Prediction of lymph node metastasis in T1 colorectal cancer based on combination of body composition and vascular invasion.

OBJECTIVES: Lymph node metastasis (LNM) in colorectal cancer (CRC) patients is not only associated with the tumor's local pathological characteristics but also with systemic factors. This study aims to assess the feasibility of using body composition and pathological features to predict LNM in early stage colorectal cancer (eCRC) patients. METHODS: A total of 192 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in the study. The cross-sectional areas of skeletal muscle, subcutaneous fat, and visceral fat at the L3 vertebral body level in CT scans were measured using Image J software. Logistic regression analysis were conducted to identify the risk factors for LNM. The predictive accuracy and discriminative ability of the indicators were evaluated using receiver operating characteristic (ROC) curves. Delong test was applied to compare area under different ROC curves. RESULTS: LNM was observed in 32 out of 192 (16.7%) patients with eCRC. Multivariate analysis revealed that the ratio of skeletal muscle area to visceral fat area (SMA/VFA) (OR = 0.021, p = 0.007) and pathological indicators of vascular invasion (OR = 4.074, p = 0.020) were independent risk factors for LNM in eCRC patients. The AUROC for SMA/VFA was determined to be 0.740 (p < 0.001), while for vascular invasion, it was 0.641 (p = 0.012). Integrating both factors into a proposed predictive model resulted in an AUROC of 0.789 (p < 0.001), indicating a substantial improvement in predictive performance compared to relying on a single pathological indicator. CONCLUSION: The combination of the SMA/VFA ratio and vascular invasion provides better prediction of LNM in eCRC.

Preoperative controlling nutritional status as an optimal prognostic nutritional index to predict the outcome for colorectal cancer.

BACKGROUND: The controlling nutritional status (CONUT) score effectively reflects a patient's nutritional status, which is closely related to cancer prognosis. This study investigated the relationship between the CONUT score and prognosis after radical surgery for colorectal cancer, and compared the predictive ability of the CONUT score with other indexes. AIM: To analyze the predictive performance of the CONUT score for the survival rate of colorectal cancer patients who underwent potentially curative resection. METHODS: This retrospective analysis included 217 patients with newly diagnosed colorectal. The CONUT score was calculated based on the serum albumin level, total lymphocyte count, and total cholesterol level. The cutoff value of the CONUT score for predicting prognosis was 4 according to the Youden Index by the receiver operating characteristic curve. The associations between the CONUT score and the prognosis were performed using Kaplan-Meier curves and Cox regression analysis. RESULTS: Using the cutoff value of the CONUT score, patients were stratified into CONUT low (n = 189) and CONUT high groups (n = 28). The CONUT high group had worse overall survival (OS) (P = 0.013) and relapse-free survival (RFS) (P = 0.015). The predictive performance of CONUT was superior to the modified Glasgow prognostic score, the prognostic nutritional index, and the neutrophil-to-lymphocyte ratio. Meanwhile, the predictive performances of CONUT + tumor node metastasis (TNM) stage for 3-year OS [area under the receiver operating characteristics curve (AUC) = 0.803] and 3-year RFS (AUC = 0.752) were no less than skeletal muscle mass index (SMI) + TNM stage. The CONUT score was negatively correlated with SMI (P < 0.01). CONCLUSION: As a nutritional indicator, the CONUT score could predict long-term outcomes after radical surgery for colorectal cancer, and its predictive ability was superior to other indexes. The correlation between the CONUT score and skeletal muscle may be one of the factors that play a predictive role.

Gastric microbiota: an emerging player in gastric cancer.

Gastric cancer (GC) is a common cancer worldwide with a high mortality rate. Many microbial factors influence GC, of which the most widely accepted one is Helicobacter pylori (H. pylori) infection. H. pylori causes inflammation, immune reactions and activation of multiple signaling pathways, leading to acid deficiency, epithelial atrophy, dysplasia and ultimately GC. It has been proved that complex microbial populations exist in the human stomach. H. pylori can affect the abundance and diversity of other bacteria. The interactions among gastric microbiota are collectively implicated in the onset of GC. Certain intervention strategies may regulate gastric homeostasis and mitigate gastric disorders. Probiotics, dietary fiber, and microbiota transplantation can potentially restore healthy microbiota. In this review, we elucidate the specific role of the gastric microbiota in GC and hope these data can facilitate the development of effective prevention and therapeutic approaches for GC.