ANALYSIS OF LUNG CANCER MORTALITY RECORDS/DEVELOP QUANTITATIVE WORKING MODEL

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We have collected the data for all forms of mortality reported to the U.S. Public Health Service from 1900 to the present day and carefully matched these records to the sizes of the populations form which the reports were made. With these data we are able to observe the age-specific mortality rates for birth cohorts reaching to the early nineteenth century. With these data we have undertaken development of quantitative working model of lung cancer building on the general models of Knudson and Moolgavkar. This model uses what is known about the number and kind of genetic changes which occur early in carcinogenesis and age-specific mutant fractions in human somatic cells to derive estimates of the rate for key processes in cancer initiation and progression in lung epithelium of smokers and non- smokers. In particular we have been able to make quantitative predictions for the rates of initiation mutations, the growth rates in intermediate pre-neoplastic colonies and the rates of mutation in such colonies leading to a frankly neoplastic cell. Our model does not extend to the mutations and population dynamics of adenocarcinomas or carcinomas, as these, which occur in a relatively short time, cannot be derived from age-specific mortality data. These quantitative predictions serve as quantitative hypothesis about the effects of exposure to tobacco smoke and urban pollutants on mutation rates and cell kinetics in human lungs. Because the national mortality data do not allow us to address the possible effect of urban air exposure and lifetime lung cancer probabilities, we have begun analysis of the mortality in all cities, towns and villages in Massachusetts using the computerized records from 1969 to the present data. Classifying reporting units as rural, suburban or urban we will re-examine the general contention that urban residents have a higher age-specific lung cancer rate with attention to the age- specific lung cancer rate parameters that night differ as a function of residential location. This analysis may allow us to identify any interaction between urban/rural residence and cigarette smoking, since the great preponderance of lung cancer cases are among smokers.