Construction of a North American Cancer Survival Index to Measure Progress of Cancer Control Efforts
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Construction of a North American Cancer Survival Index to Measure Progress of Cancer Control Efforts

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  • Alternative Title:
    Prev Chronic Dis
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    Population-based cancer survival data provide insight into the effectiveness of health care delivery. Comparing survival for all cancer sites combined is challenging, because the primary cancer site and age distribution of patients may differ among areas or change over time. Cancer survival indices (CSIs) are summary measures of survival for cancers of all sites combined and are used in England and Europe to monitor temporal trends and examine geographic differences in survival. We describe the construction of the North American Cancer Survival Index and demonstrate how it can be used to compare survival by geographic area and by race.


    We used data from 36 US cancer registries to estimate relative survival ratios for people diagnosed with cancer from 2006 through 2012 to create the CSI: the weighted sum of age-standardized, site-specific, relative survival ratios, with weights derived from the distribution of incident cases by sex and primary site from 2006 through 2008. The CSI was calculated for 32 registries for all races, 31 registries for whites, and 12 registries for blacks.


    The survival estimates standardized by age only versus age-, sex-, and site-standardized (CSI) were 64.1% (95% confidence interval [CI], 64.1%–64.2%) and 63.9% (95% CI, 63.8%–63.9%), respectively, for the United States for all races combined. The inter-registry ranges in unstandardized and CSI estimates decreased from 12.3% to 5.0% for whites, and from 5.4% to 3.9% for blacks. We found less inter-registry variation in CSI estimates than in unstandardized all-sites survival estimates, but disparities by race persisted.


    CSIs calculated for different jurisdictions or periods are directly comparable, because they are standardized by age, sex, and primary site. A national CSI could be used to measure temporal progress in meeting public health objectives, such as Healthy People 2030.

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