title: [Risk profiling in cancer surveillance in contaminated sites: an example from the ISS-AIRTUM collaborative study].
abstract: Epidemiological surveillance on high risk environmental areas or areas covered by cancer registration yields long inventories of relative risks. Summaries of the results' tables must be produced to identify priorities and tailor public health actions. The aim is, therefore, to draw conclusions from each area's disease profile, or from the area signature of each disease.With this inmind, we used data on cancer incidence from 17 Cancer Registries that participated in the ISS-AIRTUM (National Institute of Health-Italian Network of Cancer Registries) study, and we produced conditional and marginal rankings of areas/diseases using a multivariate hierarchical Bayesian model. In this context, it is important to obtain an uncertainty evaluation by calculating the credibility intervals of ranks. The areas marginal ranking shows a large overlapping of credibility intervals, such that it is not possible to speak of a limited number of ISS-AIRTUM areas as being particularly affected. Every ISS-AIRTUMarea, therefore,must be considered individually and ordering themby ranking of cancer incidence wouldn't be appropriate. Instead,marginal ranking of diseases highlights the impact of asbestos exposure in all the analyzed areas.
authors.affiliation: Dipartimento di statistica, informatica e applicazioni, Università di Firenze. catelan@disia.unifi.it.
authors.forename: Dolores
authors.initials: D
authors.lastname: Catelan
authors.forename: Carlotta
authors.initials: C
authors.lastname: Buzzoni
authors.forename: Enzo
authors.initials: E
authors.lastname: Coviello
authors.forename: Emanuele
authors.initials: E
authors.lastname: Crocetti
authors.forename: Roberto
authors.initials: R
authors.lastname: Pasetto
authors.forename: Roberta
authors.initials: R
authors.lastname: Pirastu
authors.forename: Annibale
authors.initials: A
authors.lastname: Biggeri
mesh_terms: D001194:Asbestos / Q000009:adverse effects; D001499:Bayes Theorem; D002273:Carcinogens; D004781:Environmental Exposure / Q000009:adverse effects*; D004785:Environmental Pollutants / Q000009:adverse effects*; D004787:Environmental Pollution / Q000009:adverse effects; D006801:Humans; D015994:Incidence; D007558:Italy / Q000453:epidemiology; D009369:Neoplasms / Q000453:epidemiology* / Q000209:etiology; D011159:Population Surveillance; D011634:Public Health; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors
chemical_list: D002273:Carcinogens; D004785:Environmental Pollutants; D001194:Asbestos