Monte Carlo Analysis of Impact of Underascertainment of Mesothelioma Cases on Underestimation of Risk
Leonid Kopylev*, 1, Patricia A. Sullivan2, Lisa C. Vinikoor1, Thomas F. Bateson1
Identifiers and Pagination:Year: 2011
First Page: 45
Last Page: 53
Publisher Id: TOEPIJ-4-45
Article History:Received Date: 04/02/2010
Revision Received Date: 15/04/2010
Acceptance Date: 20/04/2010
Electronic publication date: 19/1/2011
Collection year: 2011
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The accuracy of cancer mortality data varies across different cancers. Mortality records and death certificates may not always reflect the true cause of death for various reasons (e.g., misdiagnosis, improper recording on the death certificate, miscoding of the cause of death recorded on the death certificate). Mesothelioma, a rare tumor which is caused by exposure to asbestos, is a special case. Until 1999 when the 10th revision of the International Classification of Diseases (ICD-10) introduced a specific mesothelioma code, mesothelioma deaths were coded to other causes (e.g., cancer of the pleura, cancer of other or ill-specified sites). Even after the introduction of this mesothelioma code, researchers have shown that estimates of mesothelioma mortality based on death certificates are still biased downward. This article reviews available literature with quantitative information on mesothelioma underascertainment, in particular on different rates of underestimation for pleural and peritoneal mesotheliomas, and suggests two approaches to estimating downward bias in absolute risk estimates due to mesothelioma underascertainment. The choice of approach used depends on whether the information on the proportion of peritoneal mesotheliomas is available. Both approaches are demonstrated and evaluated using a cohort of asbestos workers from Libby, MT. The methods developed in this article may be used in analyses of other asbestos cohorts and in methodologies to predict future mesothelioma burden in populations. Similar approaches can be used to assess the impact of underascertainment of other cancers on risk estimates of other chemicals.