When new U.S. cancer incidence and mortality rates are compared with older data, the differences appear startling: 22% more rectal cancer and an 18% increase in female breast cancer.
But rather than revealing an abrupt and staggering surge in cancer cases, they instead reflect a decade-long federal effort to improve cancer statistical data reporting by adjusting rates to a single new population "standard" based on the year 2000 U.S. census.
"Unless you understand that this reflects a change in the statistical methodology rather than an increase in cancer rates, there will be confusion, disappointment, and concern that something has happened to our continuing progress against cancer," said Brenda K. Edwards, Ph.D., associate director of the National Cancer Institutes Surveillance Research Program.
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The change will more accurately and realistically reflect a U.S. population that has significantly more people living longer and that is more racially and ethnically diverse.
Because cancer incidence and mortality tend to occur in older age groups, statistical age-adjustments using the new standard will better reflect the composition of the current population. Adjusting for age and other variables is important because if one used only raw real numbers, states like Florida, where there are large numbers of the elderly, appear to have cancer death rates several times those in states such as Alaska where there are higher numbers of younger adults.
"The rates adjusted to this new standard are closer to the actual observed rates," said Phyllis A. Wingo, Ph.D., chief of the Cancer Surveillance Branch of the National Center for Chronic Disease Prevention and Health Promotion at the Centers for Disease Control and Prevention, Atlanta.
In addition, a more accurate representation of cancer rates will help justify and support public policy decisions, noted Joann Schellenbach, national director of medical and scientific communication for the American Cancer Society. "Current incidence projections indicate a doubling of cancer cases by 2050 with a substantial increase in the number of older cancer patients," she said. "These people will have significant medical needs, and thats something we all need to prepare for. Now, we have a more accurate picture of our population reflecting larger numbers of the elderly."
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In addition, SEER registries collect information on patient demographics, primary tumor site, tumor morphology, stage at diagnosis, treatment, and follow-up.
Data developed and packaged for public distribution by private groups such as the American Cancer Society will reflect the switch to the new standard population, as will this years Annual Report to the Nation on the Status of Cancer, scheduled for publication on May 15 in the journal Cancer.
Edwards predicted that most data users will quickly understand the limitations of comparing data using different standards. But the key message should be that, while actual numbers and rates may differ from those reported earlier, interpretation of the progress made in the field of cancer prevention and control remains the same.
Rates Appear Higher
Anticipating the potential for confusion about the new calculations, the American Cancer Society and other groups have launched an educational effort aimed at data consumers. Materials describing the change and its implications are being made available to reporters, cancer advocates, and other interested parties who will likely notice several striking differences when comparing new cancer rates with those reported in previous years.
For example, people using the new data will notice that there is an apparent 20% increase in the incidence of all cancers combined. Meanwhile, childhood cancer rates will seem to have decreased while rates of cancers in older age groups will seem to have climbed.
Moreover, updated NCHS cancer mortality rates calculated using the new standard instead of the 1940 population standard used previously will result in some striking changes. Rates among whites will appear to vault from 127 deaths per 100,000 to 208 deaths per 100,000, while rates for blacks leap from 173 deaths per 100,000 to 273 deaths per 100,000. (See Stat Bite, p. 711.)
This change will likewise have important implications for analyzing data collected through the CDCs National Program of Cancer Registries, which covers 45 states, three U.S. territories, and the District of Columbia. According to Wingo, the overall magnitude of the newly reported rates will generally be 20% to 50% higher than those previously reported, depending on the data source and population standard that was used.
Comparing Apples to Apples
At the same time, the change will bring relative order to what sometimes seems like chaosa variety of agencies and organizations releasing data based on different U.S. standard populations. For example, SEER calculated cancer rates based on projections of the 1970 U.S. population, while CDC organizations used the 1940 U.S. census, and the American Cancer Society used both.
Schellenbach illustrated just how important population standards are in the calculation of rates. Depending on the population standard used, from 1992 to 1996, cancer mortality rates for blacks were 36% (1940 standard), 33% (1970 standard), or 31% (2000 standard) higher than those for whites. Meanwhile, the mortality rates for whites could be 57%, 59%, or 63% higher than those for Native Americans during this same period.
Comparing rates using one standard population with those using a different standard is like comparing "apples and oranges," according to Edwards. Attempting these kinds of comparisons produces inaccurateand sometimes alarmingresults.
This was illustrated early last year when a Canadian advocacy group held a national press conference to report that Canadian cancer patients died at rates much higher than patients in the United States. Although Canadian cancer researchers pointed out that the group simply drew erroneous conclusions by inaccurately comparing data from the two countries, the statistics had already been widely reported by the Canadian news media (see News, January 17, 2001, p. 89).
Varying Foreign Standards
But even as the United States adopts a single standard, other countries and regions will, at least for now, continue to calculate their rates using a variety of measures.
For example, Canada uses a 1991 population standard, the World Bank uses a projected 2020 and 2050 standard based on estimates from nine industrialized countries, and the World Health Organization uses an estimated 1975 world population, which takes into account the disproportionate impact of childhood and infectious disease on incidence and mortality in developing countries. These differences will continue to limit the ability to compare U.S. rates with those generated abroad.
"The rates will not be directly comparable if they are standardized using a different population. But the situation wont be any worse than before when the U.S. was using another standard," said D. Max Parkin, M.D., chief, Unit of Descriptive Epidemiology at the International Agency for Research on Cancer, Lyon, France. "I think there will be more of a problem within the [United States], where all the old data will have to be recalculated using the new standard."
Data Improvements Under Way
While the adoption of the year 2000 U.S. population standard represents a major modernization effort for those producing cancer statistics, it is one of several such endeavors now being implemented that are designed to improve data products as well as increase cooperation, collaboration, and efficiency among various federal agencies and outside organizations.
A multiyear NCI project that is expected to be unveiled in a report next year involves looking at the relationships between multiple variables including behavioral factors such as smoking and cancer screening. These variables would be compared them over time and geographic area and by various segments of the population.
"Were looking at a whole set of explanatory variables to see if we can build on the relationships between them. We really havent been able to use that information in any systematic way for routine reporting, so were taking a new but model-based approach," Edwards explained.
One potential benefit of these efforts, Edwards said, is streamlining data analysis by developing better, more efficient, and less complicated methodologies. "Its exciting," she said. "Sometimes the simple methods will be just as good as the complex ones."
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