Association between systemic inflammation and water composition and survival in colorectal cancer

Association between ICW/TBW ratio and cancer prognosis: Subanalysis of a population-based retrospective multicenter study

BACKGROUND & AIMS

Disease burden is known to alter cellular integrity and water balance. Therefore, the intracellular water/total body water (ICW/TBW) ratio is used as an adjunctive indicator to predict disease severity and prognosis. The ICW/TBW ratio of patients with cancer, who typically present with low muscle mass, poor nutritional status, and high inflammatory response, reportedly differs from that of the healthy population. Herein, we aimed to evaluate the effect of the ICW/TBW ratio on the prognosis of different subgroups of patients with cancer.

METHODS

This multicenter cohort study included 2787 patients with malignancies between June 2014 and December 2018. The association between covariates and overall survival (OS) was assessed using restricted cubic spline models. The multivariate Cox regression model included variables demonstrating a statistical significance in the univariate Cox regression analysis (P < 0.05) without multicollinearity. The generated nomogram used the C-index and calibration curves to validate the predictive accuracy of the scoring system.

RESULTS

The optimal cut-off value for the ICW/TBW ratio was 0.61. The ICW/TBW ratio was an independent prognostic factor (hazard ratio [HR]: 0.621; 95 % confidence interval [CI]: 0.537-0.719, P < 0.001). Moreover, the ICW/TBW ratio had a greater impact on the prognosis of patients receiving chemoradiotherapy than on those receiving chemotherapy alone (chemoradiotherapy: HR = 0.495, P = 0.005 vs. chemotherapy: HR = 0.646, P < 0.001). Multivariate Cox regression analysis showed that sex, age, tumor stage, body mass index, neutrophil-to-lymphocyte ratio (NLR), and ICW/TBW ratio were associated with OS. Subsequently, a nomogram was developed incorporating these variables and yielded a C-index of 0.743.

CONCLUSIONS

The ICW/TBW ratio was associated with muscle mass, nutritional status, and inflammation. A low ICW/TBW ratio is an independent risk factor for poor prognosis in patients with cancer, especially when they are female, have advanced cancer stage, have sarcopenia, and are receiving radiotherapy.

Prognostic value of the combined effect of nutritional status and body water component in patients with colorectal cancer

The aim of this study was to explore the impact of Geriatric Nutritional Risk Index (GNRI) and body water component (BWC) on the survival of colorectal cancer (CRC) patients and whether the combined effect had a potential prognostic and predictive efficacy. We evaluated the accuracy of GNRI for malnutrition and estimated the predictive capacity of BWC for survival. Kaplan-Meier survival curves and cox regression analyses were used to examine the prognostic effects. A nutrition-water score (NWS) model was developed and evaluated the survival predictive power. GNRI and extracellular water-to-intracellular water ratio (ECW/ICW) were integrated, with the cut-off values of 103.5 and 63.7%. Lower GNRI and higher ECW/ICW were independent risk factors for poor prognosis in CRC patients. The combination of the two into the NWS model demonstrated a higher risk of death for patients with NWS ≥ 1 compared to those with NWS of 0. NWS showed a better predictive capability compared to GNRI and ECW/ICW, with the concordance index of 0.681. Our study demonstrates GNRI and ECW/ICW's prognostic utility in CRC, with their combination improving survival prediction to help guide patient-centered treatment.

Association between white blood cell count to hemoglobin ratio and risk of in-hospital mortality in patients with lung cancer

BACKGROUND

The objective of this study was to investigate the association between white blood cell count to hemoglobin ratio (WHR) and risk of in-hospital mortality in patients with lung cancer.

METHODS

In this retrospective cohort study, the medical records of patients with lung cancer were retrieved from the electronic ICU (eICU) Collaborative Research Database between 2014 and 2015. The primary outcome was in-hospital mortality. The secondary outcome was the length of stay in intensive care unit (ICU). The cut-off value for the WHR was calculated by the X-tile software. The Cox model was applied to assess the association between WHR and in-hospital mortality among patients with lung cancer and the linear regression model was used to investigate the association between WHR and length of ICU stay. Subgroup analyses of age (< 65 years or >  = 65 years), Acute Physiology and Chronic Health Evaluation (APACHE) score (< 59 or >  = 59), gender, ventilation (yes or no), and vasopressor (yes or no) in patients with lung cancer were conducted.

RESULTS

Of the 768 included patients with lung cancer, 153 patients (19.92%) died in the hospital. The median total follow-up time was 6.88 (4.17, 11.23) days. The optimal cut-off value for WHR was 1.4. ICU lung cancer patients with WHR >  = 1.4 had a significantly higher risk of in-hospital mortality [Hazard ratio: (HR): 1.65, 95% confidence interval (CI): 1.15 to 2.38, P = 0.007) and length of stay in ICU (HR: 0.63, 0.01, 95% CI: 1.24 to 0.045, P = 0.045). According to the subgroup analysis, WHR was found to be associated with in-hospital mortality in patients with higher APACHE score (HR: 1.60, 95% CI: 1.06 to 2.41, P = 0.024), in male patients (HR: 1.87, 95% CI: 1.15 to 3.04, P = 0.012), and in patients with the treatment of ventilation (HR: 2.33, 95% CI: 1.49 to 3.64, P < 0.001).

CONCLUSION

This study suggests the association between WHR and risk of in-hospital mortality in patients with lung cancer and length of stay, which indicates the importance of attention to WHR for patients with lung cancer.

Development and validation of a web-based predictive model for preoperative diagnosis of localized colorectal cancer and colorectal adenoma

Background

Localized colorectal cancer (LCC) has obscure clinical signs, which are difficult to distinguish from colorectal adenoma (CA). This study aimed to develop and validate a web-based predictive model for preoperative diagnosis of LCC and CA.

Methods

We conducted a retrospective study that included data from 500 patients with LCC and 980 patients with CA who were admitted to Dongyang People's Hospital between November 2012 and June 2022. Patients were randomly divided into the training (n=1036) and validation (n=444) cohorts. Univariate logistic regression, least absolute shrinkage and selection operator regression, and multivariate logistic regression were used to select the variables for predictive models. The area under the curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to evaluate the performance of the model.

Results

The web-based predictive model was developed, including nine independent risk factors: age, sex, drinking history, white blood cell count, lymphocyte count, red blood cell distribution width, albumin, carcinoembryonic antigen, and fecal occult blood test. The AUC of the prediction model in the training and validation cohorts was 0.910 (0.892-0.929) and 0.894 (0.862-0.925), respectively. The calibration curve showed good consistency between the outcome predicted by the model and the actual diagnosis. DCA and CIC showed that the predictive model had a good clinical application value.

Conclusion

This study first developed a web-based preoperative prediction model, which can discriminate LCC from CA and can be used to quantitatively assess the risks and benefits in clinical practice.