133
Views
8
CrossRef citations to date
0
Altmetric
Research Article

Epstein–Barr virus DNA quantification and follow-up in Tunisian nasopharyngeal carcinoma patients

, , , , &
Pages 274-280 | Received 27 Aug 2010, Accepted 27 Dec 2010, Published online: 20 Apr 2011
 

Abstract

The prognostic value of the Epstein–Barr virus (EBV) DNA load in sera of nasopharyngeal carcinoma (NPC) patients measured before any treatment, after treatment and before relapse was assessed. The real-time polymerase chain reaction was used to detect the viral load levels among 74 NPC subjects. Patients were followed up for a period going from 1 to 6 years (median 4 years). Before treatment, the EBV DNA load was correlated with lymph node involvement and advanced stages. After treatment, the viral load level declined significantly and patients presenting a viral load level lower than 1000 copies/ml showed a better overall survival (OS). Moreover, a significant result was found when the 6-year OS rates of patients having fewer or more than 15,000 copies/ml of viral load before relapse were compared. These results suggest that the EBV DNA load quantification after treatment may be a useful predictor of disease progression and survival.

Acknowledgements

We thank Mr. Adel Rdissi for English revision.

Declaration of interest

This work was supported by le Ministère de l’Enseignement Supérieur, de la recherche scientifique et de la technologie and by le Ministère de la Santé Publique de la République Tunisienne.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 527.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.