Statistical issues in biological radiation dosimetry for risk assessment using stable chromosome aberrations.

Biological dosimeters are useful for epidemiologic risk assessment in populations exposed to catastrophic nuclear events and as a means of validating physical dosimetry in radiation workers. Application requires knowledge of the magnitude of uncertainty in the biological dose estimates and an understanding of potential statistical pitfalls arising from their use. This paper describes the statistical aspects of biological dosimetry in general and presents a detailed analysis in the specific case of dosimetry for risk assessment using stable chromosome aberration frequency. Biological dose estimates may be obtained from a dose-response curve, but negative estimates can result and adjustment must be made for regression bias due to imprecise estimation when the estimates are used in regression analyses. Posterior-mean estimates, derived as the mean of the distribution of true doses compatible with a given value of the biological endpoint, have several desirable properties: they are nonnegative, less sensitive to extreme skewness in the true dose distribution, and implicitly adjusted to avoid regression bias. The methods necessitate approximating the true-dose distribution in the population in which biological dosimetry is being applied, which calls for careful consideration of this distribution through other information. An important question addressed here is to what extent the methods are robust to misspecification of this distribution, because in many applications of biological dosimetry it cannot be characterized well. The findings suggest that dosimetry based solely on stable chromosome aberration frequency may be useful for population-based risk assessment.

[1]  S. Ban,et al.  Application of generalized estimating equations to a study of in vitro radiation sensitivity. , 1993, Biometrics.

[2]  W. Bigbee,et al.  Biodosimetry for a radiation worker using multiple assays. , 1992, Health Physics.

[3]  T. Sofuni,et al.  Relationship between the radiation dose and chromosome aberrations in atomic bomb survivors of Hiroshima and Nagasaki. , 1978, Journal of radiation research.

[4]  M. Pilinskaya.  The results of selective cytogenetic monitoring of Chernobyl accident victims in the Ukraine. , 1996, Health physics.

[5]  A. Awa,et al.  Somatic cell mutations at the glycophorin A locus in erythrocytes of atomic bomb survivors: implications for radiation carcinogenesis. , 1996, Radiation research.

[6]  S. Chow,et al.  On the Difference between the Classical and Inverse Methods of Calibration , 1990 .

[7]  D. Pierce,et al.  Allowing for random errors in radiation dose estimates for the atomic bomb survivor data. , 1990, Radiation research.

[8]  J. Konishi,et al.  Frequency of mutant T lymphocytes defective in the expression of the T-cell antigen receptor gene among radiation-exposed people. , 1992, Mutation research.

[9]  D O Stram,et al.  An estimate of the magnitude of random errors in the DS86 dosimetry from data on chromosome aberrations and severe epilation. , 1991, Radiation research.

[10]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[11]  R. Carter.  Restricted Maximum Likelihood Estimation of Bias and Reliability in the Comparison of Several Measuring Methods , 1981 .

[12]  D A Pierce,et al.  Studies of the mortality of atomic bomb survivors. Report 12, Part I. Cancer: 1950-1990. , 1996, Radiation research.

[13]  W. Bigbee,et al.  Evidence for increased somatic cell mutations at the glycophorin A locus in atomic bomb survivors. , 1987, Science.

[14]  N. G. Bougrov,et al.  An approach to dose reconstruction for the Urals population. , 1996, Health physics.

[15]  Daniel O. Stram,et al.  The Errors-in-Variables Problem: Considerations Provided by Radiation Dose-Response Analyses of the A-Bomb Survivor Data , 1992 .

[16]  Max Halperin,et al.  On Inverse Estimation in Linear Regression , 1970 .

[17]  C. Lushbaugh,et al.  Current status of biological indicators to detect and quantify previous exposures to radiation. Biological Indicators Working Group. , 1991, Health Physics.

[18]  J. Friedman.  A VARIABLE SPAN SMOOTHER , 1984 .

[19]  M. Bauchinger,et al.  The suitability of the human lymphocyte micronucleus assay system for biological dosimetry. , 1983, Mutation research.

[20]  W. A. Woolson,et al.  Neutron discrepancies in the DS86 Hiroshima dosimetry system. , 1992, Health physics.

[21]  S. Ban,et al.  X-ray induction of micronuclei in human lymphocyte subpopulations differentiated by immunoperoxidase staining. , 1992, Radiation research.

[22]  R. G. Krutchkoff,et al.  Classical and Inverse Regression Methods of Calibration , 1967 .

[23]  Dirk F. Moore,et al.  Modelling the Extraneous Variance in the Presence of Extra‐Binomial Variation , 1987 .

[24]  M. Bender,et al.  Current status of cytogenetic procedures to detect and quantify previous exposures to radiation. , 1988, Mutation research.

[25]  W. Fuller,et al.  Instrumental Variable Estimation of the Simple Errors-in-Variables Model , 1980 .

[26]  E. Wegman.  Nonparametric probability density estimation , 1972 .

[27]  E. Wegman.  Nonparametric Probability Density Estimation: I. A Summary of Available Methods , 1972 .

[28]  A. Carrano,et al.  Biological effectiveness of neutrons from Hiroshima bomb replica: results of a collaborative cytogenetic study. , 1991, Radiation research.

[29]  D O Stram,et al.  Stable chromosome aberrations among A-bomb survivors: an update. , 1993, Radiation research.

[30]  T. Sofuni,et al.  Chromosome-aberration frequency in cultured blood-cells in relation to radiation dose of A-bomb survivors. , 1971, Lancet.

[31]  J. Savage.  Radiation-Induced Chromosome Damage in Man , 1984 .

[32]  J. A. Walker,et al.  Radiation-induced apoptosis in human lymphocytes: potential as a biological dosimeter. , 1996, Health physics.