"Collision of Evidence and Assumptions: TMI Deja View": Talbott Response.

We appreciate the interest of Wing and Richardson in our recent follow-up of mortality in the Three Mile Island (TMI) cohort (1). We concur with the suggestion that our data have the potential to advance the overall understanding of the health implications of the TMI incident. We also welcome the opportunity to address several of the issues raised and the concerns expressed by Wing and Richardson within the context of the strengths of our recent mortality analysis.

The primary motivating factor for the University of Pittsburgh in conducting the TMI study (1) was to explore the unknown nature of the health effects of low dose radiation. No other study to date has followed prospectively a large (n = 32,135), free-living, non-occupationally exposed population for an extended period. The only other assessment of low-level exposure was in the Hiroshima atomic bomb survivor studies (2-4), which, by the overall nature of the exposure, was relatively high compared to the more recent TMI incident.

In a reevaluation of an original study by Hatch et al. (5,6) of cancer incidence in the TMI cohort, Wing et al. (7) suggested that specific factors may have detracted from the ability of previous investigators to detect any association of specific radiosensitive cancers with low level radiation exposure at TMI, including: a) the inaccuracy of estimates of the magnitude of radiation exposure during the TMI incident and b) poor classification of relative exposures within the 10-mile study area. The ecologic nature of the Columbia University Study prevented access to individual cancer risk determinants (i.e., tobacco smoking, education, etc.). Further, possible misclassification associated with assignments of exposure based on residence at the time of diagnosis rather than at the time of the accident (5,6) may have occurred. We believe that the methodology employed in our recent mortality investigation addresses several of these key issues.

The individual dose estimates applied to the TMI population in our study were modeled by Gur et al. (8). Gur et al. used the location of residence in relation to TMI (both distance and direction) and information on movements into and out of the area during the 10 days after the accident in conjunction with estimated time-dependent dose--rate distributions to assign likely and maximum possible doses to members of the 13,000 households residing within a 5-mile radius of the TMI nuclear station. The estimated time-dependent dose--rate distribution used to assign individual dose assessments was similar to that developed by Woodard (9) and is described in detail elsewhere (8). With the inclusion of migration factors, this individualized dose estimate may represent a more sensitive measure of individual exposure than does exposure assignment based on study tracts constructed from census block boundaries and meteorologic considerations. Hatch et al. (5,6) noted the potential biases associated with the study tract method, including an inability to control for migration of the population to and from the area and the potential for exposure misclassification, particularly with inward migration. The exposure measures generated by Gur et al. (8) and used in our analyses should at the very least represent a reasonable estimate of individual rather than population-based exposure at the time of the event, and reduce the likelihood of exposure misclassification.

We assessed sociodemographic data and vital status through the TMI Population Registry (10). This registry was a compilation of individual descriptors collected at the time of the special TMI Census in June 1979. Information collected included name, address, age, sex, race, and a brief medical history of cancer diagnoses, thyroid disorders, radiation treatment or therapy, and prior exposure to ionizing radiation on the job. Pregnancies at the time of the accident were noted and smoking history was recorded, as well as the person's daily travel in and out of the 5-mile radius during the 10-day period. The documentation of the tracing of vital status of these individuals within this population was extremely complete. To maintain the follow-up registry, the Pennsylvania Department of Health (PDoH), with the cooperation of the U.S. Postal Service, devised a system to annually obtain the current addresses of persons in the registry without contacting the registrant directly. Names and addresses of all persons in the registry, aged 16 years or older, are sent to the local post office for address verification and update. The post offices are obliged to respond by supplying all relevant forwarding address information on file. Many post offices also correct spelling errors, indicate deceased addressees, and supply other helpful information. Each year, new current addresses are added to the TMI Population Registry database. Details of the follow-up from 1979 through 1992 are presented in Table 1. The PDoH follow-up yielded only 121 individuals who did not have a verified address and vital status through 1992. This represents 0.5% lost to follow-up, or a 99.5% success rate in tracing individuals in this cohort (11).

Table 1. Distribution of TMI cohort by year of follow-up, 1979-1992.

                        Lost to                Death       No death
Year   Population(a)   follow-up   Deaths   certificate   certificate

1979      32,135           0        166         166            0
1980      31,969           4        336         336            0
1981      31,633          20        322         322            0
1982      31,311           6        310         310            0
1983      31,001           6        312         310            2
1984      30,689           0        301         300            1
1985      30,388           2        303         303            0
1986      30,085          11        263         261            2
1987      29,822           0        278         277            1
1988      29,544           8        263         260            3
1989      29,281           0        274         273            1
1990      29,007          25        288         284            4
1991      28,719           0        263         261            2
1992      28,456          39        266         262            4

(a) Lost to follow-up included in population value.

After the 1979 incident, the PDoH has updated mortality status annually. The TMI Population Registry data set is matched yearly against the death certificate file maintained by the department's Health Data Center to identify those TMI residents that have died in Pennsylvania. For TMI residents who have relocated outside of Pennsylvania, the PDoH has an agreement with the National Center for Health Statistics (NCHS) to match the TMI population registry file once every 3 years with the National Death Index (NDI) file maintained by NCHS to identify those who have died outside of Pennsylvania. Data on potential confounders (i.e., sex, race, smoking status, and education) collected at baseline and information on the outcome of interest in the exposed population (i.e., mortality) through 1992 was available for our mortality assessment. Through access of the current NDI national death certificate program, it will be possible to trace all individuals though 1998 and beyond with the same amount of success.

As we suggested in the "Discussion" of our paper (1), mortality, as a function of both incidence and case fatality, may be different from incidence patterns in the TMI cohort. Therefore, it will be important to monitor both cancer incidence and mortality with respect to individualized dose estimates in this population to determine if incidence mirrors the observed mortality experience. However, the mean latency of most radiosensitive solid tumor cancers (lung, breast, and lymphopoetic--hematologic tissue) is 20-30 years (12), and this population is only now experiencing these tumors. In the 1998 follow-up currently in-progress, we intend to assess the significance of this long-term latency and its relationship to cancer incidence and mortality in the TMI population.

Wing and Richardson suggest that the exposures to the population on the day of the accident may have been far greater than previously estimated. In fact, they reference apparent chromosomal effects in this population as potentially attributable to low-level radiation (13,14). A total of 29 blood samples were collected from predominantly older individuals near TMI 15 years after the accident (13,14). There was no local control group and no adjustment for confounding (smoking, occupational exposure) or other environmental insults during this 15-year elapsed period. Hence we can not rule out a spurious cause and effect.

Because we are aware that exposure misclassification error remains a possibility, we agree that it may be reasonable to consider a worst-case scenario regarding exposure, if in fact increases in cancer mortality or morbidity are observed in this population over time. With the data analysis thus far, we have noted no increases that would allude to a more serious exposure scenario than we previously suggested. Assuming, however, that exposure was underestimated across all levels of either likely or maximum gamma, we suggest that a linear trend, if not an absolute association, should be evident if all cause or cause-specific mortality was associated with increasing exposure to low-level radiation.

Our finding of a significant trend of higher likely gamma with increasing breast cancer risk is therefore important. We cited two statistical probabilities in the assessment of this association. The global p-value reflected the statistical significance in assessing overall breast cancer risk when comparing risk levels to the lowest category of each risk factor as baseline. This global p-value was not significant (p = 0.17), indicating no overall difference in breast cancer when the reference group for low gamma exposure was compared to all remaining groups. However, the test for linear trend, which assessed whether a statistically significant dose response was evident when comparing groups to the baseline risk category, was in fact statistically significant (p = 0.02). The risk estimates by exposed and nonexposed subjects suggest possible dose response in incrementally dosed groups (1.76, 1.76, and 2.42). However, multiple comparison adjustments were not considered in this study. Multiple comparison problems occur and often yield significance because of the sheer number of tests done on a population. We have continued to follow the trend in breast cancer and likely gamma exposure in the 1995 update. The data indicate that the trend is slightly attenuated and no longer statistically significant. Continued follow-up of this population is critical to reconciling this important issue.

We agree with Wing and Richardson's comment that using a matching criterion of a 1-month caliper in date of birth may be too precise for such an epidemiologic study. However, we were constricted by hardware and software limitations at the time of the analyses. Because of the size of the total cohort, the risk sets were extremely large, resulting in computational difficulties. The 1-month caliper was used to decrease the risk set size to a more manageable level. This tight match resulted in a loss of only four deaths in the analysis. In comparison to the total deaths, we felt that this was loss was minimal. Fortunately, these software and hardware limitations are no longer an issue, and such a tight match will not be necessary in future updates.

Because childhood cancers are quite different in both presentation and pathology than those manifesting in adults, the mortality and incidence experience of the children of TMI ([is less than] 18 years of age) is currently being assessed in a separate analysis that includes mortality data through 1998. Because potential confounders (education and smoking) were not available for those [is less than] 18 years of age at the time of the accident, we restricted our relative risk regression analysis to those [is greater than or equal to] 18 years of age. Table 2 shows the number of observed deaths for each outcome of interest used in relative risk regression modeling. Also shown is the total number of deaths for the same cause categories that were used in the standardized mortality ratio analyses. As seen in Table 2, 0-4 deaths were omitted when subjects were restricted to those [is greater than or equal to] 18 years of age. Through 1992, a total of six deaths from neoplasms had occurred in individuals [is less than] 18 years of age at the time of the accident.

Table 2. Number of observed deaths available for relative risk
regression modeling.

                                             Males

                            [is greater than       <18 years   Total
                           or equal to] 18 years

All heart causes                    814                 3        817
All malignancies                    419                 4        423
   Bronchus, trachea,               147                 0        147
    and lung cancer
All lymphopoietic and                40                 3         43
    hematopoietic cancer
CNS cancer                            6                 0          6
Breast cancer                        NA                NA         NA

                                             Females

                             [is greater than      <18 years   Total
                           or equal to] 18 years

All heart causes                    851                 2        853
All malignancies                    382                 2        384
   Bronchus, trachea,                56                 0         56
    and lung cancer
All lymphopoietic and                47                 0         47
    hematopoietic cancer
CNS cancer                           11                 1         12
Breast cancer                        78                 0         78

Abbreviations: CNS, central nervous system; NA, not available.

It is reassuring to note that Eastman Kodak (Rochester, NY), in an independent effort, collected and analyzed high-speed photographic film located in the area during the TMI releases (15). None of the film showed any unusual fogging. The minimum exposure level at which fogging occurs is 5 mrem, and no film received an exposure in excess of that amount. At this time, the impact of the radiation exposure from the TMI incident on the mortality of the residents appears minimal. However, due to latency in the development of several radiosensitive malignant neoplasms, we plan to continue our active involvement in the monitoring of health risks in the TMI cohort.

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.) Kato H, Schull WJ. Studies of the mortality of A-bomb survivors. 7 Mortality, 1950-1978: part I. Cancer mortality. Radiat Res 90:395-432 (1982).

(3.) Preston DL, Kato H, Kopecky K J, Fugita S. Life Span Study Report 10. Part 1. Cancer Mortality among A-Bomb Survivors in Hiroshima and Nagasaki, 1950-82. RERF TR 1-86. Hiroshima, Japan:Radiation Effects Research Foundation, 1987.

(4.) Shimizu Y, Kato H, Schull WJ. Life Span Study Report 11. Part II. Cancer Mortality in the Years 1950-1985 Based on the Recently Revised Doses. Hiroshima, Japan:Radiation Effects Research Foundation, 1988.

(5.) Hatch MC, Beyea J, Nieves JW, Susser M. Cancer near the Three Mile Island nuclear plant: radiation emissions. Am J Epidemiol 132:397-412 (1990).

(6.) 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 81:719-724 (1991).

(7.) 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).

(8.) 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).

(9.) Woodard K. Assessment of offsite radiation doses from the Three Mile Island Unit 2 Accident TDR-TMI-116. Newport Beach, CA:Pickard, Lower and Garrick Engineering Services, 1979.

(10.) Ramaswamy K, Tokuhata GK, Hartman TE, Williams DP. Three Mile Island (TMI) population registry-based cohort mortality: 1979-1985 period. Harrisburg, PA: Pennsylvania Department of Health., 1988.

(11.) Ramaswamy K. Personal communication.

(12.) Mettler FA, Upton AC. Medical Effects of Ionizing Radiation. Philadelphia, PA:W.B. Saunders, 1995.

(13.) 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, 1996;39-64.

(14.) 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, 1996;55-77.

(15.) Scranton WW. Report of the Governor's Commission on Three Mile Island. Harrisburg, PA:Commonwealth of Pennsylvania, 1980.

Evelyn O. Talbott Amin Zhang Ada O. Youk Kathleen P. McHugh-Pemu Jeanne V. Zborowski

Graduate School of Public Health University of Pittsburgh Pittsburgh, Pennsylvania E-mail: [e-mail]