Periconceptional maternal vitamin supplementation and childhood leukaemia: an uncertainty analysis.

BACKGROUND: Recent studies in childhood cancer suggest that maternal vitamin supplementation may reduce the risk of leukaemia, neuroblastoma and certain types of childhood brain tumours. For example, a previous study found a significantly reduced risk of acute lymphoblastic leukaemia (ALL) but not a...

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Bibliographic Details
Published in:Journal of Epidemiology & Community Health Vol. 63; no. 2; pp. 168 - 173
Main Authors: Jurek AM, Maldonado G, Spector LG, Ross JA
Format: equations & formulas research tables/charts Journal Article
Published: BMJ Publishing Group Feb2009
Online Access:View this record in EBSCOhost
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Summary:BACKGROUND: Recent studies in childhood cancer suggest that maternal vitamin supplementation may reduce the risk of leukaemia, neuroblastoma and certain types of childhood brain tumours. For example, a previous study found a significantly reduced risk of acute lymphoblastic leukaemia (ALL) but not acute myeloid leukaemia (AML) in children with Down syndrome whose mothers reported any vitamin supplement use prior to knowledge of pregnancy (ALL OR adjusted for confounders 0.51, 95% confidence limits (CL): 0.30, 0.89; AML OR adjusted for confounders 0.92, 95% CL 0.48, 1.76). Recall of exposures, including maternal vitamin supplement use, however, may be difficult and subject to error. Epidemiologists are encouraged to quantitatively adjust for systematic error in study results, but often do not. METHODS: The impact that misclassification of maternal vitamin supplement use may have had on the observed ORs in this study was quantified. Uncertainty analysis was used to calculate ORs adjusted for inaccurate reporting of vitamin supplement use under assumed probability distributions for exposure misclassification parameters. RESULTS: Given our assumptions, adjustment for exposure misclassification yielded ORs that were predominantly more protective for ALL than the crude OR. CONCLUSIONS: Uncertainty analysis can give important insights into the magnitude and direction of error in study results due to exposure misclassification.