We used the most recently available cancer incidence, survival, and medical cost of care data in the United States to estimate and project the national costs of cancer care through the year 2020. In our base case model using constant cancer incidence, survival, and cost of care, we estimated that the national costs of cancer care in 2010 will be approximately $124.57 billion. We projected national costs to increase to $157.77 billion in 2020 under the base case scenario (constant incidence, survival, and cost), a 27% increase. Because we used dynamic assumptions of aging and growing of the US population (3
) for all projections, this increase in costs over time in the base case scenario reflects growth and aging in the population only. The largest increase in cost projected for 2020 was in the continuing care phase for female breast and prostate cancers (). This increase in the number of breast and prostate cancer survivors has important implications for the demand for medical oncologists (20
), as well as the interaction between primary care and oncology for coordination of surveillance care. Our findings will be particularly useful for policy makers for planning and allocation of resources.
We also evaluated a variety of sensitivity analysis scenarios reflecting different assumptions about future trends in incidence, survival, and costs of care. Projections using different assumptions of survival and incidence trends were robust and show that changes in incidence and/or survival have a smaller impact on estimates compared with the aging and growth of the US population. The 2020 predicted costs of cancer care under the assumptions of 1) continuing trends (decreasing incidence and increasing survival) and 2) constant incidence and survival were very similar, 154.70 and 157.77 billion US 2010 dollars, respectively. These estimates represent increases of 27% and 24%, respectively, in cost compared with 2010. In both of these scenarios, we assumed that currently developed cancer control technologies and their current costs will continue as in the past. It is likely that new tools for diagnosis, treatment, and follow-up of cancer patients will be developed and will be more expensive. Assuming recent incidence and survival trends, a 2% increase in annual costs of care in the initial and last year of life phases will result in a 39% increase in costs over the 10 years and a cost estimate of $173 billion in 2020. With expected increases in use of targeted chemotherapies, increases in the cost of a course of treatment are expected to escalate more rapidly. A 5% increase in the annual costs of care in the initial and last year of life phases yields a projected $207 billion in 2020, a 66% increase from 2010. However, trends in costs associated with the use of targeted chemotherapies might be mitigated somewhat through the use of genomic based prognostic markers.
Our estimates of the national cost of cancer care in the year 2010 are higher than those reported elsewhere (5
), even after accounting for differences in the base year used for inflation adjustment. Important differences include our use of the most recent incidence, survival, and cost of care data, identification of cancer patients from registry rather than self-report, use of dynamic population estimates and projections, and detailed methods for estimating cancer prevalence. In particular, our cost estimates were based on Medicare claims through the year 2006, reflecting the use of targeted therapies in this population. In addition, we used a phase of care framework to measure the trajectory of cancer care from diagnosis to death to classify cancer survivors and estimate the cost of care for distinct periods. Costs of care for cancer patients who die of their disease follows a “U-shaped” curve, with the highest costs in the initial phase following diagnosis and the phase before death, and the lowest costs in the period in-between, the continuing phase. This approach not only provides more detailed information of the costs of cancer care but also allows for projections and provides more accurate estimates, especially for less common cancers.
Our estimates for 2010 were substantially higher than a recent study (21
) of national expenditures for cancer treatment in 2001–2005, which used data on Medical Expenditure Panel Survey (MEPS) respondents who reported being treated for cancer. Importantly, population-based surveys such as the MEPS may underidentify respondents with less common cancers or cancers with short survival following diagnosis (eg, lung, brain, gastric, and pancreatic). Individuals who are ill may also be less likely to respond but may be more likely to receive higher levels of medical care. In addition, as shown here and elsewhere (13
), costs in the continuing phase of care are higher for cancer survivors compared with similar individuals without cancer. However, cancer survivors no longer receiving active cancer treatment in the continuing phase could not be identified as having cancer in these surveys. As a result, estimates from surveys, particularly those that estimate “treated prevalence,” are likely to understate national cancer expenditures.
There were limitations to our analysis. Our estimates of cancer prevalence were based on cancer incidence and survival from the SEER-9 areas, which do not cover the entire United States. The SEER areas had lower incidence rates than most other states and have been found to have higher socioeconomic status, greater urban population, and more specialty care than the rest of the US population. In addition, because people can be diagnosed with multiple tumors, cancer prevalence and costs estimates that are based on first tumor diagnosed per person may be underestimates. Our estimates for cancer are not directly comparable to those for other diseases, in part because other diseases do not have the high-quality, comprehensive, population-based disease registries that can be linked to health insurance data to provide information from diagnosis to death. In addition, we do not explicitly control for the presence of diseases other than cancer. If the prevalence of other diseases is the same in cancer patients and control subjects, the net difference is associated only with cancer. However, if the prevalence of other diseases is higher in cancer patients than in control subjects, the net difference reflects costs in cancer patients including those associated with other diseases. Evaluating methods for allocating disease-specific health-care costs is an ongoing area of research (23
We made a number of assumptions to develop our national cost estimates. We assumed that costs associated with cancer care in Medicare fee-for-service and managed care settings are the same. Because managed care plans have not traditionally been required to submit claims or encounter data for services received by their Medicare enrollees, we necessarily excluded managed care beneficiaries from the sample used to develop our cost estimates. To date, no studies have compared the costs of care in Medicare fee-for-service and managed care settings, although a study comparing costs of care for younger colorectal cancer patients in a health maintenance organization and a preferred provider organization reported small but not statistically significant differences (24
). Furthermore, because Medicare provides coverage for almost all of those over the age of 65 years and the linkage of SEER and Medicare claims represents approximately 26% of the US population, the linked SEER–Medicare data are the most comprehensive longitudinal data available for estimating the cost of cancer care in the elderly.
We also made assumptions about the relationship between the costs of cancer care in younger populations and the elderly. In populations younger than 65 years, health insurance is predominantly employer based, with many distinct and separate insurance programs. Comprehensive, longitudinal, population-based insurance data with detailed information about patients and cancer diagnosis (ie, linkage to cancer registries) are generally not available for the population younger than 65 years outside of managed care settings. Because of this lack of comprehensive data for the population under the age of 65 years, we adjusted the SEER–Medicare cost estimates for patients aged 65 years and older by ratios of 1.2 and 1.5 to reflect more aggressive cancer care received by younger cancer patients in the initial and last year of life phases, respectively. These ratios were based on published studies comparing the costs for patients older and younger than 65 years in managed care settings from the early 1990s (18
A more recent study (25
) of treated cancer survivors from the MEPS reported that overall costs among patients younger than 65 years are on average 35% higher than patients of all ages, which is roughly consistent with our estimate of 20% and 50% higher costs for younger patients in the initial and terminal phases, respectively. Because the estimates from the MEPS represented “treated prevalence” and were not reported by phase of care, and the cost data from Health Maintenance Organizations (HMOs) are considerably more detailed and reliable than MEPS data, we relied on the HMO data for our ratios.
Another implication of using the ratios of 1.2 and 1.5 to estimate cost in younger populations is that we assumed that the younger population would have access to care similar to that of the elderly population, and, as for the elderly, we assumed that estimates from the fee-for-service setting are consistent with those from settings with other types of insurance. Although approximately 11% of cancer survivors younger than 65 years are uninsured (25
), diagnosis of cancer confers Medicaid eligibility in many states. Finally, because most cancer prevalence is among those 65 years and older, for whom our data are strongest, limitations associated with our assumptions about cost estimates for the younger age group have a smaller impact in the overall cost estimate.
Because it is difficult to anticipate future developments of cancer control technologies and their impact on survival and incidence trends, we produced future prevalence and cost estimates based on projections of trends in incidence, survival, and costs. These projections were developed separately for each sex and cancer site using reasonable assumptions of future incidence and survival trends based on historical cancer incidence and survival data. In addition, changes in survival and incidence have a reduced impact on prevalence because prevalence includes both people newly diagnosed and those diagnosed more than 1 year ago. The latter represents the vast majority of prevalence cases for most cancer sites. Projections based on these hypothetical scenarios provide a sensitivity analysis of estimates and useful information to future planning and resource allocation.
To investigate the impact of specific cancer control strategies on cancer survivorship and to estimate the societal return on investments in cancer research, more complex modeling approaches are necessary. A cooperative agreement funded by the National Cancer Institute, the Cancer Intervention Surveillance Modeling Network (http://cisnet.cancer.gov/
), uses microsimulation models to investigate the impact of interventions (ie, primary prevention, screening, and treatment) on population-based cohorts of patients with breast, colorectal, prostate, lung, and esophageal cancers. These microsimulation models require as inputs direct estimates of population use, efficacy, sensitivity, and specificity of new interventions, such as screening and treatment, and can produce estimates of survival and incidence that reflect the usage patterns of the assumed interventions. Although these types of projections are undoubtedly more reliable than the projections reported in this article, they each require a substantial research effort and, therefore, can only be done for a very limited number of cancer sites and specific interventions.
Rising health-care costs represent a central challenge for both the federal government and the private sector. The estimates and projections reported in this article may be particularly useful for policy makers for understanding the future burden of cancer care and for prioritizing future resources on cancer research, treatment, and prevention.