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Estimation of Hazard Functions in the Log-Linear Age-Period-Cohort Model: Application to Lung Cancer Risk Associated with Geographical Area
Author(s) -
T. G. Mdzinarishvili,
Michael X. Gleason,
Simon Sherman
Publication year - 2010
Publication title -
cancer informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.606
H-Index - 31
ISSN - 1176-9351
DOI - 10.4137/cin.s4522
Subject(s) - hazard ratio , demography , cohort , hazard , proportional hazards model , categorical variable , medicine , incidence (geometry) , estimation , statistics , gerontology , mathematics , confidence interval , engineering , biology , ecology , geometry , systems engineering , sociology
An efficient computing procedure for estimating the age-specific hazard functions by the log-linear age-period-cohort (LLAPC) model is proposed. This procedure accounts for the influence of time period and birth cohort effects on the distribution of age-specific cancer incidence rates and estimates the hazard function for populations with different exposures to a given categorical risk factor. For these populations, the ratio of the corresponding age-specific hazard functions is proposed for use as a measure of relative hazard. This procedure was used for estimating the risks of lung cancer (LC) for populations living in different geographical areas. For this purpose, the LC incidence rates in white men and women, in three geographical areas (namely: San Francisco-Oakland, Connecticut and Detroit), collected from the SEER 9 database during 1975-2004, were utilized. It was found that in white men the averaged relative hazard (an average of the relative hazards over all ages) of LC in Connecticut vs. San Francisco-Oakland is 1.31 +/- 0.02, while in Detroit vs. San Francisco-Oakland this averaged relative hazard is 1.53 +/- 0.02. In white women, analogous hazards in Connecticut vs. San Francisco-Oakland and Detroit vs. San Francisco-Oakland are 1.22 +/- 0.02 and 1.32 +/- 0.02, correspondingly. The proposed computing procedure can be used for assessing hazard functions for other categorical risk factors, such as gender, race, lifestyle, diet, obesity, etc.

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