Article Text

Download PDFPDF

Funnel plots and choropleth maps in cancer risk communication: a comparison of tools for disseminating population-based incidence data to stakeholders
  1. Walter Mazzucco1,2,
  2. Rosanna Cusimano1,3,
  3. Maurizio Zarcone1,4,
  4. Sergio Mazzola1,4,
  5. Francesco Vitale1,2,4
  1. 1Registro Tumori di Palermo e Provincia, University of Palermo, Palermo, Italy
  2. 2Dipartimento Scienze Promozione della Salute e Materno Infantile “G. D'Alessandro”, Sezione di Igiene, University of Palermo, Palermo, Italy
  3. 3Azienda Sanitaria Provinciale 6 di Palermo—Dipartimento di Prevenzione, Palermo, Italy
  4. 4Unità Operativa Complessa di Epidemiologia Clinica con Registro Tumori, Azienda Ospedaliera Universitaria Policlinico “Paolo Giaccone”, Palermo, Italy
  1. Correspondence to Dr Walter Mazzucco; walter.mazzucco{at}unipa.it

Abstract

Background Population-based cancer registries provide epidemiological cancer information, but the indicators are often too complex to be interpreted by local authorities and communities, due to numeracy and literacy limitations. The aim of this paper is to compare the commonly used visual formats to funnel plots to enable local public health authorities and communities to access valid and understandable cancer incidence data obtained at the municipal level.

Methods A funnel plot representation of standardised incidence ratio (SIR) was generated for the 82 municipalities of the Palermo Province with the 2003–2011 data from the Palermo Province Cancer Registry (Sicily, Italy). The properties of the funnel plot and choropleth map methodologies were compared within the context of disseminating epidemiological data to stakeholders.

Results The SIRs of all the municipalities remained within the control limits, except for Palermo city area (SIR=1.12), which was sited outside the upper control limit line of 99.8%. The Palermo Province SIRs funnel plot representation was congruent with the choropleth map generated from the same data, but the former resulted more informative as shown by the comparisons of the weaknesses and strengths of the 2 visual formats.

Conclusions Funnel plot should be used as a complementary valuable tool to communicate epidemiological data of cancer registries to communities and local authorities, visually conveying an efficient and simple way to interpret cancer incidence data.

  • Funnel plot
  • cancer epidemiology
  • cancer registry;
  • Standardized Incidence Ratio
  • cancer data dissemination

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Footnotes

  • Contributors All individuals listed as authors have contributed substantially to designing, performing or reporting of the study and every specific contribution is indicated as follows. WM, RC, MZ and SM were involved in conception and design of the study. MZ and SM were involved in statistical analysis. WM, RC, MZ and SM were involved in interpretation of data. WM and RC were involved in manuscript writing and drafting. FV, WM and RC were involved in revision of the manuscript. WM, RC, MZ, SM and FV were involved in approval of the final version of the manuscript. The document has been reviewed and corrected by a native English speaker with extensive scientific editorial experience to ensure a high level of spelling, grammar and punctuation.

  • Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Online supplementary data (results of overdispersion tests, R-script to detect the greatest cut-off for the winsorisation procedure) have been provided as an online supplementary file. Other statistical results are available by emailing walter.mazzucco@unipa.it.