Environmental Health (Mar 2022)

Temporal clustering of neuroblastic tumours in children and young adults from Ontario, Canada

  • Louise Hayes,
  • Nermine Basta,
  • Colin R. Muirhead,
  • Jason D. Pole,
  • Paul Gibson,
  • Bruna Di Monte,
  • Meredith S. Irwin,
  • Mark Greenberg,
  • Deborah A. Tweddle,
  • Richard J. Q. McNally

DOI
https://doi.org/10.1186/s12940-022-00846-y
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 8

Abstract

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Abstract Background The aetiology of neuroblastic tumours is likely to involve both genetic and environmental factors. A number of possible environmental risk factors have been suggested, including infection. If an irregular temporal pattern in incidence is found, this might suggest that a transient agent, such as an infection, is implicated. Previous work has found evidence for temporal clustering in children and young adults living in northern England. Methods We examined data from a second population-based registry from Ontario, Canada to determine whether there was evidence of temporal clustering of neuroblastic tumours. Cases diagnosed in children and young adults aged 0-19 years between 1985 and 2016 were extracted from the population-based Pediatric Oncology Group of Ontario Networked Information System (POGONIS). A modified version of the Potthoff-Whittinghill method was used to test for temporal clustering. Estimates of extra-Poisson variation (EPV) and standard errors (SE) were obtained. Results Eight hundred seventy-six cases of neuroblastic tumours were diagnosed during the study period. Overall, no evidence of temporal clustering was found between fortnights, between months or between quarters within years. However, significant EPV was found between years within the full study period (EPV = 1.05, SE = 0.25; P = 0.005). Conclusions The findings are consistent with the possibility that a transient agent, such as an infection that is characterised by ‘peaks and troughs’ in its occurrence, might be implicated in the aetiology of neuroblastic tumours. However, this pattern may also reflect a long-term increase in the numbers of cases, rather than peaks and troughs.

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