Viruses (Dec 2022)

The Dynamic Change in Plasma Epstein–Barr Virus DNA Load over a Long-Term Follow-Up Period Predicts Prognosis in Nasopharyngeal Carcinoma

  • Amina Gihbid,
  • Raja Benzeid,
  • Abdellah Faouzi,
  • Imane El Alami,
  • Nezha Tawfiq,
  • Nadia Benchakroun,
  • Karima Bendahhou,
  • Abdellatif Benider,
  • Amal Guensi,
  • Wafa Khaali,
  • Imane Chaoui,
  • Mohammed El Mzibri,
  • Rachida Cadi,
  • Meriem Khyatti

DOI
https://doi.org/10.3390/v15010066
Journal volume & issue
Vol. 15, no. 1
p. 66

Abstract

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The current study was designed to investigate the changes in the circulating Epstein–Barr virus DNA load (EBV DNA) at various time points before and after treatment and its clinical significance in nasopharyngeal carcinoma (NPC). A total of 142 patients with NPC were prospectively enrolled in this study. The plasma EBV DNA concentration was measured before and after treatment using qPCR. The prognostic values of the EBV DNA load were analyzed using the Kaplan–Meier and Cox regression tests. Following multivariate analysis, our data showed that high pre-EBV DNA loads were associated with significantly poorer distant metastasis free survival (DMFS) and progression free survival (PFS); detectable end-EBV DNA loads were associated with significantly worse loco-regional recurrence free survival (LRRFS) and PFS, and the detecTable 6 months-post-EBV DNA loads were associated with significantly poorer overall survival (OS), DMFS and PFS (p < 0.05). Additionally, combining the pre-EBV DNA load and the stage of the disease, our results showed that patients at stage III-IVA with a low pre-EBV DNA load had similar survival rates as patients at stage II with a low or high pre-EBV DNA load, but had better survival rates than those at stage III-IVA with a high pre-EBV DNA load. Taken together, we showed that the change of the EBV DNA load measured at several time points was more valuable than at any single time point for predicting patients’ survival for NPC. Furthermore, combining the pre-EBV DNA load and the TNM classification could help to formulate an improved prognostic model for this cancer.

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