Risk factors for Burkitt lymphoma in East African children and minors: A case-control study in malaria-endemic regions in Uganda, Tanzania and Kenya

Abstract

Endemic Burkitt lymphoma (eBL) is the most common childhood cancer in sub-Saharan African countries, however, few epidemiologic studies have been undertaken and none attempted enrolling cases from multiple countries. We therefore conducted a population-based case-control study of eBL in children aged 0-15 years old in six regions in Northern Uganda, Northern Tanzania and Western Kenya, enrolling 862 suspected cases and 2,934 population controls (response rates 98.5-100%), and processing ~40,000 vials of samples using standardized protocols. Risk factor questionnaires were administered, and malaria period prevalence was measured using rapid diagnostic tests (RDTs). A total of 80.9% of the recruited cases were diagnosed as eBL; 61.4% confirmed by histology. Associations with eBL risk were computed using logistic regression models adjusted for relevant confounders. Associations common in at least two countries were emphasized. eBL risk was decreased with higher maternal income and paternal education and elevated with history of inpatient malaria treatment >12 months before enrollment. Reporting malaria-attributed fever up to 6 months before enrollment and malaria-RDT positivity at enrollment were associated with decreased eBL risk. Conversely, reporting exposure to mass malaria suppression programs (e.g., indoor residual insecticide) was associated with elevated risk. HIV seropositivity was associated with elevated eBL risk, but the relative impact was small. The study shows that it is feasible to conduct networked, multisite population-based studies of eBL in Africa. eBL was inversely associated with socioeconomic status, positively associated with inpatient malaria treatment 12 months ago and with living in areas targeted for malaria suppression, which support a role of malaria in eBL.

Keywords: Burkitt lymphoma; Epstein-Barr virus; HIV/AIDS; Plasmodium falciparum malaria; epidemiology; non-Hodgkin lymphoma.

Figure 1.

Map showing the EMBLEM study area marked with green shading and the participating hospitals marked with a red cross (St. Mary’s Hospital, Lacor and Kuluva Hospital in Northern Uganda; Bugando Medical Center and Shirati District Hospital in Northern Tanzania; Homa Bay District and Webuye District Hospitals and Moi University Teaching and Referral Hospital in Western Kenya). Two regions were selected per country. A locator map shows East Africa within Africa. Multi-panel maps show the zoom out of the study areas for each country. The bottom row shows the relief features, including rivers and the location of 100 villages randomly sampled per country as a source of matched population controls. The sampled villages are indicated according to their stratification category, that is, proximity to water and population density (see “Methods” section). The upper row shows the geographical distribution of the cases that were enrolled in the EMBLEM study plotted within their district of origin (large urban centers are marked on the map). The primary all season roads serving the study areas are included to give a rough idea of the geographical dispersion of cases in relation to the villages where the matched population controls were sampled and the transport infrastructure in the study areas.

Figure 2.

Figure shows malaria-RDT positivity among cases and controls by indoor residual spraying (IRS) use (IRS+) or not (IRS−) in the past year (Panel A) and by mosquito bed net ownership (Panel B) and mosquito bed net ownership by IRS use in the past year (Panel C). The results are ordered as controls first followed by cases for Uganda, Tanzania and Kenya.

Figure 3.

Venn diagram showing the characteristics associated with elevated or decreased risk of eBL in Uganda, Tanzania, and Kenya, highlighting findings common in the three or two countries.