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

Authors

  • Gregory S. Calip,

    Corresponding author
    1. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
    • Department of Epidemiology, University of Washington, Seattle, WA, USA
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  • Jean A. McDougall,

    1. Department of Epidemiology, University of Washington, Seattle, WA, USA
    2. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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  • Mark C. Wheldon,

    1. Department of Statistics, University of Washington, Seattle, WA, USA
    2. Center for Statistics and the Social Sciences, University of Washington, Seattle, WA, USA
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  • Christopher I. Li,

    1. Department of Epidemiology, University of Washington, Seattle, WA, USA
    2. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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  • Anneclaire J. De Roos

    1. Department of Epidemiology, University of Washington, Seattle, WA, USA
    2. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Correspondence: Gregory S. Calip, Cancer Prevention Studies, Fred Hutchinson Cancer Research, Center 1100 Fairview Ave N, M4-B402, Seattle, Washington 98109-1024, United States.

E-mail: gcalip@fhcrc.org

Summary

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 (= 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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