Laura Botta1, Riccardo Capocaccia2, Annalisa Trama2, Christian Herrmann3, Diego Salmerón4, Roberta De Angelis5, Sandra Mallone5, Ettore Bidoli6, Rafael Marcos-Gragera7, Dorota Dudek-Godeau8, Gemma Gatta2, Ramon Cleries9. 1. Evaluative Epidemiology Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy. Electronic address: Laura.botta@istitutotumori.mi.it. 2. Evaluative Epidemiology Unit, Fondazione IRCCS Istituto Nazionale Tumori, Milan, Italy. 3. Cancer Registry St Gallen-Appenzell, Cancer League Eastern Switzerland, St. Gallen, Switzerland; Department of Public Health, University of Basel, Switzerland; Swiss Tropical and Public Health Institute, Basel, Switzerland. 4. Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Department of Health and Social Sciences, Universidad de Murcia, Spain. 5. Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy. 6. Unit of Cancer Epidemiology, CRO Aviano National Cancer Institute, Aviano, PN, Italy. 7. Epidemiology Unit and Girona Cancer Registry (Oncology Coordination Plan), Department of Health, Autonomous Government of Catalonia, Catalan Institute of Oncology, Girona Biomedical Research Institute, Girona, Spain. 8. National Institute of Public Health - National Institute of Hygiene, Warsaw, Poland. 9. Departamento de Ciencias Clínicas, Facultad de Medicina, Universitat de Barcelona, Spain; Plan for Oncology of the Catalan Government, L'Hospitalet de Llobregat, Barcelona, Spain.
Abstract
BACKGROUND: The RARECAREnet project has updated the estimates of the burden of the 198 rare cancers in each European country. Suspecting that scant data could affect the reliability of statistical analysis, we employed a Bayesian approach to estimate the incidence of these cancers. METHODS: We analyzed about 2,000,000 rare cancers diagnosed in 2000-2007 provided by 83 population-based cancer registries from 27 European countries. We considered European incidence rates (IRs), calculated over all the data available in RARECAREnet, as a valid a priori to merge with country-specific observed data. Therefore we provided (1) Bayesian estimates of IRs and the yearly numbers of cases of rare cancers in each country; (2) the expected time (T) in years needed to observe one new case; and (3) practical criteria to decide when to use the Bayesian approach. RESULTS: Bayesian and classical estimates did not differ much; substantial differences (>10%) ranged from 77 rare cancers in Iceland to 14 in England. The smaller the population the larger the number of rare cancers needing a Bayesian approach. Bayesian estimates were useful for cancers with fewer than 150 observed cases in a country during the study period; this occurred mostly when the population of the country is small. CONCLUSION: For the first time the Bayesian estimates of IRs and the yearly expected numbers of cases for each rare cancer in each individual European country were calculated. Moreover, the indicator T is useful to convey incidence estimates for exceptionally rare cancers and in small countries; it far exceeds the professional lifespan of a medical doctor.
BACKGROUND: The RARECAREnet project has updated the estimates of the burden of the 198 rare cancers in each European country. Suspecting that scant data could affect the reliability of statistical analysis, we employed a Bayesian approach to estimate the incidence of these cancers. METHODS: We analyzed about 2,000,000 rare cancers diagnosed in 2000-2007 provided by 83 population-based cancer registries from 27 European countries. We considered European incidence rates (IRs), calculated over all the data available in RARECAREnet, as a valid a priori to merge with country-specific observed data. Therefore we provided (1) Bayesian estimates of IRs and the yearly numbers of cases of rare cancers in each country; (2) the expected time (T) in years needed to observe one new case; and (3) practical criteria to decide when to use the Bayesian approach. RESULTS: Bayesian and classical estimates did not differ much; substantial differences (>10%) ranged from 77 rare cancers in Iceland to 14 in England. The smaller the population the larger the number of rare cancers needing a Bayesian approach. Bayesian estimates were useful for cancers with fewer than 150 observed cases in a country during the study period; this occurred mostly when the population of the country is small. CONCLUSION: For the first time the Bayesian estimates of IRs and the yearly expected numbers of cases for each rare cancer in each individual European country were calculated. Moreover, the indicator T is useful to convey incidence estimates for exceptionally rare cancers and in small countries; it far exceeds the professional lifespan of a medical doctor.
Authors: Diego Salmerón; Laura Botta; José Miguel Martínez; Annalisa Trama; Gemma Gatta; Josep M Borràs; Riccardo Capocaccia; Ramon Clèries Journal: Am J Epidemiol Date: 2022-02-19 Impact factor: 4.897
Authors: Gemma A Bilkey; Richard W Trevithick; Emily P Coles; Jennifer Girschik; Kristen J Nowak Journal: BMC Cancer Date: 2021-07-08 Impact factor: 4.430
Authors: M Mena; J Frias-Gomez; M Taberna; B Quirós; S Marquez; O Clavero; A Baena; B Lloveras; M Alejo; X León; J García; R Mesía; O Bermejo; T Bonfill; A Aguila; M Guix; R Hijano; M A Pavón; M Torres; S Tous; R Clèries; L Alemany Journal: Sci Rep Date: 2020-08-06 Impact factor: 4.379