A novel prognostic model predicts overall survival in patients with nasopharyngeal carcinoma based on clinical features and blood biomarkers

Abstract

Background To develop and validate a novel prognostic model to estimate overall survival (OS) in nasopharyngeal carcinoma (NPC) patients based on clinical features and blood biomarkers. And assess its incremental value to TNM staging system, clinical treatment, and Epstein-Barr virus DNA (EBV DNA) for individual OS estimation. Methods We retrospectively analyzed 519 consecutive NPC. A prognostic model was generated by using the Lasso-Cox regression model in training cohort (n = 346). Then comparison of predictive accuracy between the novel prognostic model, TNM staging, clinical treatment, and EBV DNA using concordance index (C-index), time-dependent ROC (tdROC), and decision curve analysis (DCA). Subsequently, a nomogram for OS incorporating the prognostic model, TNM staging and clinical treatment was built. Finally, we stratified patients into high- risk and low-risk groups according to the model risk score, and the survival time of these two groups was analyzed using Kaplan–Meier survival plots. All the results were validated in the independent validation cohort (n = 173). Results Using the Lasso-Cox regression, a prognostic model was established consisting of 13 variables with respect to patient prognosis. The C-index, tdROC and DCA all showed the prognostic model had good predictive accuracy and discriminatory power than TNM staging, clinical treatment and EBV DNA in training cohort. Nomogram consisting of the prognostic model, TNM staging, clinical treatment and EBV DNA shown some superior net benefit. According to the model risk score, we split the patients into two subgroups: low- risk (risk score ≤ -1.423) and high-risk (risk score > -1.423). There had significant differences in OS between the two subgroups of patients. In the validation cohort, similar results were obtained. Conclusion The proposed novel prognostic model based on clinical features and serological markers represents a promising signature for estimating OS in NPC patients.

The value of the Advanced Lung Cancer Inflammation Index (ALI) in assessing the prognosis of patients with hepatocellular carcinoma treated with camrelizumab: a retrospective cohort study

“…P r e v i o u s s t u d i e s h a v e f o u n d t h a t c a n c e r a n d inflammation are closely related to various inflammationbased biomarkers; for example, the NLR, the platelet-tolymphocyte ratio, and the albumin-globulin ratio have been used for early prognostic assessments of several tumors, but their efficacy has been controversial in different studies (18,19). Notably, elevated C-reactive protein (CRP) has been shown to indicate an increased risk of lung and bowel cancer, and the NLR has been found to be a poor prognostic factor for several tumors (20,21). However, as cachexia due to chronic systemic inflammation may affect patient prognosis through the BMI and serum albumin levels (20,22), an ALI indicator that includes both these factors could theoretically better reflect a patient's nutritional status and systemic inflammation (23,24).…”