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Purpose: To compare ascertainment of central nervous system (CNS) neoplasms with the use of mortality and incidence data as part of an occupational epidemiology study., Methods: Deaths were identified by matching the cohort of 223,894 jet engine manufacturing employees to the U.S. Social Security Administration death files and the National Death Index. Incident cancer cases were identified by matching the cohort to 19 state cancer registries., Results: We identified 718 cases overall: 59% by the use of both mortality and cancer incidence tracing; 24% by the use of only mortality tracing, and 17% by the use of only cancer incidence tracing. Compared with state cancer registries, death certificates missed 38% of the malignant, more than six times the benign and nearly 1.5 times the unspecified CNS cases. The positive predictive value of death certificates, with cancer registry as gold standard, was 6% for unspecified, 35% for benign, and 86% for malignant histologies., Conclusions: Death certificates seriously underascertained benign and unspecified CNS tumors; analyses determined with mortality data would not accurately capture the true extent of disease among the cohort. Most state cancer registries have only collected nonmalignant CNS tumor information since 2004, which currently limits the usefulness of state cancer registries as a source of nonmalignant CNS tumor identification. Underascertainment of CNS deaths could seriously affect interpretation of results, more so if examining nonmalignant CNS., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Purpose: To examine mortality among workers in a pharmaceutical production plant and to address community concerns about 1980 to 1990 increases in local county cancer mortality rates., Methods: Subjects were 1999 workers with some full-time employment during the period between 1970 and 1996. We identified deaths through the year 2000 and reconstructed exposures to nine chemical agents with available exposure measurements. Data analyses included standardized mortality ratios (SMRs) and time trends in local cancer mortality rates., Results: We observed deficits in deaths from all causes combined, all cancers combined, and most cause of death categories examined. Male workers with potential plant exposure had excesses in deaths from all lymphatic-hematopoietic tissue cancers (LHTC), in particular non-Hodgkin's lymphoma (NHL), and respiratory system cancers (RSC) that were larger among long-term workers, but the pattern of findings suggested the excesses were probably not related to occupational factors at the plant. The increase in local county cancer mortality rates was simply the upward cycle of a periodic trend that peaked in 1990 and returned to 1980 levels in 2000., Conclusions: With the possible exceptions of LHTC, in particular NHL, and RSC, this study provided no evidence of elevated total or cause-specific cohort mortality risks. It does not appear that plant factors played a role in the 1980 to 1990 increases in local county cancer mortality rates.

Purpose: In a cohort in which racial data are unknown for some persons, race-specific persons and person-years are imputed using a model-based iterative allocation algorithm (IAA)., Methods: An EM algorithm-based approach to address misclassification in a censored data regression setting can be adapted to estimate the probability that a person of unknown race is white. The corresponding race-specific person-years are obtained as a by-product of the estimation procedure. Variance estimates are computed using the bootstrap. The proposed approach is compared with the proportional allocation method (PAM)., Results: In an occupational cohort where racial data were missing for 41% of the workers, the age-time-race-specific person-years were estimated within a relative variation of approximately 20%, using the IAA. The deaths were less reliably estimated. The standardized mortality ratios (SMRs) for all-cause mortality estimated using the IAA and the PAM were more similar for the non-white workers than for a smaller subgroup of white workers., Conclusions: The IAA provides a method to reliably estimate race-specific person-year denominators in cohort studies with missing racial data. This method is applicable to other incompletely observed non-time-dependent categorical covariates. Internal cohort rates or SMRs can be computed and modeled, with bootstrap confidence intervals that account for the uncertainty in the determination of race.