Prognostic significance of EBV latent membrane protein 1 expression in lymphomas: evidence from 15 studies

Abstract

Background: Epstein-Barr virus (EBV) infection has been associated with lymphoma development. EBV latent membrane protein 1 (LMP1) is essential for EBV-mediated transformation and progression of different human cells, including lymphocytes. This meta-analysis investigated LMP1 expression with prognosis of patients with lymphoma.

Methods: The electronic databases of PubMed, Embase, and Chinese Biomedicine Databases were searched. There were 15 published studies available for a random effects model analysis. Quality assessment was performed using the Newcastle-Ottawa Quality Assessment Scale for cohort studies. A funnel plot was used to investigate publication bias, and sources of heterogeneity were identified by meta-regression analysis. The combined hazard ratios (HR) and their corresponding 95% confidence intervals of LMP1 expression were calculated by comparison to the overall survival.

Results: Overall, there was no statistical significance found between LMP1 expression and survival of lymphoma patients (HR 1.25 [95% CI, 0.92-1.68]). In subgroup analyses, LMP1 expression was associated with survival in patients with non-Hodgkin lymphoma (NHL) (HR = 1.84, 95% CI: 1.02-3.34), but not with survival of patients with Hodgkin disease (HD) (HR = 1.03, 95% CI: 0.74-1.44). In addition, significant heterogeneity was present and the meta-regression revealed that the outcome of analysis was mainly influenced by the cutoff value.

Conclusions: This meta-analysis demonstrated that LMP1 expression appears to be an unfavorable prognostic factor for overall survival of NHL patients. The data suggested that EBV infection and LMP1 expression may be an important factor for NHL development or progression.

Figure 1. PRISMA flow diagram for selection of studies in the meta-analysis.

Figure 2. Forest plot of the hazard ratios (HR) and 95% confidence intervals (CI) of each study on association of LMP1 expression with lymphoma (random-effect model) and with histological types of lymphomas.

Figure 3. Funnel plots of Begg and Egger’s tests. Publication bias on overall estimation was evaluated.

Studies are symmetrical distributed approximately above and below the horizontal line, and suggest the absence of publication bias in this meta-analysis.