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http://hdl.handle.net/2445/187901
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DC Field | Value | Language |
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dc.contributor.author | Salmerón, Diego | - |
dc.contributor.author | Botta, Laura | - |
dc.contributor.author | Martínez, José Miguel | - |
dc.contributor.author | Trama, Annalisa | - |
dc.contributor.author | Gatta, Gemma | - |
dc.contributor.author | Borràs Andrés, Josep Maria | - |
dc.contributor.author | Capocaccia, Ricardo | - |
dc.contributor.author | Clèries Soler, Ramon | - |
dc.date.accessioned | 2022-07-19T12:29:41Z | - |
dc.date.available | 2022-07-19T12:29:41Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 0002-9262 | - |
dc.identifier.uri | http://hdl.handle.net/2445/187901 | - |
dc.description.abstract | Estimating incidence of rare cancers is challenging for exceptionally rare entities and in small populations. In a previous study, investigators in the Information Network on Rare Cancers (RARECARENet) provided Bayesian estimates of expected numbers of rare cancers and 95% credible intervals for 27 European countries, using data collected by population-based cancer registries. In that study, slightly different results were found by implementing a Poisson model in integrated nested Laplace approximation/WinBUGS platforms. In this study, we assessed the performance of a Poisson modeling approach for estimating rare cancer incidence rates, oscillating around an overall European average and using small-count data in different scenarios/computational platforms. First, we compared the performance of frequentist, empirical Bayes, and Bayesian approaches for providing 95% confidence/credible intervals for the expected rates in each country. Second, we carried out an empirical study using 190 rare cancers to assess different lower/upper bounds of a uniform prior distribution for the standard deviation of the random effects. For obtaining a reliable measure of variability for country-specific incidence rates, our results suggest the suitability of using 1 as the lower bound for that prior distribution and selecting the random-effects model through an averaged indicator derived from 2 Bayesian model selection criteria: the deviance information criterion and the Watanabe-Akaike information criterion. | - |
dc.format.extent | 12 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Oxford University Press | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1093/aje/kwab262 | - |
dc.relation.ispartof | American Journal of Epidemiology, 2022, vol. 191, num. 3, p. 487-498 | - |
dc.relation.uri | https://doi.org/10.1093/aje/kwab262 | - |
dc.rights | cc by (c) Salmerón, Diego et al., 2022 | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.source | Articles publicats en revistes (Ciències Clíniques) | - |
dc.subject.classification | Càncer | - |
dc.subject.classification | Estimació d'un paràmetre | - |
dc.subject.classification | Epidemiologia | - |
dc.subject.other | Cancer | - |
dc.subject.other | Parameter estimation | - |
dc.subject.other | Epidemiology | - |
dc.title | Estimating country-specific incidence rates of rare cancers: comparative perfomance analysis of modeling approaches using European cancer registry data | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 716056 | - |
dc.date.updated | 2022-07-19T12:29:41Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.pmid | 34718388 | - |
Appears in Collections: | Articles publicats en revistes (Ciències Clíniques) Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
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