Acute Lymphoblastic Leukemia among Children in Rome: a Spatial Clustering and Clusters Analysis between 2000-2010

Abstract

Acute Lymphoblastic Leukemia among Children in Rome: a Spatial Clustering and Clusters Analysis between 2000-2010Abstract Number:2558 Patrizia Schifano*, Clarissa Ferrari, Federica Asta, and Paola Michelozzi Patrizia Schifano* Department of Epidemiology Regional Health Service, Italy, E-mail Address: [email protected] Search for more papers by this author , Clarissa Ferrari IRCCS Centro San Giovanni di Dio Fatebenefratelli, Italy, E-mail Address: [email protected] Search for more papers by this author , Federica Asta Department of Epidemiology Lazio Regional Health Service, Italy, E-mail Address: [email protected] Search for more papers by this author , and Paola Michelozzi Department of Epidemiology Lazio Regional Health Service, Italy, E-mail Address: [email protected] Search for more papers by this author AbstractIntroduction Acute Lymphoblastic Leukemia (ICD9-CM:204, ALL) tendency to clusters has been widely analyzed with no conclusive evidences.Objectives We conducted a childhood ALL’s cases clustering analysis in Rome 2000-2010, through a systematic approach based on different spatial resolutions.Materials andMethods Cases were selected through a record linkage among: the archive of the Italian Association of Pediatric Oncology, the Regional Hospital Information System and Anagraphic Municipality Registry to attribute residence at diagnosis. Cases were geocoded at 3 spatial resolutions: 20 districts (D), 155 neighborhoods (NB) and 5812 census tracts (CT). Indirect standardized incidence ratios (SIR) were computed for the NBs with Rome average incidence rate (IR) of ALL as reference and then smoothed by Besag-York-Mollie (BYM) model. General clustering was tested by Tango statistics whereas localized clustering was detected via two different statistics: Besag&Newell and Kulldorf&Nagarwalla. Both general and local clustering was tested at the city level, using NBs as area units, and at the district level using CTs as area units.Results We identified 194 ALL cases in the 0-14 age group (IR:43.7x1.000.000). SIRs ranged between 0.00 and 18.1 among NBs. After smoothing, a significant excess of cases was identified only in 3 D. At city level, no general clustering was highlighted (Tango’s test p-value=0.08) while both tests for local clustering were significant in one of the 3 D with the highest SIRs. Finally, at the district level, although no general cluster was founded, a total of 7 clusters were identified in the 3 D with highest SIRs, each clusters being composed by a number of cases ranging between 2 and 6.ConclusionResults indicate the presence of clusters in some area of Rome, evident only when the finest spatial resolution is used. This standardised procedure is a fondamental tool to properly analyse potential clusters reported by the public to our Department.