D-dimer, one of the canonical markers of hypercoagulability, was reported to be a potential prognostic marker of colorectal cancer. However, an inconsistent conclusion existed in several published studies. Thus, we performed this meta-analysis to provide a comprehensive insight into the prognostic role for pretreatment D-dimer in colorectal cancer. Six databases (English: Pubmed, Embase and Web of Science; Chinese: CNKI, Wangfang and VIP) were utilized for the literature retrieval. Hazard ratio (HR) was pooled by Stata 12.0. A total of fifteen studies (2283 cases) corresponded to this meta-analysis and provided available data to evaluate the prognostic role of D-dimer for colorectal cancer. The pooled HR reached 2.167 (95%. CI (confidence interval): 1.672–2.809, P < 0.001) utilizing random effect model due to obvious heterogeneity among the included studies (I2: 73.3%; P < 0.001). To explore the heterogeneity among the studies, we conducted a sensitivity analysis and found a heterogeneous study. After removing it, the heterogeneity reduced substantially (I2: 0%; P = 0.549) and we obtained a more convincing result by fixed effect model (HR = 2.143, 95% CI = 1.922–2.390, P < 0.001, 14 studies with 2179 cases). In summary, high pretreatment plasma D-dimer predicts poor survival of colorectal cancer based on the current evidence. Further prospective researches are necessary to confirm the role of D-dimer in colorectal cancer.

Background and Aim. Colorectal cancer (CRC) is the third most lethal cancer globally. This study sought to determine the feasibility of using red cell distribution width-to-lymphocyte ratio (RLR) as a tool to facilitate CRC detection. Methods. Seventy-eight healthy controls, 162 patients diagnosed with CRC, and 94 patients with colorectal polyps (CP) from June 2017 to October 2018 were retrospectively reviewed. Clinical data were obtained to analyze preoperative RLR level, and receiver operating characteristic (ROC) curve analysis was performed to estimate the potential role of RLR as a CRC biomarker. Results. RLR was higher in patients with CRC than in healthy participants (P < 0.05). ROC analysis indicated that combined detection of RLR and CEA appears to be a more effective marker to distinguish among controls, CP, and CRC patients, yielding 56% sensitivity and 90% specificity. RLR levels were significantly greater in those who had more advanced TNM stages (P < 0.05) and patients with distant metastasis stages (P < 0.05). Conclusions. RLR might serve as a potential biomarker for CRC diagnosis.

BackgroundLymph node metastasis (LNM) is a well-established prognostic factor for colon cancer. Preoperative LNM evaluation is relevant for planning colon cancer treatment. The aim of this study was to construct and evaluate a nomogram for predicting LNM in primary colon cancer according to pathological features.Patients and MethodsSix-hundred patients with clinicopathologically confirmed colon cancer (481 cases in the training set and 119 cases in the validation set) were enrolled in the Affiliated Cancer Hospital of Guangxi Medical University from January 2010 to December 2019. The expression of molecular markers (p53 and β-catenin) was determined by immunohistochemistry. Multivariate logistic regression was used to screen out independent risk factors, and a nomogram was established. The accuracy and discriminability of the nomogram were evaluated by consistency index and calibration curve.ResultsUnivariate logistic analysis revealed that LNM in colon cancer is significantly correlated (P &lt;0.05) with tumor size, grading, stage, preoperative carcinoembryonic antigen (CEA) level, and peripheral nerve infiltration (PNI). Multivariate logistic regression analysis confirmed that CEA, grading, and PNI were independent prognostic factors of LNM (P &lt;0.05). The nomogram for predicting LNM risk showed acceptable consistency and calibration capability in the training and validation sets.ConclusionsPreoperative CEA level, grading, and PNI were independent risk factor for LNM. Based on the present parameters, the constructed prediction model of LNM has potential application value.

Background: Tumor status can affect patient prognosis. Prognostic nutritional index (PNI), as a nutritional indicator, is closely related to the prognosis of cancer. However, few studies have examined the combined prognostic value of CEA and PNI in patients. This study investigated the relationship between CEA/PNI and prognosis of colon cancer patients.Methods: A total of 513 patients with stage II–III colon cancer who underwent curative resection at two medical centers from 2009 to 2019 were included. Clinicopathological factors were assessed and overall survival (OS) was assessed in a cohort of 413 patients. Multivariate analysis was used to identify independent prognostic variables to construct histograms predicting 1-year and 3-year OS. Data from 100 independent patients in the validation group was used to validate the prognostic model.Results: The median OS time was 33.6 months, and mortality was observed in 54 patients. Multivariate analysis revealed that preoperative CEA/PNI, lymph node metastasis, peripheral nerve invasion, operation mode, and postoperative chemotherapy were independent factors for prognosis evaluation and thus were utilized to develop the nomogram. The C-index was 0.788 in the learning set and 0.836 in the validation set. The calibration curves reached favorable consensus among the 1-, 3-year OS prediction and actual observation.Conclusion: The combined use of CEA and PNI is an independent prognostic factor and thus can serve as a basis for a model to predict the prognosis of patients with stage II–III colon cancer.