NEWS

Statistical Projections, Modeling Techniques Help Researchers Measure Progress, Effectiveness

Christine Theisen

Second in a series.

Several organizations collect cancer incidence and mortality rates to study trends and make predictions about future rates so they can allocate resources and develop guidelines (see News, June 18, p. 846). These groups have slightly different approaches to making such predictions, but the goal is the same: To measure progress against cancer and to assess how the groups can improve their own effectiveness.

The World Health Organization (WHO) gathers data from around the globe. For cancer in particular, the International Agency for Research in Cancer (IARC), a subunit of WHO, looks to registry data and surveys. "We use global and national estimates of mortality," said Derek Yach, M.D., Ph.D., executive director of WHO’s Noncommunicable Diseases and Mental Health cluster. A part of the cluster, IARC uses three sources of population-based data on survival: its own Cancer Survival in Developing Countries project, which includes data on China, Cuba, India, the Philippines, and Thailand; Surveillance, Epidemiology, and End Results (SEER) data covering 10% of the U.S. population; and EUROCARE II, which provides data from several different European cancer registries. Mortality data are taken from the WHO mortality data bank and from the most recent national reports of cancer mortality. The WHO estimates cancer prevalence from incidence and survival data.

The American Cancer Society generates annual projections of cancer incidence and mortality primarily from data from government sources—incidence data comes from NCI’s Surveillance, Epidemiology, and End Results program, and mortality data comes from the National Center for Health Statistics at the Centers for Disease Control and Prevention, said Ahmedin Jemal, Ph.D., program director for Cancer Occurrence in the American Cancer Society’s Department of Epidemiology and Surveillance Research. Additional state level data is taken from the North American Association of Central Cancer Registries’ publication Cancer in North America.

The society makes the projections using a statistical time series method, explained Eric "Rocky" Feuer, Ph.D., chief of the Statistical Research Applications Branch in the Surveillance Research Program within NCI’s Division of Cancer Control and Population Sciences. "Those methods are reasonable to do for maybe 2 [or] 3 years into the future, taking the trends that we currently have, saying ‘what do we know about them and how do they project?’" said Feuer.

The lag time in data collection means that the organization must rely on dated data for its projections—3-year-old data from NCHS and 4-year-old data from SEER. The society and NCI are working together to improve mortality projections. "We’re trying to improve the data that we use for projecting cancer deaths. We’re working on a new method that looks very promising," said Jemal. "We are hopeful that we are going to use the new method at least for cancer deaths for next year, for 2004."

Although NCI does not make projections about incidence and mortality rates, it is closely involved with surveillance and modeling that links current data to factors that will affect cancer incidence and mortality. NCI’s SEER program collects data from population-based cancer registries that now cover approximately 26% of the United States. SEER data does not cover every individual in the capture areas but "is linked to census data so that the census data can be used to characterize the socioeconomic status, for example, of cancer patients by where they live," said Martin Brown, Ph.D., chief of the Health Services and Economics Branch of NCI’s Division of Cancer Control and Population Sciences.

In addition to gathering information about current trends through SEER, part of NCI also takes a longer-term approach. "If you want to try to think about what’s going on further in the future, what you want to do is model the things that influence the trends," said Feuer. "For example, the colorectal endoscopy rate is not that high, but maybe we could make big improvements in the future and model different scenarios. And you can project those."

Modeling factors that influence cancer incidence and mortality rates is the focus of an NCI project called the Cancer Intervention and Surveillance Modeling Network (CISNET). The project includes a series of grants for developing and applying statistical models designed to help determine what types of interventions can make a difference in current trends in the incidence and mortality of breast, prostate, colorectal, and lung cancers. "It’s modeling the impact of cancer control interventions—in other words, screening, treatment, and prevention—on current trends, future trends, and what I would call optimal cancer control planning," said Feuer.

The figures from the WHO, NCI, and the American Cancer Society can all be looked at on a broad scale to measure progress against cancer. The CISNET project will add a new dimension to such surveillance by examining health care decisions that are based on modeling, such as the cancer objectives included in Healthy People 2010. Healthy People 2010, a national health promotion and disease prevention initiative, will undergo a midcourse correction in 2005, evaluating progress toward and perhaps revising certain objectives, which will provide a first opportunity for evaluation. "In the future I’m really going to be looking forward to making these links, to make the results as useful as possible," said Feuer.



             
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