RESUMO
PURPOSE: Conventional staging and scoring systems such as the Tumor, Node, and Metastasis; Cancer of the Liver Italian Program; Barcelona Clinic Liver Cancer; and Okuda have failed to predict overall survival (OS) in patients with resected primary hepatocellular carcinoma. Thus, we aimed to establish a novel D-index and nomogram to improve prognostic accuracy. PATIENTS AND METHODS: We selected 396 patients who underwent liver resection between January 2007 and February 2015 at the First Affiliated Hospital of Wenzhou Medical University. These patients were randomly divided into the training and validation groups in a ratio of 7:3. RESULTS: We generated a nomogram using five independent risk factors, including the D-index (calculated by total bilirubin × tumor size/the ratio of fat-to-muscle area 0.5) in the training set. The predictive performance of the nomogram was similar in both the training and validation cohorts according to the concordance index. The nomogram demonstrated the strongest predictive power for 1-year, 3-year, and 5-year OS, with the area under the receiving operating characteristic curve being 0.8486, 0.7785, and 0.752, respectively. The calibration curves exhibited stable capabilities in both cohorts. The stratification of the Kaplan-Meier curve was significant (P < 0.001). CONCLUSION: The associated nomogram of the D-index demonstrated a powerful and accurate predictive ability for OS in patients with primary hepatocellular carcinoma.
RESUMO
Diabetic retinopathy (DR), the most common microvascular complication of diabetes and leading cause of visual impairment in adults worldwide, is suggested to be linked to abnormal lipid metabolism. The present study aims to comprehensively investigate the relationship between n-6 polyunsaturated fatty acids (PUFAs) and DR. This was a propensity score matching based case-control study, including 69 pairs of DR patients and type 2 diabetic patients without DR with mean age of 56.7 ± 9.2 years. Five n-6 PUFAs were determined by UPLC-ESI-MS/MS system. Principle component regression (PCR) and multiple conditional logistic regression models were used to investigate the association of DR risk with n-6 PUFAs depending on independent training and testing sets, respectively. According to locally weighted regression model, we observed obvious negative correlation between levels of five n-6 PUFAs (linoleic acid, γ-linolenic acid, eicosadienoic acid, dihomo-γ-linolenic acid and arachidonicacid) and DR. Based on multiple PCR model, we also observed significant negative association between the five n-6 PUFAs and DR with adjusted OR (95% CI) as 0.62 (0.43,0.87). When being evaluated depending on the testing set, the association was still existed, and PCR model had excellent classification performance, in which area under the curve (AUC) was 0.88 (95% CI: 0.78, 0.99). In addition, the model also had valid calibration with a non-significant Hosmer-Lemeshow Chi-square of 9.44 (P = 0.307) in the testing set. n-6 PUFAs were inversely associated with the presence of DR, and the principle component could be potential indicator in distinguishing DR from other T2D patients.
