Background: Although epidemiologic studies suggest that early immune stimulation is protective against childhood leukemia, evidence for this relationship is equivocal for Hispanic children, who are disproportionately affected by this disease. The complex biological processes underlying immune stimulation and leukemogenesis may benefit from novel statistical approaches that account for mixed exposures and their nonlinear interactions. In this study, we utilized targeted machine learning and traditional statistical methods to investigate the association of multiple measures of early immune stimulation with acute lymphoblastic leukemia (ALL) in Costa Rican children.
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