Hepatitis C virus infection is associated with high risk of breast cancer: a pooled analysis of 68,014 participants

Front Oncol. 2023 Oct 13:13:1274340. doi: 10.3389/fonc.2023.1274340. eCollection 2023.

Abstract

Introduction: Breast cancer is the most common malignancy among women. Previous studies had shown that hepatitis C virus (HCV) infection might serve as a risk factor for breast cancer, while some studies failed to find such an association.

Methods: In this study, we presented a first attempt to capture and clarify this clinical debate via a cumulative analysis (registration ID: CRD42023445888).

Results: After systematically searching and excluding the irrelevant publications, five case-control or cohort studies were finally included. The synthetic effect from the eligible studies showed that patients with HCV infection had a significantly higher prevalence of breast cancer than non-HCV infected general population (combined HR= 1.382, 95%CI: 1.129 to 1.692, P=0.002). There was no evidence of statistical heterogeneity during this pooled analysis (I2 = 13.2%, P=0.33). The sensitivity analyses confirmed the above findings. No significant publication bias was observed among the included studies. The underlying pathophysiological mechanisms for this relationship might be associated with persistent infection/inflammation, host immune response, and the modulation of HCV-associated gene expression.

Discussion: Though the causal association between HCV infection and breast cancer did not seem quite as strong, screening for HCV might enable the early detection of breast cancer and help to prevent the progression of the disease. Since the topic of this study remains a matter of clinical debate, further studies are still warranted to validate this potential association.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023445888.

Keywords: breast cancer; cumulative analysis; hepatitis C virus; prevalence; risk.

Publication types

  • Systematic Review

Grants and funding

The authors declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the grants from the Science and Technology Planning Project of Guangzhou (No. 201904010401) and the Science and Technology Project of Panyu District, Guangzhou (No. 2020-Z04-006).