Detalle Publicación

Spatial analysis of childhood cancer: a case/control study

Autores: Ramis, R. (Autor de correspondencia); Gómez-Barroso, D.; Tamayo Uria, Ibon; García-Pérez, J.; Morales, A.; Romaguera, E. P.; López-Abente, G.
Título de la revista: PLOS ONE
ISSN: 1932-6203
Volumen: 10
Número: 5
Páginas: e0127273
Fecha de publicación: 2015
Resumen:
Background Childhood cancer was the leading cause of death among children aged 1-14 years for 2012 in Spain. Leukemia has the highest incidence, followed by tumors of the central nervous system (CNS) and lymphomas (Hodgkin lymphoma, HL, and Non-Hodgkin's lymphoma, NHL). Spatial distribution of childhood cancer cases has been under concern with the aim of identifying potential risk factors. Objective The two objectives are to study overall spatial clustering and cluster detection of cases of the three main childhood cancer causes, looking to increase etiological knowledge. Methods We ran a case-control study. The cases were children aged 0 to 14 diagnosed with leukemia, lymphomas (HL and NHL) or CNS neoplasm in five Spanish regions for the period 1996-2011. As a control group, we used a sample from the Birth Registry matching every case by year of birth, autonomous region of residence and sex with six controls. We geo-coded and validated the address of the cases and controls. For our two objectives we used two different methodologies. For the first, for overall spatial clustering detection, we used the differences of K functions from the spatial point patterns perspective proposed by Diggle and Chetwynd and the second, for cluster detection, we used the spatial scan statistic proposed by Kulldorff with a level for statistical significance of 0.05. Results We had 1062 cases of leukemia, 714 cases of CNS, 92 of HL and 246 of NHL. Accordingly we had 6 times the number of controls, 6372 controls for leukemia, 4284 controls for CNS, 552 controls for HL and 1476 controls for NHL. We found variations in the estimated empirical D(s) for the different regions and cancers, including some overall spatial clustering for specific regions and distances. We did not find statistically significant clusters. Conclusions The variations in the estimated empirical D(s) for the different regions and cancers could be partially explained by the differences in the spatial distribution of the population; however, according to the literature, we cannot discard environmental hazards or infections agents in the etiology of these cancers.