Cancer cluster and citizen alarms: epidemiological and statistical approaches. (30th September 2020)

• Record Type: Journal Article
• Authors: Miligi, L; Stoppa, G; Piro, S; Caldarella, A; Intrieri, T; Mannesci, G; Ferrari, C; Biggeri, A; Catelan, D
• Is Part Of: European journal of public health. Volume 30(2020)Supplement 5
• Publication Date: 2020-09-30
• Subjects: Epidemiology -- Europe -- Periodicals; Public health -- Europe -- Periodicals; 362.109405
• DOI: 10.1093/eurpub/ckaa166.1150
• Languages: English
• ISSNs: 1101-1262

Abstract

Abstract: Background: Respond to alarms for possible cancer cluster is a public health problem, but the management of these alarms is difficult and sometime conflictual. Methods: We reviewed the guidelines on the management of disease clusters developed in various countries and the approaches used in previous disease cluster episodes in Tuscany. Statistical approaches for cluster detection were also reviewed. We performed a clustering analysis (spatio or spatio-temporal when appropriate) on childhood leukemia using data from Tuscany Cancer Registry (RTT). We used spatial hierarchical Bayesian model on aggregate data at municipality level. We performed test for general clustering and cluster detection on individual data. Results: More than 100 tests for clustering analysis has been identified in the literature. Bayesian analysis on aggregate data did not show areas at higher risk with the exception of the city of Florence for childhood cancer among males. We did not found clusters for leukemia. In previous studies on disease clusters in Tuscany, most investigations have been started from community concerns and in the majority of situations a multidisciplinary approach was used. In some case an increase of incidence rate was observed, but rarely specific cluster cancer tests were used. Conclusions: Hierarchical Bayesian models to aggregate data provided useful to identify long range geographical patterns while clustering analysis on individual data is a useful tool for small scale patterns. Both represent important tools for epidemiological surveillance studies particularly on childhood cancer. The best test for all situations doesn't exist, but the choice is determined by the type of question being asked from the data, by different situations and by different approaches. The Tuscany cancer clusters survey and the review of the guidelines on the management of clusters developed in different countries, give us the opportunity to formulate some suggestions for the health agencies. Key messages: Respond to alarms for cluster of cancer and suggest recommendations for epidemiological and statistical standardized approaches is a public health issue. Tuscany cancer clusters survey and the review of the guidelines on the management of clusters developed in different countries, give the opportunity to formulate some suggestions for health agencies.