Childhood leukemia incidence in Brazil according to different geographical regions

Pediatr Blood Cancer. 2011 Jan;56(1):58-64. doi: 10.1002/pbc.22736.

Abstract

Background: Resource-rich countries tend to have a higher incidence of childhood acute lymphoblastic leukemia (ALL), whereas lower rates are seen in more deprived countries. This study describes the incidence of childhood acute leukemia in Brazil, an upper middle-income country, based on data from 16 population-based cancer registries (PBCRs).

Procedure: Data were examined from 16 PBCRs in Brazilian cities located in five geographical regions during the period from 1997 to 2004. Incidence rates were analyzed according to gender, age, and type of leukemia. The Wilcoxon test was performed to evaluate for gender-age based difference between by leukemia type.

Results: The median age-adjusted incidence rate (AAIR) of leukemia in children aged 0-14 years old was 53.3 per million. A different AAIR was found regarding ALL and myeloproliferative disorders (MPD) that ranged from 24.8 to 76.84 per 1,000,000 children. Manaus, although located in a poor area of Brazil, exhibited the highest AAIR (56.6 per million) of ALL. Goiania had the highest AAIR (24.5 per million) of MPD. The median age-specific incidence rate (ASIR) for the 16 Brazilian PBCRs demonstrated a marked peak in incidence of ALL at age 3 years old, in both genders.

Conclusions: This population-based study of childhood leukemia demonstrates that substantial regional differences exist regarding the incidence of acute leukemia in Brazil, which warrants further ecological study.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Age Factors
  • Brazil / epidemiology
  • Child
  • Child, Preschool
  • Data Collection
  • Female
  • Humans
  • Incidence
  • Infant
  • Infant, Newborn
  • Male
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma / epidemiology*
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma / etiology
  • Registries
  • Sex Factors
  • Socioeconomic Factors
  • Topography, Medical / statistics & numerical data*