Technical Report No. 17-91
Joint analysis of site-specific cancer risks for the atomic bomb survivors
Pierce DA, Preston DLEditor’s note: A publication based on this report was published in Radiat Res 134(2):134-42, 1993.
Summary
Statistical methods are presented for joint analysis of site-specific cancer risks for the atomic-bomb survivors. Previous analyses of these data, aside from those on leukemia, have been made either without regard to cancer type, or separately for types or classes of cancers. Clearly, analyses without regard to cancer type are less than satisfactory. The primary advantages of joint, rather than separate, analyses are that (1) models can be fitted with parameters common to cancer types, which can allow more-precise estimation of effects of interest, (2) significance tests can be used to compare type-specific risks, and (3) a clearer understanding may be obtained of risk-modification factors such as sex, age at exposure, and time since exposure. Joint analysis is straightforward, entailing primarily the incorporation of another factor for cancer type in the usual cross-tabulation of the data for analysis. The use of these methods is illustrated in an analysis of three categories of cancer studied by the fifth Advisory Committee on the Biological Effects of Ionizing Radiation (BEIR V): digestive, respiratory, and other solid tumors. Based on this analysis, some criticism is made of the BEIR V-preferred models. Since the proposed methods are applicable to models for either relative or absolute risks, some comments on the use of explicit models for the absolute excess risk are also given. Although some of the gains from joint analysis are apparent from the results here, it will be important to use these methods with a more suitable choice of cancer classes and for cancer incidence data in which the diagnoses are more accurate.
Statistical methods are presented for joint analysis of site-specific cancer risks for the atomic-bomb survivors. Previous analyses of these data, aside from those on leukemia, have been made either without regard to cancer type, or separately for types or classes of cancers. Clearly, analyses without regard to cancer type are less than satisfactory. The primary advantages of joint, rather than separate, analyses are that (1) models can be fitted with parameters common to cancer types, which can allow more-precise estimation of effects of interest, (2) significance tests can be used to compare type-specific risks, and (3) a clearer understanding may be obtained of risk-modification factors such as sex, age at exposure, and time since exposure. Joint analysis is straightforward, entailing primarily the incorporation of another factor for cancer type in the usual cross-tabulation of the data for analysis. The use of these methods is illustrated in an analysis of three categories of cancer studied by the fifth Advisory Committee on the Biological Effects of Ionizing Radiation (BEIR V): digestive, respiratory, and other solid tumors. Based on this analysis, some criticism is made of the BEIR V-preferred models. Since the proposed methods are applicable to models for either relative or absolute risks, some comments on the use of explicit models for the absolute excess risk are also given. Although some of the gains from joint analysis are apparent from the results here, it will be important to use these methods with a more suitable choice of cancer classes and for cancer incidence data in which the diagnoses are more accurate.