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Background: Despite trials of mammography and widespread use, optimal screening policy is controversial. Objective: To evaluate U.S. breast cancer screening strategies. Design: 6 models using common data elements. Data Sources: National data on age-specific incidence, competing mortality, mamography characteristics, and treatment effects. Target Population: A contemporary population cohort. Time Horizon: Lifetime. Perspective: Societal. Interventions: 20 screening strategies with varying initiation and cessation ages applied annually or biennially. Outcome Measures: Number of mammograms, reduction in deaths from breast cancer or life-years gained (vs. no screening), false-positive results, unnecessary biopsies, and overdiagnosis. Results of Base-Case Analysis: The 6 models produced consistent rankings of screening strategies. Screening biennially maintained an average of 81% (range across strategies and models, 67% to 99%) of the benefit of annual screening with almost half the number of false-positive results. Screening biennially from ages 50 to 69 years achieved a median 16.5% (range, 15% to 23%) reduction in breast cancer deaths versus no screening. Initiating biennial screening at age 40 years (vs. 50 years) reduced mortality by an additional 3% (range, 1% to 6%), consumed more resources, and yielded more false-positive results. Biennial screening after age 69 years yielded some additional mortality reduction in all models, but overdiagnosis increased most substantially at older ages. Results of Sensitivity Analysis: Varying test sensitivity or treatment patterns did not change conclusions. Limitation: Results do not include morbidity from false-positive results, patient knowledge of earlier diagnosis, or unnecessary treatment. Conclusion: Biennial screening achieves most of the benefit of annual screening with less harm. Decisions about the best strategy depend on program and individual objectives and the weight placed on benefits, harms, and resource considerations. Primary Funding Source: National Cancer Institute.

Background A model that predicts the economic benefit of reduced cancer mortality provides critical information for allocating scarce resources to the interventions with the greatest benefits. Methods We developed models using the human capital approach, which relies on earnings as a measure of productivity, to estimate the value of productivity lost as a result of cancer mortality. The base model aggregated age- and sex-specific data from four primary sources: 1) the US Bureau of the Census, 2) US death certificate data for 1999-2003, 3) cohort life tables from the Berkeley Mortality Database for 1900-2000, and 4) the Bureau of Labor Statistics Current Population Survey. In a model that included costs of caregiving and household work, data from the National Human Activity Pattern Survey and the Caregiving in the U.S. study were used. Sensitivity analyses were performed using six types of cancer assuming a 1% decline in cancer mortality rates. The values of forgone earnings for employed individuals and imputed forgone earnings for informal caregiving were then estimated for the years 2000-2020. Results The annual productivity cost from cancer mortality in the base model was approximately $115.8 billion in 2000; the projected value was $147.6 billion for 2020. Death from lung cancer accounted for more than 27% of productivity costs. A 1% annual reduction in lung, colorectal, breast, leukemia, pancreatic, and brain cancer mortality lowered productivity costs by $814 million per year. Including imputed earnings lost due to caregiving and household activity increased the base model total productivity cost to $232.4 billion in 2000 and to $308 billion in 2020. Conclusions Investments in programs that target the cancers with high incidence and/or cancers that occur in younger, working-age individuals are likely to yield the greatest reductions in productivity losses to society.

Background Value-of-life methods are increasingly used in policy analyses of the economic burden of disease. The purpose of this study was to estimate and project the value of life lost from cancer deaths in the United States. Methods We estimated and projected US age-specific mortality rates for all cancers and for 16 types of cancer in men and 18 cancers in women in the years 2000-2020 and applied them to US population projections to estimate the number of deaths in each year. Cohort life tables were used to calculate the remaining life expectancy in the absence of cancer deaths--the person-years of life lost (PYLL). We used a willingness-to-pay approach in which the value of life lost due to cancer death was calculated by multiplying PYLL by an estimate of the value of 1 year of life ($150000). We performed sensitivity analyses for female breast, colorectal, lung, and prostate cancers using varying assumptions about future cancer mortality rates through the year 2020. Results The value of life lost from all cancer deaths in the year 2000 was $960.6 billion; lung cancer alone represented more than 25% of this value. Projections for the year 2020 with current cancer mortality rates showed a 53% increase in the total value of life lost ($1472.5 billion). Projected annual decreases of cancer mortality rates of 2% reduced the expected value of life lost in the year 2020 from $121.0 billion to $80.7 billion for breast cancer, $140.1 billion to $93.5 billion for colorectal cancer, from $433.4 billion to $289.4 billion for lung cancer, and from $58.4 billion to $39.0 billion for prostate cancer. Conclusions Estimated value of life lost due to cancer deaths in the United States is substantial and expected to increase dramatically, even if mortality rates remain constant, because of expected population changes. These estimates and projections may help target investments in cancer control strategies to tumor sites that are likely to result in the greatest burden of disease and to interventions that are the most cost-effective.

Background: Understanding trends in the dissemination of findings from clinical research can help in estimating their population-level benefits. We evaluated trends in the use of adjuvant multi-agent chemotherapy, tamoxifen, and the combination of both treatments for early-stage breast cancer in the United States from 1975 through 1999. Methods: Data on treatment of 217508 patients diagnosed from 1975 through 1999 with stages I, II, and IIIA breast cancer were obtained from eight registries of the Surveillance, Epidemiology, and End Results (SEER) Program. Models of dissemination were developed from these data after adjustment based on information from a series of population-based Patterns of Care (POC) studies that randomly selected case patients from the SEER registries. The POC studies included 7116 patients diagnosed from 1987 through 1991 and in 1995 who were eliminated from the SEER data used in this analysis. Results: The modeled disseminations were generally compatible with the POC-observed proportions of each treatment. The use of multi-agent chemotherapy was higher among premenopausal women, and the use of tamoxifen was higher among postmenopausal women. The use of multi-agent chemotherapy for postmenopausal women diagnosed with lymph node-positive stage II+ or stage IIIA cancer reached a peak in 1983 and then decreased through 1986, indicating its substitution with tamoxifen. After 1986, the combined use of multi-agent chemotherapy and tamoxifen increased for almost all stages and ages. After the early 1990s, tamoxifen use in postmenopausal women with stage II+ or stage III breast cancer declined. Conclusions: The observed dissemination patterns suggest that the results of clinical trials are disseminated fairly rapidly to community-based physicians and their patients. [J Natl Cancer Inst 2002;94:1626-34]

Background: Cancer incidence rates and trends are a measure of the cancer burden in the general population. We studied the impact of reporting delay and reporting error on incidence rates and trends for cancers of the female breast, colorectal, lung/bronchus, prostate, and melanoma. Methods: Based on statistical models, we obtained reporting-adjusted (i.e., adjusted for both reporting delay and reporting error) case counts for each diagnosis year beginning in 1981 using reporting information for patients diagnosed with cancer in 1981-1998 from nine cancer registries that participate in the Surveillance, Epidemiology, and End Results (SEER) program. Joinpoint linear regression was used for trend analysis. All statistical tests are two-sided. Results: Initial incidence case counts (i.e., after the standard 2-year delay) accounted for only 88%-97% of the estimated final counts; it would take 4-17 years for 99% or more of the cancer cases to be reported. The percent change between reporting-adjusted and unadjusted cancer incidence rates for the 1998 diagnosis year ranged from 3% for colorectal cancers to 14% for melanoma in whites and for prostate cancer in black males. Reporting-adjusted current incidence trends for breast cancer and lung/bronchus cancer in white females showed statistically significant increases (estimated annual percent change [EAPC] = 0.6%, 95% confidence interval [CI] = 0.1% to 1.2%) and 1.2%, 95% CI = 0.7% to 1.6%, respectively), whereas trends for these cancers using unadjusted incidence rates were not statistically significantly different from zero (EAPC = 0.4%, 95% CI = -0.1% to 0.9% and 0.5%, 95% CI = -0.1% to 1.1%, respectively). Reporting-adjusted melanoma incidence rates for white males showed a statistically significant increase since 1981 (EAPC = 4.1%, 95% CI = 3.8% to 4.4%) in contrast to the unadjusted incidence rate, which was most consistent with a flat or downward trend (EAPC = -4.2%, 95% CI = -11.1% to 3.3 %) after 1996. Conclusions: Reporting-adjusted cancer incidence rates are valuable in precisely determining current cancer incidence rates and trends and in monitoring the timeliness of data collection. Ignoring reporting delay and reporting error may produce downwardly biased cancer incidence trends, particularly in the most recent diagnosis years.

Background: Overdiagnosis of clinically insignificant prostate cancer is considered a major potential drawback of prostate-specific antigen (PSA) screening. Quantitative estimates of the magnitude of this problem are, however, lacking. We estimated rates of prostate cancer overdiagnosis due to PSA testing that are consistent with the observed incidence of prostate cancer in the United States from 1988 through 1998. Overdiagnosis was defined as the detection of prostate cancer through PSA testing that otherwise would not have been diagnosed within the patient's lifetime. Methods: We developed a computer simulation model of PSA testing and subsequent prostate cancer diagnosis and death from prostate cancer among a hypothetical cohort of two million men who were 60-84 years old in 1988. Given values for the expected lead time--that is, the time by which the test advanced diagnosis--and the expected incidence of prostate cancer in the absence of PSA testing, the model projected the increase in population incidence of prostate cancer associated with PSA testing. By comparing the model-projected incidence with the observed incidence derived from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) registry data, we determined the lead times and corresponding overdiagnosis rates that were consistent with the observed data. Results: SEER data on prostate cancer incidence from 1988 through 1998 were consistent with overdiagnosis rates of approximately 29% for whites and 44 % for blacks among men with prostate cancers detected by PSA screening. Conclusions: Among men with prostate cancer that would be detected only at autopsy, these rates correspond to overdiagnosis rates of, at most, 15% in whites and 37% in blacks. The observed trends in prostate cancer incidence are consistent with considerable overdiagnosis among PSA-detected cases. However, the results suggest that the majority of screen-detected cancers diagnosed between 1988 and 1998 would have presented clinically and that only a minority of cases found at autopsy would have been detected by PSA testing. [J Natl Cancer Inst 2002;94: 981-90]

Background: Area socioeconomic deprivation indices are widely used to monitor health disparities in Europe. However, such indices have not been used in cancer surveillance in the United States. We developed an area socioeconomic index to examine area socioeconomic patterns in all-cancer mortality among U.S. men between 1950 and 1998. Methods: Principal components analysis on 11 census variables was used to develop an area socioeconomic index that was then used to stratify all U.S. counties into one of five socioeconomic categories. The index was linked to 1950-1998 county mortality data to generate annual mortality rates for each area socioeconomic group. Joinpoint regression analysis was used to model mortality trends, and Poisson regression analysis was used to estimate socioeconomic gradients in mortality over time. Results: Area socioeconomic patterns in U.S. male cancer mortality changed dramatically between 1950 and 1998. Throughout the 1950s and 1960s, there was a positive socioeconomic gradient, with higher cancer mortality rates in high area socioeconomic groups than in low area socioeconomic groups. For example, in 1950-1952, cancer mortality was 49% (95% confidence interval [CI] = 41% to 59%) greater in the highest area socioeconomic group than in the lowest. The positive gradient narrowed in the 1970s, and by the late 1980s, socioeconomic differences in cancer mortality began to reverse and widen. In 1997-1998, cancer mortality was 19% (95% CI = 11% to 28%) higher in the lowest area socioeconomic group than in the highest. Gradients were steeper for men aged 25-64 years than for men aged 65 years or older. Conclusions: Socioeconomic patterns in male cancer mortality have reversed over time in the United States. Area socioeconomic indices could serve as a powerful surveillance tool for monitoring health disparities in cancer outcomes. [J Natl Cancer Inst 2002;94:904-15]

Background: The lifetime risk of developing breast cancer in U.S. women, often quoted as one in nine, is a commonly cited cancer statistic. However, many estimates have used cancer rates derived from total rather than the cancer-free population and have not properly accounted for multiple cancers in the same individual. Purpose: Our purpose was to provide a revised method for calculating estimates of the lifetime risk of developing breast cancer and to aid in interpretation of the estimates. Methods: A multiple decrement life table was derived by applying age-specific incidence and mortality rates from cross-sectional data to a hypothetical cohort of women. Incidence, mortality, and population data from 1975-1988 were used, representing the geographic areas of the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program. The incidence rates reflected only the First breast primary cancer; mortality rates reflected causes other than breast cancer. The population denominator used in calculating incidence rates was adjusted to reflect only those women without previously diagnosed breast cancers in the hypothetical cohort. Results: Our calculations showed an overall lifetime risk for developing invasive breast cancer of approximately one in eight with use of 1987-1988 SEER data, although up to age 85, it was still the commonly quoted one in nine. Conclusion: Our estimate was calculated assuming constant age-specific rates derived from 1987-1988 SEER data. Because incidence and mortality rates change over time, conditional risk estimates over the short term (10 or 20 years) may be more reliable. A large portion of the rise in the lifetime risk of breast cancer estimated using 1975-1977 data (one in 10.6) to an estimate using 1987-1988 data (one in eight) may be attributed to 1) early detection of prevalent cases due to increased use of mammographic screening and 2) lower mortality due to causes other than breast cancer. A common misperception is that the lifetime risk estimate assumes that all women live to a particular age (e.g., 85 or 95). In fact, the calculation assumes that women can die from causes other than breast cancer at any possible age. Cutting off the lifetime risk calculation at age 85 assumes that no women develop breast cancer after that age. While the lifetime risk of developing breast cancer rose over the period 1976-1977 to 1987-1988, the lifetime risk of dying of breast cancer increased from one in 30 to one in 28, reflecting generally flat mortality trends.

Mammography among older women aged 65 to 74 increased significantly from 1987-88 to 1991, but clinical breast examination decreased over the same period. While older women have twice the breast cancer mortality rate of younger women and although studies suggest breast cancer screening is more effective in older women, they are still less likely to undergo mammography and clinical breast examination than younger women. A study comparing surveys of mammography and clinical breast examination use among older women in five different areas of the US found mammography use increased from 19% to 33% in 1987-88 to 35% to 59% in 1988. However, clinical breast examination use decreased from 95% to 85% among women who had had a mammogram. To be most effective, breast cancer screening should include mammography, clinical breast examination and a third method not surveyed, breast self examination.

Background: The prostate-specific antigen test was approved by the U.S. Food and Drug Administration in 1986 to monitor the disease status in patients with prostate cancer and, in 1994, to aid in prostate cancer detection. However, after 1986, the test was performed on many men who had not been previously diagnosed with prostate cancer, apparently resulting in the diagnosis of a substantial number of early tumors. Our purpose is to provide insight into the effect of screening on prostate cancer rates. Detailed data are presented for whites because the size of the population allows for calculating statistically reliable rates; however, similar overall trends are seen for African-Americans and other races. Methods: Prostate cancer incidence data from the National Cancer Institute's Surveillance, Epidemiology, and End Results Program and mortality data from the National Center for Health Statistics were analyzed. Results/ Conclusions: The following findings are consistent with a screening effect: 1) the recent decrease since 1991 in the incidence of distant stage disease, after not having been perturbed by screening; 2) the decline in the incidence of earlier stage disease beginning the following year (i.e., 1992); 3) the recent increases and decreases in prostate cancer incidence and mortality by age that appear to indicate a calendar period effect; and 4) trends in the incidence of distant stage disease by tumor grade and trends in the survival of patients with distant stage disease by calendar year that provide suggestive evidence of the tendency of screening to detect slower growing tumors. Implications: The decline in the incidence of distant stage disease holds the promise that testing for prostate-specific antigen may lead to a sustained decline in prostate cancer mortality. However, population data are complex, and it is difficult to confidently attribute relatively small changes in mortality to any one cause. [J Natl Cancer Inst 1999;91:1017-24]

Background: The objective of this study was to investigate the circumstances under which dissemination of prostate-specific antigen (PSA) testing, beginning in 1988, could plausibly explain the declines in prostate cancer mortality observed from 1992 through 1994. Methods: We developed a computer simulation model by use of information on population-based PSA testing patterns, cancer detection rates, average lead time (the time by which diagnosis is advanced by screening), and projected decreased risk of death associated with early diagnosis of prostate cancer through PSA testing. The model provides estimates of the number of deaths prevented by PSA testing for the 7-year period from 1988 through 1994 and projects what prostate cancer mortality for these years would have been in the absence of PSA testing. Results: Results were generated by assuming a level of screening efficacy similar to that hypothesized for the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Under this assumption, the projected mortality in the absence of PSA testing continued the increasing trend observed before 1991 only when it was assumed that the mean lead time was 3 years or less. Projected mortality trends in the absence of PSA screening were not consistent with pre-1991 increasing trends for lead times of 5 years and 7 years. Conclusions: When screening is assumed to be at least as efficacious as hypothesized in the PLCO trial, it is unlikely that the entire decline in prostate cancer mortality can be explained by PSA testing based on current beliefs concerning lead time. Only very short lead times,would produce a decline in mortality of the magnitude that has been observed. [J Natl Cancer Inst 1999;91:1033-9]

Background. The rise and fall of prostate cancer mortality correspond closely to the rise and fall of newly diagnosed cases. To understand this phenomenon, we explored the role that screening, treatment, iatrogenic (i.e., treatment-induced) deaths, and attribution bias (incorrect labeling of death from other causes as death from prostate cancer) have played in recent mortality trends. Methods. Join point regression is utilized to assess the recent rise and fall in mortality and the relationship of total U.S. trends to those areas served by the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Cancer Registry Program. Incidence-based mortality (IBM) is estimated with the use of prostate cancer data from the SEER Program to partition (from overall prostate cancer mortality trends) the contribution of cases diagnosed since the widespread use of prostate-specific antigen (PSA) testing starting in 1987. IBM is also used to examine the contribution of stage at diagnosis to the recent prostate cancer mortality trends. Results. IBM for cases diagnosed since 1987 rose above the pre-1987 secular (i.e., background) trend, peaked in the early 1990s, and almost returned to the secular trend by 1994. This rise and fall of IBM track with the pool of prevalent cases diagnosed within the prior 2 years. IBM for cases diagnosed with metastatic disease fell starting in 1991, while IBM for those diagnosed with localized/regional disease was relatively flat. Conclusions. The rise and fall in prostate cancer mortality observed since the introduction of PSA testing in the general population are consistent with a hypothesis that a fixed percent of the rising and falling pool of recently diagnosed patients who die of other causes may be mislabeled as dying of prostate cancer. The decline in IBM for distant stage disease and flat IBM trends for localized/regional disease provide some evidence of improved prognosis for screen-detected cases, although alternative interpretations are possible. [J Natl Cancer Inst 1999;91:1025-32]