Last data update: May 13, 2024. (Total: 46773 publications since 2009)
Records 1-2 (of 2 Records) |
Query Trace: Sullivan PA[original query] |
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Monte Carlo analysis of impact of underascertainment of mesothelioma cases on underestimation of risk
Kopylev L , Sullivan PA , Vinikoor LC , Bateson TF . Open Epidemiol J 2011 4 (1) 45-53 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. |
Occupational lung cancer in US women, 1984-1998
Robinson CF , Sullivan PA , Li J , Walker JT . Am J Ind Med 2010 54 (2) 102-17 BACKGROUND: Lung cancer is the leading cause of cancer death in US women, accounting for 72,130 deaths in 2006. In addition to smoking cessation, further reduction of the burden of lung cancer mortality can be made by preventing exposure to occupational lung carcinogens. Data for occupational exposures and health outcomes of US working women are limited. METHODS: Population-based mortality data for 4,570,711 women who died between 1984 and 1998 in 27 US States were used to evaluate lung cancer proportionate mortality over time by the usual occupation and industry reported on death certificates. Lung cancer proportionate mortality ratios were adjusted for smoking, using data from the National Health Interview Survey (NHIS) and the American Cancer Society's Cancer Prevention Study II. RESULTS: Analyses revealed that 194,382 white, 18,225 Black and 1,515 Hispanic women died 1984-1998 with lung cancer reported as the underlying cause of death. Following adjustment for smoking, significant excess proportionate lung cancer mortality was observed among US women working in the US manufacturing; transportation; retail trade; agriculture, forestry, and fishing; and nursing/personal care industries. Women employed in precision production, technical, managerial, professional specialty, and administrative occupations experienced some of the highest significantly excess proportionate lung cancer mortality during 1984-1998. CONCLUSIONS: The results of our study point to significantly elevated risks for lung cancer after adjustment for smoking among women in several occupations and industries. Because 6-17% of lung cancer in US males is attributable to known exposures to occupational carcinogens, and since synergistic interactions between cigarette smoke and other occupational lung carcinogens have been noted, it is important to continue research into the effects of occupational exposures on working men and women. Am. J. Ind. Med. (c) 2010 Wiley-Liss, Inc. |
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