4.4 Article

Exposure to Coxiella burnetii and risk of non-Hodgkin lymphoma: a retrospective population-based analysis in the Netherlands

Journal

LANCET HAEMATOLOGY
Volume 5, Issue 5, Pages E211-E219

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/S2352-3026(18)30038-3

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Funding

  1. Foundation Q-support
  2. Institut Merieux

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Background An association between Coxiella burnetii and non-Hodgkin lymphoma has been suggested. After a large Q fever epidemic in the Netherlands (2007-10), we postulated that the incidence of non-Hodgkin lymphoma would be increased during and after the epidemic in areas with a high endemicity of Q fever compared with those with low endemicity. Methods We did a retrospective population-based analysis and calculated relative risks (RRs) of non-Hodgkin lymphoma during 1-year periods before, during, and after the Q fever epidemic, for areas with intermediate and high endemicity of Q fever compared with low endemic areas. We also calculated the RR of non-Hodgkin lymphoma in people with chronic Q fever compared with the general population. Findings Between Jan 1, 2002, and Dec 31, 2013, 48 760 cases of non-Hodgkin lymphoma were diagnosed. The incidence of non-Hodgkin lymphoma ranged from 21.4 per 100 000 per year in 2002 to 26.7 per 100 000 per year in 2010. A significant association with non-Hodgkin lymphoma was noted in 2009 for areas with a high endemicity of Q fever compared with low endemic areas (RR 1.16, 95% CI 1.02-1.33; p=0.029); no further associations were noted in any other year or for areas with intermediate Q fever endemicity. Among 439 individuals with chronic Q fever, five developed non-Hodgkin lymphoma, yielding a crude absolute risk of 301.0 cases per 100 000 per year (RR 4.99, 95% CI 2.07-11.98; p=0.0003) compared with the general population in the Netherlands. Interpretation These findings do not support the hypothesis that Q fever has a relevant causal role in the development of non-Hodgkin lymphoma. Several limitations, inherent to the design of this study, might lead to both underestimation and overestimation of the studied association.

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