Creation and Validation of a Survival Nomogram Based on Immune-Nutritional Indexes for Colorectal Cancer Patients

Analysis of cancer-specific survival in patients with metastatic colorectal cancer: A evidence-based medicine study

BACKGROUND

Metastatic colorectal cancer (mCRC) is a common malignancy whose treatment has been a clinical challenge. Cancer-specific survival (CSS) plays a crucial role in assessing patient prognosis and treatment outcomes. However, there is still limited research on the factors affecting CSS in mCRC patients and their correlation.

AIM

To predict CSS, we developed a new nomogram model and risk grading system to classify risk levels in patients with mCRC.

METHODS

Data were extracted from the United States Surveillance, Epidemiology, and End Results database from 2018 to 2023. All eligible patients were randomly divided into a training cohort and a validation cohort. The Cox proportional hazards model was used to investigate the independent risk factors for CSS. A new nomogram model was developed to predict CSS and was evaluated through internal and external validation.

RESULTS

A multivariate Cox proportional risk model was used to identify independent risk factors for CSS. Then, new CSS columns were developed based on these factors. The consistency index (C-index) of the histogram was 0.718 (95%CI: 0.712-0.725), and that of the validation cohort was 0.722 (95%CI: 0.711-0.732), indicating good discrimination ability and better performance than tumor-node-metastasis staging (C-index: 0.712-0.732). For the training set, 0.533, 95%CI: 0.525-0.540; for the verification set, 0.524, 95%CI: 0.513-0.535. The calibration map and clinical decision curve showed good agreement and good potential clinical validity. The risk grading system divided all patients into three groups, and the Kaplan-Meier curve showed good stratification and differentiation of CSS between different groups. The median CSS times in the low-risk, medium-risk, and high-risk groups were 36 months (95%CI: 34.987-37.013), 18 months (95%CI: 17.273-18.727), and 5 months (95%CI: 4.503-5.497), respectively.

CONCLUSION

Our study developed a new nomogram model to predict CSS in patients with synchronous mCRC. In addition, the risk-grading system helps to accurately assess patient prognosis and guide treatment.

Study on the correlation between controlling nutritional status score and clinical biochemical indicators in patients with colorectal cancer

Purpose

The controlling nutritional status (CONUT) score is an important tool for predicting the prognosis of colorectal cancer (CRC); however, its effectiveness is relatively insufficient. This study aimed to screen for more effective clinical indicators as supplements to the CONUT scoring system and improve the predictive value of CRC prognosis.

Patients and methods

Between 2014 and 2020, the clinical information of all CRC patients in our unit was retrospectively collected, and the CONUT scores were calculated based on the levels of serum albumin (ALB), lymphocytes (LC), and total cholesterol. The included patients were divided into the following three groups: normal nutrition (0-1), mild malnutrition (2-4), and moderate-to-severe malnutrition (5-12). The correlations between the CONUT score and baseline characteristics and clinical indicators were evaluated.

Results

This study ultimately included 5014 CRC patients. The nutritional status of patients with colon cancer (CC) was worse than that of rectal cancer (RC). The nutritional status was worse in men than in women. The older the patient, the poorer the nutritional status, and the poorer the nutritional status, the longer the hospital stay. In addition, poor nutritional status in patients is indicated by higher values of neutrophils (NE), monocytes (MC), eosinophils (EOS), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), carcinoembryogenic antigen (CEA), and lower values of white blood cells (WBC), basophils (BAS), haemoglobin (HB), total protein (TP), triglycerides (TG), low density lipoprotein (LDL), aspartate transaminase (AST), and blood urea nitrogen (BUN), which was statistically significant (P < 0.05). Indicators that significantly correlated with the CONUT score reflected the immune nutritional status, including WBC (odds ratio [OR] = 0.036, P < 0.001), NE (OR = 30.815, P < 0.001), MC (OR = 41.388, P < 0.001), EOS (OR = 27.577, P < 0.001), BAS (OR = 0.006, P = 0.046), and LDL (OR = 0.319, P < 0.001).

Conclusion

Additional variables such as WBC, NE, MC, EOS, BAS, and LDL may be used as supplementary indicators in the CONUT scoring system to more effectively predict the clinical prognosis of CRC patients.

Prognostic Utility of Platelet-to-Albumin Ratio among Critically Ill Patients with Colorectal Cancer: A Propensity Score Matching Study

The platelet-to-albumin ratio (PAR) was developed to evaluate inflammatory and nutritional status among patients. The primary goal of the current study was to gain insight into the prognostic role of PAR in critically ill patients with colorectal cancer (CRC). The secondary aim was to develop and verify a clinical model including PAR for the prediction of 28-day mortality. This observational, multicenter study used data from the Medical Information Mart for Intensive Care (MIMIC) IV, e-ICU databases, and Union cohort. Data from 776 critically ill patients with CRC were from the e-ICU database, 219 from the MIMC-IV database, and 135 from the Wuhan Union Hospital. Propensity score matching (PSM) analysis, along with inverse probability treatment weighting, was used to control the influence of confounding factors. Support vector machine (SVM) and LASSO Cox models were then applied to identify significant metrics associated with 28-day mortality in the test cohort. Receiver operating curve (ROC) analysis, along with sensitivity and specificity, was measured to assess the predictive performances of PAR and the survival nomogram. The threshold value for PAR was 8.6, and patients with high PAR (≥8.6) experienced higher 28-day mortality compared to those with low PAR (<8.6). ROC curve analyses revealed that the discriminative ability of PAR was better than platelet count and albumin alone. LASSO Cox regression along with SVM identified six significant metrics associated with 28-day mortality in critically ill patients with CRC, including PAR. The C-index of the critically ill CRC nomogram was 0.802 (0.744–0.859) in the e-ICU training cohort, 0.839 (0.779–0.899) in the e-ICU validation cohort, 0.787 (0.695–0.879) in the MIMIC-IV cohort, and 0.767 (0.703–0.831) in the Union cohort. PAR is a simple score that combines inflammatory and nutritional status. PAR was a reliable index to predict short-term survival outcome of critically ill patients with CRC. Moreover, a clinical nomogram incorporating PAR exhibited satisfactory performance for predicting 28-day mortality of critically ill patients with CRC.