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The likelihood of developing cancer during one's lifetime is
approximately one in two for men and one in three for women in the
United States. Cancer is the second-leading cause of death and
accounts for one in every four deaths. Evidence-based policy
planning and decision making by cancer researchers and public health
administrators are best accomplished with up-to-date age-adjusted
site-specific cancer death rates. Because of the 3-year lag in
reporting, forecasting methodology is employed here to estimate the
current year's rates based on complete observed death data up
through three years prior to the current year. The authors expand
the State Space Model (SSM) statistical methodology currently in use
by the American Cancer Society (ACS) to predict age-adjusted cancer
death rates for the current year. These predictions are compared
with those from the previous Proc Forecast ACS method and results
suggest the expanded SSM performs well.


Originally published in:

Hayat, M.J., Tiwari, R.C., Ghosh, K., Hachey, M., Hankey, B., Feuer, R. 2010. “Age-Adjusted US Cancer Death Rate Predictions,” Journal of Data Science, 8: 339-348.

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