Collision of Evidence and Assumptions: TMI Deja View.
Talbott et al.'s paper (1) suffers from the same logical mistake that we identified previously (2). Specifically, the authors undertook a study in which empirical findings cannot lead to rejection of the study's null hypothesis. Both Talbott et al. (1) and Hatch et al. (3,4), who reported on the Columbia University studies of cancer incidence, began with the assumption that the maximum possible radiation doses from the accident were well below average annual background radiation levels. Even if standard radiation risk estimates are underestimated by an order of magnitude or more, such doses would be associated with very small increases in cancer in a general population with heterogeneous susceptibility (2). Given the measurement constraints of epidemiologic studies, it would not be possible to detect an accident-related increase in cancer at the dose levels assumed by these authors. Thus, when they find increased cancer rates among residents assumed to have received relatively higher radiation doses from the accident, such as the significant linear trend in female breast cancer (1), the authors must conclude that the association is not due to the exposure they are studying. There is no scientific reason to conduct a study in which the null hypothesis cannot be rejected due to a priori assumptions. This logical problem was further discussed in letters to EHP (5-8). Interestingly, Talbott et al. (1) did not cite our paper, which introduced this logical problem (2), or the subsequent letters (5-8).
Talbott et al. (1) did not consider the possibility that some people received radiation doses from the TMI accident that were substantially higher than background. Such a possibility is supported by residents' reports of acute symptoms following the accident (9,10) and by evidence of elevated chromosomal aberration rates among persons reporting symptoms (11,12). The radiation dose estimates used by Talbott et al. depended on extensive assumptions about releases and dispersion because no measurements were available for individuals in the study (13). Simplistic assumptions were made about exponential decline of emissions and dispersion over the first 10 days of the accident (13). Further misclassification should be expected from errors in responses to survey questions about locations and movements of persons during this time period. Inability to accurately classify doses in an epidemiologic study threatens its ability to detect effects. Neither Talbott et al. (1) nor the authors of the Columbia studies (3,4) discussed exposure measurement error in interpreting their findings.
Gur et al. (13), the authors of the dosimetry report, state that their methodology was developed "for educational, public relations and defensive epidemiology purposes." This description of the rationale for dosimetry reminds us of the constraints on TMI dosimetry imposed upon other investigators by court order (2,6). That order (14) prohibited the investigators from making
upper limit or worst case estimates of releases of radioactivity or population doses ... [unless] such estimates would lead to a mathematical projection of less than 0.01 health effects and specified that a technical analyst ... designated by counsel for the Pools [nuclear industry insurers] concur on the nature and scope of the [dosimetry] projects.
We were disappointed in the lack of detail provided by Talbott et al. (1) regarding epidemiologic methods typically used in cohort studies. An advantage of their study compared to the Columbia University study (3,4) is that exposed persons could be followed as they left the area; however, there is no information given regarding methods of vital status follow-up, death certificate retrieval, or determination of loss to follow-up. Talbott et al.'s (1) Table 1 presents information for a "1992 cohort," including the number of households, implying that a 'second survey of households might have been done. However, no information is given to explain the 1992 cohort or its relationship to the 1979 cohort.
Because exposed persons were followed, Talbott et al. (1) could also have addressed the problem of tracing birth cohorts through time, a method that could not be employed in the Columbia study (2). Fetal and childhood exposures appear to be particularly effective in producing cancer (15,16); therefore, analyses of cancer mortality among persons exposed at those ages would be of special interest. Talbott et al. (1), however, excluded persons younger than 18 years of age from their dose--response analyses.
The number of persons and cancer deaths included in relative risk regression analyses of dose response were not given (1). These numbers may differ from those presented in Tables 1-4 not only because of the exclusion of persons under 18 years of age but also because of Talbott et al.'s requirement that members of the cohort be born within 1 month of the case in order to be included in the risk set for the case. The authors gave no rationale for using such a narrow restriction, which could limit the size of risk sets, especially at older ages (the median age for the cohort was reported as 29 years), leading to a possible loss of precision because of small risk sets or even loss of cases for which there were no eligible controls.
Studies of relationships between cancer and environmental exposures typically take into account latency periods known to occur between exposure and disease. Failure to consider exposure lag times reduces sensitivity to detect the effects under investigation. Talbott et al. (1) presented no latency analyses.
Although the data collected by Talbott et al. (1) appear to have the potential to advance our understanding of mortality in the TMI area, lack of information about the materials and methods limits our ability to evaluate their report. Furthermore, the statistical issues raised above lead us to question the sensitivity of their analysis to effects under investigation. We hope that more information about this study will be presented in the future, that further analyses will be conducted using methods which increase the study's sensitivity and precision, and that interpretations will be offered that are not inhibited by the a priori assumption that positive results cannot be interpreted as evidence in support of the hypothesis being investigated.
REFERENCES AND NOTES
(1.) Talbott EO, Youk AO, McHugh KP, Shire JD, Zhang A, Murphy BP, Engberg RA. Mortality among the residents of the Three Mile Island accident area: 1979-1992. Environ Health Perspect 108:545-552 (2000).
(2.) Wing S, Richardson D, Armstrong D, Crawford-Brown D. A reevaluation of cancer incidence near the Three Mile Island nuclear plant: the collision of evidence and assumptions. Environ Health Perspect 105:52-57 (1997).
(3.) Hatch MC, Beyea J, Nieves JW, Susser M. Cancer near the Three Mile Island nuclear plant: radiation emissions. Am J Epidemiol 132:397-417 (1990).
(4.) Hatch MC, Wallenstein S, Beyea J, Nieves JW, Susser M. Cancer rates after the Three Mile Island nuclear accident and proximity of residence to the plant. Am J Public Health 81:719-24 (1991).
(5.) Susser M. Consequences of the 1979 Three Mile Island accident continued: further comment [Letter]. Environ Health Perspect 105:566-567 (1997).
(6.) Wing S, Richardson D, Armstrong D. Response: Science, public health and objectivity: research into the accident at Three Mile Island [Letter]. Environ Health Perspect 105:567-570 (1997).
(7.) Mangano J. Low-level radiation harmed humans near Three Mile Island [Letter]. Environ Health Perspect 105:786 (1997).
(8.) Wing S, Richardson D, Armstrong D. Response [Letter]. Environ Health Perspect 105:787 (1997).
(9.) Moholdt B. Summary of acute symptoms by TMI area residents during accident. In: Proceedings of the Workshop on Three Mile Island Dosimetry. Philadelphia, PA:Academy of Natural Sciences, 1985;A109-111.
(10.) Aamodt M, Aamodt N v. United States Nuclear Regulatory Commission. Docket No. 50-289. Administrative Court, Washington, DC, 1984.
(11.) Shevchenko V, Snigiryova G. Cytogenetic effects of the action of ionizing radiation on human populations. In: Consequences of the Chernobyl Catastrophe: Human Health (Burlakova E, ed). Moscow:Center for Russian Environmental Policy, Scientific Council on Radiobiology, Russian Academy of Sciences, 1996;23--45.
(12.) Shevchenko V. Assessment of genetic risk from exposure of human populations to radiation. In: Consequences of the Chernobyl Catastrophe: Human Health (Burlakova E, ed), Moscow:Center for Russian Environmental Policy, Scientific Council on Radiobiology, Russian Academy of Sciences, 1996;46-61.
(13.) Gur D, Good W, Tokuhata G, Goldhaber M, Rosen J, Rao G, Herron J, Miller D, Hollis R. Radiation dose assignment to individuals residing near the Three Mile Island nuclear station. Proc PA Acad Sci 57:99-102 (1983).
(14.) Rambo S. Three Mile Island Litigation. Civil Action 79-0432. Middle District of Pennsylvania, U.S. District Court, 1986.
(15.) Stewart AM, Webb J, Giles D, Hewitt D. Malignant diseases in childhood and diagnostic irradiation in utero. Lancet 2:447 (1956).
(16.) Stewart A. The role of epidemiology in the detection of harmful effects of radiation. Environ Health Perspect 108:93-96 (2000).
Steve Wing Department of Epidemiology School of Public Health University of North Carolina Chapel Hill, North Carolina E-mail: firstname.lastname@example.org David Richardson International Agency for Research on Cancer Lyon, France
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|Publication:||Environmental Health Perspectives|
|Date:||Dec 1, 2000|
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