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A New Method of Estimating United States and State-level Cancer Incidence Counts for the Current Calendar Year

Dr. Pickle is Senior Mathematical Statistician and Coordinator of Geographic Research, Statistical Research and Applications Branch, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD.
Dr. Hao is GIS Analyst and Statistician, Department of Epidemiology and Surveillance Research, American Cancer Society, Atlanta, GA.
Dr. Jemal is Strategic Director, Cancer Occurrence, Department of Epidemiology and Surveillance Research, American Cancer Society, Atlanta, GA.
Mr. Zou is Statistical Programmer, Information Management Services, Inc., Silver Spring, MD.
Dr. Tiwari is Mathematical Statistician and Program Director, Statistical Research and Applications Branch, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD.
Dr. Ward is Managing Director, Surveillance Research, Department of Epidemiology and Surveillance Research, American Cancer Society, Atlanta, GA.
Mr. Hachey is Statistical Programmer, Information Management Services, Inc., Silver Spring, MD.
Dr. Howe is Executive Director, North American Association of Central Cancer Registries, Inc., Springfield, IL.
Dr. Feuer is Chief, Statistical Research and Applications Branch, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD.

This article is available online at http://CAonline.AmCancerSoc.org

The American Cancer Society (ACS) has published the estimated number of new cancer cases and deaths in the current year for the United States that are commonly used by cancer control planners and the media. The methods used to produce these estimates have changed over the years as data (incidence) and statistical models improved. In this paper we present a new method that uses statistical models of cancer incidence that incorporate potential predictors of spatial and temporal variation of cancer occurrence and that account for delay in case reporting and then projects these estimated numbers of cases ahead 4 years using a piecewise linear (joinpoint) regression method. Based on evidence presented here that the new method produces more accurate estimates of the number of new cancer cases for years and areas for which data are available for comparison, the ACS has elected to use it to estimate the number of new cancer cases in Cancer Facts & Figures 2007 and in Cancer Statistics, 2007.

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