancer by cancer type. Population-attributable risk proportions were used to estimate the number of cases that could be prevented by eliminating a risk factor from the population. Except for liver cancer, incidence rates for nearly all types of cancer increased during the study period. Smoking, alcohol consumption, lipid metabolism disorders, hypertension, diabetes mellitus, fatty liver, and inflammation were associated with a significantly increased risk of cancer at multiple sites, but risk factors for cancer incidence differed by site. Smoking, alcohol consumption, inflammation, and hypertension were the major contributors to preventable cancer. The incidence of several different types of cancer, including early-onset cancer, is increasing in northeastern China. Differences in risk factors between early-onset and later-onset malignancies may contribute to the divergence in the observed changes in incidence trends between these two specific types of cancer.

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.

Deciphering the folate puzzle: Unraveling the impact of genetic variations and metabolites on cancer risk.

The C677T polymorphism in the MTHFR gene and its role in folate metabolism, impacting serum folate metabolites like THF and 5-MTHF, is a critical but underexplored area in cancer research. This nested case-control study utilized data from CHHRS, involving 87,492 hypertensive adults without prior cancer. During a median of 2.02 years, we identified 1332 cancer cases and matched controls based on age, sex, and residency. Serum levels of folate, THF, and 5-MTHF were measured, and the MTHFR C677T gene polymorphism was considered. Statistical analyses included restricted cubic spline regression and conditional logistic regression models. Serum THF levels were inversely associated with overall cancer risk (ORper SD = 0.90, 95% CI = 0.82-0.99), while 5-MTHF levels showed a negative association in the general cohort (ORQ3 vs. Q1 = 0.76, 95% CI = 0.60-0.96; ORQ4 vs. Q1 = 0.75, 95% CI = 0.58-0.98) and in individuals with MTHFR C677T (CC + CT) polymorphism (ORper SD = 0.87, 95% CI = 0.77-0.99; ORQ4 VS. Q1 = 0.79, 95% CI = 0.61-0.98), but a positive association in the MTHFR C677T (TT) subgroup (ORper SD = 1.89, 95% CI = 1.02-3.72; ORQ4 VS. Q1 = 2.17, 95% CI = 1.06-8.21). The impact of folate, THF, and 5-MTHF on cancer risk varied significantly across different cancer types and MTHFR C677T genotypes. This study provides novel insights into the variable effects of folate and its metabolites on cancer risk, influenced by genetic factors like the MTHFR C677T polymorphism and cancer type.

Unexpected mutations occurred in CRISPR/Cas9 edited Drosophila analyzed by deeply whole genomic sequencing.

CRISPR/Cas9 possesses the most promising prospects as a gene-editing tool in post-genomic researches. It becomes an epoch-marking technique for the features of speed and convenience of genomic modification. However, it is still unclear whether CRISPR/Cas9 gene editing can cause irreversible damage to the genome. In this study, we successfully knocked out the WHITE gene in Drosophila, which governs eye color, utilizing CRISPR/Cas9 technology. Subsequently, we conducted high-throughput sequencing to assess the impact of this editing process on the stability of the entire genomic profile. The results revealed the presence of numerous unexpected mutations in the Drosophila genome, including 630 SNVs (Single Nucleotide Variants), 525 Indels (Insertion and Deletion) and 425 MSIs (microsatellite instability). Although the KO (knockout) specifically occurred on chromosome X, the majority of mutations were observed on chromosome 3, indicating that this effect is genome-wide and associated with the spatial structure between chromosomes, rather than being solely limited to the location of the KO gene. It is worth noting that most of the mutations occurred in the intergenic and intron regions, without exerting any significant on the function or healthy of the animal. In addition, the mutations downstream of the knockout gene well beyond the upstream. This study has found that gene editing can lead to unexpected mutations in the genome, but most of these mutations are harmless. This research has deepened our understanding of CRISPR/Cas9 and broadened its application prospects.

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.

The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information.

BACKGROUND & AIMS: The key step of the Global Leadership Initiative on Malnutrition (GLIM) is nutritional risk screening, while the most appropriate screening tool for colorectal cancer (CRC) patients is yet unknown. The GLIM diagnosis relies on weight loss information, and bias or even failure to recall patients' historical weight can cause misestimates of malnutrition. We aimed to compare the suitability of several screening tools in GLIM diagnosis, and establish machine learning (ML) models to predict malnutrition in CRC patients without weight loss information. METHODS: This multicenter cohort study enrolled 4487 CRC patients. The capability of GLIM diagnoses combined with four screening tools in predicting survival probability was compared by Kaplan-Meier curves, and the most accurate one was selected as the malnutrition reference standard. Participants were randomly assigned to a training cohort (n = 3365) and a validation cohort (n = 1122). Several ML approaches were adopted to establish models for predicting malnutrition without weight loss data. We estimated feature importance and reserved the top 30% of variables for retraining simplified models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess and compare model performance. RESULTS: NRS-2002 was the most suitable screening tool for GLIM diagnosis in CRC patients, with the highest hazard ratio (1.59; 95% CI, 1.43-1.77). A total of 2076 (46.3%) patients were malnourished diagnosed by GLIM combined with NRS-2002. The simplified random forest (RF) model outperformed other models with an AUC of 0.830 (95% CI, 0.805-0.854), and accuracy, sensitivity and specificity were 0.775, 0.835 and 0.742, respectively. We deployed an online application based on the simplified RF model to accurately estimate malnutrition probability in CRC patients without weight loss information (https://zzuwtt1998.shinyapps.io/dynnomapp/). CONCLUSIONS: Nutrition Risk Screening 2002 was the optimal initial nutritional risk screening tool in the GLIM process. The RF model outperformed other models, and an online prediction tool was developed to properly identify patients at high risk of malnutrition.

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.

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.

Relationship between educational level and survival of patients with cancer: A multicentre cohort study.

BACKGROUND: Although socioeconomic factors are important determinants of population mortality, the effect of educational level on the survival of patients with cancer in China is unclear. This study aimed to assess whether educational level is associated with the prognosis of patients with cancer and to explore the mediators of this association. METHODS: This multicentre cohort study included 18,251 patients diagnosed with cancer between May 2013 and December 2018. The main parameters measured were overall survival (OS) and all-cause mortality. The relationship between educational level and all-cause mortality was assessed using multifactor-corrected Cox survival analysis. Logistic regression was used to analyze the association between educational level and patient-generated subjective global assessment (PG-SGA). RESULTS: The mean age of the 18,251 participants (men, 9939 [54.4%]) was 57.37 ± 11.66 years. Multifactorial survival analysis showed that patients survived longer with increasing education (university and above vs. elementary school and below; p = p = <0.001, HR = 0.84, 95% CI: 0.77-0.92), and the differences were statistically significant in different subgroups. The potential impact factors included sex, age, TNM stage, and PG-SGA score. Logistic regression showed a significant negative association between educational level and the modifiable factor PG-SGA (secondary vs. primary and below; p = 0.004, HR = 0.90, 95% CI: 0.83-0.97; university and above vs. primary and below; p < 0.001, HR = 0.79, 95% CI: 0.71-0.88). CONCLUSIONS: Educational level was a significant prognostic factor for patients with cancer, independent of other known prognostic factors. This association was further improved by modifying the nutritional status.

Integrated neutrophil-to-lymphocyte ratio and handgrip strength better predict survival in patients with cancer cachexia.

OBJECTIVES: Systemic inflammation and skeletal muscle strength play crucial roles in the development and progression of cancer cachexia. In this study we aimed to evaluate the combined prognostic value of neutrophil-to-lymphocyte ratio (NLR) and handgrip strength (HGS) for survival in patients with cancer cachexia. METHODS: This multicenter cohort study involved 1826 patients with cancer cachexia. The NLR-HGS (NH) index was defined as the ratio of neutrophil-to-lymphocyte ratio to handgrip strength. Harrell's C index and receiver operating characteristic (ROC) curve analysis were used to assess the prognosis of NH. Kaplan-Meier analysis and Cox regression models were used to evaluate the association of NH with all-cause mortality. RESULTS: Based on the optimal stratification, 380 women (NH > 0.14) and 249 men (NH > 0.19) were classified as having high NH. NH has shown greater predictive value compared to other indicators in predicting the survival of patients with cancer cachexia according to the 1-, 3-, and 5-y ROC analysis and Harrell's C index calculation. Multivariate survival analysis showed that higher NH was independently associated with an increased risk of death (hazard ratio = 1.654, 95% confidence interval = 1.389-1.969). CONCLUSION: This study demonstrates that the NH index, in combination with NLR and HGS, is an effective predictor of the prognosis of patients with cancer cachexia. It can offer effective prognosis stratification and guidance for their treatment.