Serum C-Reactive Protein-to-Body Mass Index Ratio Predicts Overall Survival in Patients With Resected Colorectal Cancer.

BACKGROUND AND PURPOSE: Systemic inflammation and nutritional status have been shown to be associated with the prognosis of colorectal cancer. The purpose of this study was to evaluate the impact of the serum C-reactive protein-to-body mass index ratio on the prognosis of patients with curatively resected colorectal cancer. METHODS: We conducted a retrospective analysis of a database of 2,471 eligible patients with colorectal cancer who underwent curative resection at our hospital between 2004 and 2019. The optimal cut-off for CPR-to-BMI ratio was determined using maximally selected rank statistics. Patients were divided into 2 groups according to the cut-off value of the serum C-reactive protein-to-body mass index ratio. Kaplan-Meier curves and Cox regression analysis were used to compare overall survival. A two-sided P-value < 0.05 was considered statistically significant. RESULTS: The proportion of patients with a high C-reactive protein-to-body mass index ratio increased with increasing age, male sex, right-sided colon cancer, poorly differentiated tumors, advanced-stage disease, local/distant metastases, tumor-node-metastasis stage, and microsatellite instability. In subgroup analysis according to tumor-node-metastasis stage, the overall survival of the high C-reactive protein-to-body mass index ratio group was significantly shorter than that of the low C-reactive protein-to-body mass index ratio group (P < 0.001). Multivariate analysis identified age, differentiation, tumor-node-metastasis stage, carcinoembryonic antigen level, and the C-reactive protein-to-body mass index ratio as independent poor prognostic factors for overall survival. CONCLUSIONS: The C-reactive protein-to-body mass index ratio predicts the prognosis of patients with curatively resected colorectal cancer and is an independent risk factor for overall survival in patients with colorectal cancer.

Prognostic Value of Combined Preoperative Carcinoembryonic Antigen and Prognostic Nutritional Index in Patients With Stage II-III Colon Cancer.

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.

Preoperative Predictors of Lymph Node Metastasis in Colon Cancer.

BACKGROUND: Lymph 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 METHODS: Six-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 ß-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. RESULTS: Univariate logistic analysis revealed that LNM in colon cancer is significantly correlated (P <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 <0.05). The nomogram for predicting LNM risk showed acceptable consistency and calibration capability in the training and validation sets. CONCLUSIONS: Preoperative 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.

A Novel Nomogram for Individually Predicting of Vascular Invasion in Gastric Cancer.

PURPOSE: Vascular invasion (VI) is associated with recurrence and is an indicator of poor prognosis in gastric cancer (GC). Pre-operative identification of VI may guide the selection of the optimal surgical approach and assess the requirement for neoadjuvant therapy. METHODS: A total of 271 patients were retrospectively collected and randomly allocated into the training and validation datasets. The least absolute shrinkage and selection operator regression model was used to select potentially relevant features, and multivariable logistic regression analysis was used to develop the nomogram. RESULTS: The nomogram consisted of pre-operative serum complement C3 levels, duration of symptoms, pre-operative computed tomography stage, abdominal distension and undifferentiated carcinoma. The nomogram provided good calibration for both the training and the validation set, with area under the curve values of 0.792 and 0.774. Decision curve analysis revealed that the nomogram was clinically useful. CONCLUSION: The present study constructed a nomogram for the pre-operative prediction of VI in patients with GC. The nomogram may aid the identification of high-risk patients and aid the optimization of pre-operative decision-making.

Nomogram for predicting overall survival in stage II-III colorectal cancer.

PURPOSE: The overall survival (OS) of patients diagnosed with stage II-III colorectal cancer (CRC) can vary greatly, even between patients with the same tumor stage. We aimed to design a nomogram to predict OS in resected, stage II-III CRC and stratify patients with CRC into different risk groups. PATIENTS AND METHODS: Based on data from 873 patients with CRC, we used univariate Cox regression analysis to select the significant prognostic features, which were subjected to the least absolute shrinkage and selection operator (LASSO) regression algorithm for feature selection. Cross-validation was used to confirm suitable tuning parameters (λ) for LASSO logistic regression. Then, the nomogram was used to estimate 3- and 5-year OS based on the multivariable Cox regression model. The survival curves of the two groups were produced using the Kaplan-Meier method. Risk group stratification was performed to assess the predictive capacity of the nomogram. RESULTS: Preoperative mean platelet volume, preoperative platelet distribution width, monocytes, and postoperative adjuvant chemotherapy were identified as independent prognostic factors by LASSO regression and integrated for the construction of the nomogram. The nomogram provided good discrimination, with C-indices of 0.67 and 0.69 for the training and validation sets, respectively. Calibration plots illustrated excellent agreement between the nomogram predictions and actual observations for 3- and 5-year OS. Moreover, a significant difference in OS was shown between patients stratified into different risk groups (P < .001). CONCLUSION: We constructed and validated an original predictive nomogram for OS in patients with CRC after surgery, facilitating physicians to appraise the individual survival of postoperative patients accurately and identify high-risk patients who need more aggressive treatment and follow-up strategies.

Systematic profiling of alternative splicing events and splicing factors in left- and right-sided colon cancer.

Left- and right-sided colon cancer (LC and RC) differ substantially in their molecular characteristics and prognoses, and are thus treated using different strategies. We systematically analyzed alternative splicing (AS) events and splicing factors in LC and RC. RNA-seq data were used for genome-wide profiling of AS events that could distinguish LC from RC. The Exon Skip splicing pattern was more common in RC, while the Retained Intron pattern was more common in LC. The AS events that were upregulated in RC were enriched for genes in the axon guidance pathway, while those that were upregulated in LC were enriched for genes in immune-related pathways. Prognostic models based on differentially expressed AS events were built, and a prognostic signature based on these AS events performed well for risk stratification in colon cancer patients. A correlation network of differentially expressed AS events and differentially expressed splicing factors was constructed, and RBM25 was identified as the hub gene in the network. In conclusion, large differences in AS events may contribute to the phenotypic differences between LC and RC. The differentially expressed AS events reported herein could be used as biomarkers and treatment targets for colon cancer.