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Evaluation of seasonality in the diagnosis of acute myeloid leukaemia among adults in the United States, 1992-2008
Journal article   Open access   Peer reviewed

Evaluation of seasonality in the diagnosis of acute myeloid leukaemia among adults in the United States, 1992-2008

Gregory S. Calip, Jean A. McDougall, Mark C. Wheldon, Christopher I. Li and Anneclaire J. Roos
British journal of haematology, v 160(3), pp 343-350
01 Feb 2013
PMID: 23189956
url
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/bjh.12137View
Published, Version of Record (VoR) Open
url
https://doi.org/10.1111/bjh.12137View
Published, Version of Record (VoR) Open

Abstract

Hematology Life Sciences & Biomedicine Science & Technology
Recent studies have suggested seasonal variation in the diagnosis of acute myeloid leukaemia (AML), and the aetiological role seasonal factors may play in this group of haematological neoplasms remains unclear. We evaluated potential seasonality of AML diagnosis among adults. Cases included were ascertained from the Surveillance, Epidemiology, and End Results (SEER) 13 registries from 1992-2008. Chi-square analysis for heterogeneity and multiple Poisson regression using parametric harmonic modelling and bootstrap testing were used to detect possible monthly variation. Months of peak diagnoses were December and January, although some variation was present by sex and age. Heterogeneity across months was statistically significant (P < 0.001). In stratified analyses, monthly variation was detected only among males (P = 0.009) and in cases aged 65 years and older (P = 0.031). Poisson regression found no seasonal effect among all cases when fit to the sinusoidal model (P = 0.110). However, similar variation among males (P = 0.009) and cases aged 65 years and older (P = 0.018) was present. There is growing evidence of seasonality in AML diagnosis, particularly among older persons and men. Investigation of specific seasonal risk factors would be informative in explaining the aetiology behind the observed variation.

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Collaboration types
Domestic collaboration
Web of Science research areas
Hematology
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