Establishment and Validation of a Nomogram for Nasopharyngeal Carcinoma Patients Concerning the Prognostic Effect of Parotid Lymph Node Metastases

Nomogram Based on Liver Function Test Indicators for Survival Prediction in Nasopharyngeal Carcinoma Patients Receiving PD-1 Inhibitor Therapy

PURPOSE

The aim of this study was to investigate the prognostic significance of PD-1 inhibitor therapy in nasopharyngeal carcinoma (NPC) and to develop a nomogram to estimate individual risks.

METHODS

We retrospectively analyzed 162 NPC patients who were administered the PD-1 inhibitor combined with radiotherapy and chemotherapy at the Sun Yat-Sen University Cancer Center. In total, 108 NPC patients were included in the training cohort and 54 NPC patients were included in the validation cohort. Univariate and multivariate Cox survival analyses were performed to determine the prognostic factors for 1-year and 2-year progression-free survival (PFS). In addition, a nomogram model was constructed to predict the survival probability of PFS. A consistency index (C-index), a decision curve, a clinical impact curve, and a standard curve were used to measure predictive accuracy, the clinical net benefit, and the consistency of prognostic factors.

RESULTS

Univariate and multivariate analyses indicated that the metastasis stage, the levels of ALT, the AST/ALT ratio, and the LDH were independent risk factors associated with the prognosis of PD-1 inhibitor therapy. A nomogram based on these four indicators was constructed and the Kaplan-Meier survival analysis showed that patients with a higher total score have a shorter PFS. The C-index of this model was 0.732 in the training cohort and 0.847 in the validation cohort, which are higher than those for the TNM stages (training cohort: 0.617; validation cohort: 0.727; p <0.05). Decision Curve Analysis (DCA), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) showed that our model has better prediction accuracy than TNM staging.

CONCLUSIONS

Predicting PFS in NPC patients based on liver function-related indicators before PD-1 treatment may help clinicians predict the efficacy of PD-1 treatment in these patients.

A Randomized Controlled Trial on Evaluation of Plasma Epstein-Barr Virus Biomarker for Early Diagnosis in Patients With Nasopharyngeal Carcinoma

INTRODUCTION

Early diagnosis of nasopharyngeal carcinoma (NPC) remains a major problem in Southern China. Epstein-Barr virus (EBV) biomarkers have been widely used in NPC screening. This study aims to evaluate the early diagnostic performances of individual EBV biomarkers in NPC.

METHODS

The levels of EBV biomarkers-IgA antibodies against EBV nuclear antigen 1 (EBNA1-IgA), EBV capsid antigen (VCA-IgA), EBV early antigen (EA-IgA), EBV BZLF1 transcription activator protein (Zta-IgA) and IgG antibodies against EBV BRLF1 transcription activator protein (Rta-IgG)-from 106 NPC patients (stage I and II) and 150 normal subjects were measured. VCA-IgA and EA-IgA were detected by immunofluorescence assay (IFA), EBNA1-IgA, Rta-IgG and Zta-IgA were measure by enzyme-linked immunosorbent assay (ELISA), and EBV DNA was detected by qPCR. Statistical analyses of a single index were conducted to evaluate the significance of NPC early diagnosis and TNM classification.

RESULTS

The level of EBNA1-IgA, EBV DNA, VCA-IgA, EA-IgA, Rta-IgG and Zta-IgA in early-stage NPC was significantly higher than in healthy controls (all P < 0.001). EBNA1-IgA yielded the biggest area under the curve (AUC) of 0.962 in distinguishing early-stage NPC patients from the normal subjects, with a sensitivity of 91.5% and a specificity of 98.7%. However, EBV biomarker levels were not associated with tumor size (all P > 0.050), whereas four biomarker levels (EBNA1-IgA, EBV DNA, VCA-IgA, EA-IgA) were related to lymph node metastasis (N0 and N1-2), among which EBNA1-IgA and EBV DNA showed good performance. Finally, high correlation was found between VCA-IgA and EA-IgA (r > 0.800).

CONCLUSION

A single EBNA1-IgA exhibits excellent discrimination performance in early diagnosis of NPC and could become a promising marker for NPC screening.

Prognosis prediction signature of seven immune genes based on HPV status in cervical cancer

Cervical cancer (CC) has a high incidence and mortality rate, with a low 5-year survival rate, and human papillomavirus (HPV) is one of its carcinogenic risks. However, little evidence exists on the impact of HPV infection on the survival of patients with CC. In the present study, the CC cohort and immune genes were downloaded from the TCGA database and the ImmPort database, respectively. Subsequently, the Gene Set Enrichment Analysis was performed and found that HPV status was involved in multiple immune signaling pathways, which revealed that HPV infection might play critical roles in the immune response. Then seven prognostic immune genes were identified according to HPV status in CC. Using the seven immune genes, we established an immune risk score (IRS) signature and the Kaplan-Meier curve showed that high IRS was significantly correlated with poor prognosis of CC in both the training sets (HR = 2.32, 95% CI = 1.66-3.33; AUC = 0.712) and the validation sets (HR = 1.38, 95% CI = 1.02-1.85 and AUC = 0.583 in TCGA-HNSCC; HR = 2.58, 95% CI = 1.364-4.893, AUC = 0.676 in GSE44001). A nomogram of IRS combined with clinical features was established, and further analyses demonstrated that the power of the nomogram to predict the prognosis of CC was more reliable than that of a single independent factor. In conclusion, this study provided a more comprehensive understanding of the correlation between HPV and immune mechanisms as well as a novel signature that can effectively predict the prognosis of CC patients.