THE GROWTH OF BIOSTATISTICS AND ESTIMATION OF CANCER RISK ESTIMATES: PAST, CURRENT, AND FUTURE CHALLENGES.
There has been a long process of growth and development of statistical approaches to the analysis of cancer incidence and mortality data obtained from the follow-up of radiation exposed populations. The challenges of radiation risk analysis provided impetus for innovative statistical methods, including, the inception and continued improvement of hazard rate regression methods. Key statistical contributions that improved cancer risk estimation include statistical advances pertaining to the measurement error problem. Current statistical problems involve extensions of the measurement error methods to account for shared non-independent uncertainties in dose estimation, 'transportability' of risk coefficients for radioprotection and risk estimation world-wide, and extrapolation from high dose rate to low-dose rate exposures or from low LET to high LET. Future problems include quantification of individual sensitivity to radiation-related diseases due to individual genetic differences (or other factors), and in understanding the synergy (additive, multiplicative, etc.) between underlying individual risk and radiation exposure.
Hirosoft Corporation, 1345 H Street, Eureka, CA 95501, USA.
Dale L
DL
Preston
Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90089-9234, USA.
Daniel O
DO
Stram
D056808:Biostatistics; D004307:Dose-Response Relationship, Radiation; D005544:Forecasting; D006801:Humans; D015994:Incidence; D009381:Neoplasms, Radiation-Induced; D011835:Radiation Protection; D018570:Risk Assessment