Background and Purpose
Several studies have proposed that the advanced lung cancer inflammation index (ALI), a new inflammation-related index, can be used for the prognosis assessment of various malignancies. However, few studies have reported its prognostic value in colorectal cancer (CRC). Therefore, this study explored the relationship between ALI and outcomes in CRC patients.
Methods
A total of 662 CRC patients who underwent surgery between 2012 and 2014 were included. The ALI was defined as: body mass index × serum albumin/neutrophil to lymphocyte ratio. The X-tile program identified the optimal cut-off value of ALI. Logistic regression analyses determined factors affecting postoperative complications. The Kaplan–Meier method and Cox proportional hazards analyses evaluated potential prognostic factors.
Results
The optimal cut-off of ALI in males and females were 31.6 and 24.4, respectively. Low-ALI was an independent risk factor for postoperative complications in CRC patients (odds ratio: 1.933, 95% CI [1.283–2.911], p = 0.002). Low-ALI groups also had significantly lower progression-free survival (PFS) and overall survival (OS), when compared with the high-ALI group, especially at advance tumor stages. Using multivariate analysis, ALI was determined as an independent prognostic factor for PFS (hazard ratio: 1.372, 95% CI [1.060–1.777], p = 0.016) and OS (hazard ratio: 1.453, 95% confidence interval: 1.113–1.898, p = 0.006).
Conclusion
ALI is an independent predictor of short and long-term outcomes in CRC patients, especially at advance tumor stages. The ALI-based nomograms can provide accurate and individualized prediction of postoperative complication risk and survival for CRC patients.
Background:
This study aimed to explore the value of controlling nutritional status (CONUT) score in assessing short-term and long-term outcomes of colorectal cancer (CRC) patients, and construct CONUT-based nomograms to predict risk of postoperative comorbidities and survival.
Methods:
We retrospectively enrolled 512 patients from 2012 to 2014. Patients were categorized into low-CONUT and high-CONUT groups. Logistic regression analysis was used to determine characteristics influencing postoperative comorbidities. Kaplan-Meier survival curve and Cox proportional hazards analysis were used to determine characteristics affecting prognosis. The receiver operating characteristic was used to compare ability of the CONUT score with other immune-nutritional indicators to predict prognosis.
Results:
Logistic regression analysis suggested that high CONUT score was an independent risk factor affecting postoperative comorbidities (odds ratio, 1.792; 95% confidence interval [CI], 1.113-2.886; P = 0.016). Patients with low-CONUT score had longer disease-free survival (DFS) (P < 0.001) and overall survival (OS) (P < 0.001) compared to those with high-CONUT score, especially at the early stage. CONUT score was an independent factor affecting both DFS (hazard ratio [HR], 1.820; 95% CI, 1.204-2.752; P = 0.005) and OS (HR, 1.815; 95% CI, 1.180-2.792; P = 0.007). The area under the curve of CONUT score was higher than for other immune-nutritional indicators. The CONUT-based nomograms had good predictive capability.
Conclusions:
CONUT score is a strong independent predictor of postoperative comorbidities and long-term outcomes in CRC patients, and might be a better prognostic factor than other immune-nutritional indicators. The CONUT-based nomograms are conducive to the individualized formulation of follow-up strategies and treatment plans.
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