Prognostic significance of quantitative EBV biomarkers in extranodal NK/T-cell lymphoma: a meta-analysis of EBV DNA load and EBER-positive cell proportion.

OBJECTIVES: Pre-treatment peripheral blood EBV DNA and tumor EBV-encoded small RNA (EBER) are recognized prognostic factors in Extranodal NK/T-Cell Lymphoma (ENKTL). However, their quantitative values and optimal positive thresholds remain inconsistent, hindering clinical application. This meta-analysis systematically assesses their prognostic value in ENKTL. METHODS: Relevant studies from PubMed, Embase, Web of Science, and Cochrane Library were searched until 24 December, 2025. Eligible studies reported hazard ratios (HRs) for overall survival (OS) based on Pre-treatment EBV DNA levels or tumor EBER positivity. Subsequently, Pooled HRs with 95% confidence intervals (CIs) were calculated via random-effects models. Next, Subgroup analyses examined different blood compartments, EBV DNA cut-offs, and study design. Additionally, Heterogeneity (I²) and publication bias (Egger’s test) were assessed. RESULTS: In total, 17 studies from 15 articles were enrolled in this meta-analysis, including 15 on EBV DNA and 2 on EBER. These studies demonstrated that elevated pre-treatment EBV DNA level (HR = 3.04, 95% CI 1.97–4.69; P < 0.001, I2 = 38%) and high tumor EBER positivity thresholds of ≥ 75% (HR = 5.53, 95%CI2.21-14.38; P < 0.001, I2 = 0%) independently predicted reduced survival. Moreover, Stratification by EBV DNA cut-off (500 copies/ML) showed significantly higher mortality risk in the ≥ 500 group (HR = 2.82, 95% CI 1.84–4.31; P < 0.001) compared to the < 500 group (HR = 2.66, 95% CI 0.56–12.72; P = 0.22). Furthermore, Egger’s test suggested no publication bias(P = 0.111). Finally, Sensitivity analyses suggested the robustness and credibility of our results. CONCLUSIONS: High pre-treatment EBV DNA load (cut-off of ≥ 500 copies/mL) and high EBER-Positive Cell Proportion (≥ 75%) predict poor survival in ENKTL. Those quantitative EBV Biomarkers may serve as practical biomarkers for risk stratification and guiding therapeutic decisions in this patient population.