Liver Cancer Risk and Incidence Attributable to Human Immunodeficiency Virus: A Meta-Analysis and Population-Attributable Modeling Study of Over 1.2 Million Individuals.

Int J CancerJun 11, 2026 (epub)

Jianhui Zhao, Kangning Li, Yixuan Zhang et al.

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In 30 seconds

This systematic review and meta-analysis, combined with population-attributable modeling, assessed the association between HIV and liver cancer using studies published from 1984 to 2023 and data covering over 1.2 million individuals, as stated in the title. People living with HIV had a pooled relative risk of liver cancer of 3.36 (95% CI: 2.72-4.15). The modeled global population-attributable fraction was 1.43% in 2019, three times higher than 30 years earlier. Incidence patterns varied by region, with rapid increases reported in Eastern Europe and Central Asia.

Key findings

  • People living with HIV had a pooled liver cancer relative risk of 3.36 (95% CI: 2.72-4.15).
  • The global population-attributable fraction for HIV-attributed liver cancer was 1.43% in 2019, a three-fold increase over the past 30 years.
  • The highest estimated annual percentage change in age-standardized incidence reached 22.98% in Eastern Europe and Central Asia.

Why it matters

The findings indicate a substantial association between HIV and liver cancer, while modeled burden and incidence trends differ across regions. This supports attention to liver cancer prevention and to coexisting contributors identified by the authors, including viral hepatitis and liver disease, in settings with a high burden of HIV-attributed liver cancer.

What to keep in mind

The pooled estimate combines studies published across a long period; the abstract does not describe study-level heterogeneity or the methods and assumptions underlying the population-attributable modeling.

Source

Published in Int J Cancer. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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