This study aimed to establish an effective predictive nomogram for non-small cell lung cancer (NSCLC) patients with chronic hepatitis B viral (HBV) infection. The nomogram was based on a retrospective study of 230 NSCLC patients with chronic HBV infection. The predictive accuracy and discriminative ability of the nomogram were determined by a concordance index (C-index), calibration plot and decision curve analysis and were compared with the current tumor, node, and metastasis (TNM) staging system. Independent factors derived from Kaplan–Meier analysis of the primary cohort to predict overall survival (OS) were all assembled into a Cox proportional hazards regression model to build the nomogram model. The final model included age, tumor size, TNM stage, treatment, apolipoprotein A-I, apolipoprotein B, glutamyl transpeptidase and lactate dehydrogenase. The calibration curve for the probability of OS showed that the nomogram-based predictions were in good agreement with the actual observations. The C-index of the model for predicting OS had a superior discrimination power compared with the TNM staging system [0.780 (95% CI 0.733–0.827) vs. 0.693 (95% CI 0.640–0.746), P < 0.01], and the decision curve analyses showed that the nomogram model had a higher overall net benefit than did the TNM stage. Based on the total prognostic scores (TPS) of the nomogram, we further subdivided the study cohort into three groups: low risk (TPS ≤ 13.5), intermediate risk (13.5 < TPS ≤ 20.0) and high risk (TPS > 20.0). The proposed nomogram model resulted in more accurate prognostic prediction for NSCLC patients with chronic HBV infection.

Recent studies have indicated that inflammation-based prognostic scores, such as the Glasgow Prognostic Score (GPS), modified GPS (mGPS) and C-reactive protein/Albumin (CRP/Alb) ratio, platelet–lymphocyte ratio (PLR), and neutrophil–lymphocyte ratio (NLR), have been reported to have prognostic value in patients with many types of cancer, including nasopharyngeal carcinoma (NPC). In this study, we proposed a novel inflammation-based stage, named I stage, for patients with NPC. A retrospective study of 409 newly-diagnosed cases of NPC was conducted. The prognostic factors (GPS, mGPS, CRP/Alb ratios, PLR, and NLR) were evaluated using univariate and multivariate analyses. Then, according to the results of the multivariate analyses, we proposed a I stage combination of independent risk factors (CRP/Alb ratio and PLR). The I stage was calculated as follows: patients with high levels of CRP/Alb ratio (>0.03) and PLR (>146.2) were defined as I2; patients with one or no abnormal values were defined as I1 or I0, respectively. The relationships between the I stage and clinicopathological variables and overall survival (OS) were evaluated. In addition, the discriminatory ability of the I stage with other inflammation-based prognostic scores was assessed using the AUCs (areas under the curves) analyzed by receiver operating characteristics (ROC) curves. The p value of <0.05 was considered to be significant. A total of 409 patients with NPC were enrolled in this study. Multivariate analyses revealed that only the CRP/Alb ratio (Hazard ratio (HR) = 2.093; 95% Confidence interval (CI): 1.222–3.587; p = 0.007) and PLR (HR: 2.003; 95% CI: 1.177–3.410; p = 0.010) were independent prognostic factors in patients with NPC. The five-year overall survival rates for patients with I0, I1, and I2 were 92.1% ± 2.9%, 83.3% ± 2.6%, and 63.1% ± 4.6%, respectively (p < 0.001). The I stage had a higher area under the curve value (0.670) compared with other systemic inflammation-based prognostic scores (p < 0.001). The I stage is a novel and useful predictive factor for OS in patients with NPC.

Objective: To assess the clinical utility of the ratio of CD4+CD25+CD127^low regulatory T cells (Tregs) in subjects at high risk of HCC, investigate the relationship between the percentage of Tregs and the expression of transforming growth factor (TGF)-β1 and interleukin (IL)-10 in patients with hepatocellular carcinoma before and after treatment.