Biomedical subjects

Eric J Feuer

Publications and source records attributed to Eric J Feuer.

32 records · Page 2Linked to original sources

PubMed2004

Comparability of segmented line regression models.

Segmented line regression models, which are composed of continuous linear phases, have been applied to describe changes in rate trend patterns. In this article, we propose a procedure to compare two segmented line regression functions, specifically to test (i) whether the two segmented line regression functions are identical or (ii) whether the two mean functions are parallel allowing different intercepts. A general form of the test statistic is described and then the permutation procedure is proposed to estimate the p-value of the test. The permutation test is compared to an approximate F-test in terms of the p-value estimation and the performance of the permutation test is studied via simulations. The tests are applied to compare female lung cancer mortality rates between two registry areas and also to compare female breast cancer mortality rates between two states.

Biometry↗

PubMed2004

The use of modeling to understand the impact of screening on U.S. mortality: examples from mammography and PSA testing.

Surveillance data represent a vital resource for understanding the impact of cancer control interventions on the population cancer burden. However, population cancer trends are a complex product of many factors, and estimating the contribution of any one of these factors can be challenging. Surveillance modeling is a technique for estimating the contribution of one or more interventions of interest to trends in disease incidence and mortality. In this article, we present several approaches to surveillance modeling of cancer screening interventions. We classify models as biological or epidemiological, depending on whether they model the full unobservable aspects of disease onset and progression, or models which reduce the complex process to simpler terms by summarizing portions of the disease process using mostly observed population level measures. We also describe differences between macrolevel models, microsimulation models and mechanistic models. We discuss procedures for model calibration and validation, and methods for presenting model results which are robust with respect to certain types of biased model estimates. As examples, we present several models of the impact of mammography screening on breast cancer mortality, and PSA screening on prostate cancer mortality. Both these examples are appropriate uses of surveillance modeling, even though for mammography there is extensive (although somewhat controversial) randomized trial evidence, whereas for PSA this biomarker has seen extensive use as a screening test prior to any controlled trial evidence of its efficacy. Some of the models presented here were developed as part of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network.

Breast Neoplasms↗

PubMed2003

The prevalence of patients with colorectal carcinoma under care in the U.S.

BACKGROUND: Prevalence usually is defined as the proportion of individuals alive who previously had a diagnosis of the disease, regardless of whether the individuals still are receiving treatment or are cured. The objective of this study was to estimate the proportion of elderly patients with colorectal carcinoma (CRC) in the U.S. that actually were receiving care for their disease as a better quantification of the burden of CRC. METHODS: The authors used data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program linked to Medicare claims. Four phases of CRC care were defined: initial diagnosis and treatment, postdiagnostic monitoring, treatment for recurrent/metastatic disease, and terminal care. CRC care prevalence measures by phase were extrapolated to the U.S. population age 65 years and older. RESULTS: For all patients with CRC who were diagnosed between 1975 and 1996, 62% received at least 1 service related to their CRC in 1996, and patients received an average of 2.1 months per person of CRC care. Among the U.S. population age 65 years and older, 1.81% had 1 diagnosis of CRC, and (1.81% x 0.62%) = 1.12% received at least 1 service related to their CRC. This translated to 380,783 individuals who received care and 1,210,121 person months of care during 1996. CONCLUSIONS: To the authors' knowledge, this is the first report in which care prevalence has been estimated directly. The classification of CRC care by phases of care provides a very detailed picture of the amount of care delivered in the U.S. population. Person-month estimates can be used to estimate the cost of CRC.

Aged↗

PubMed2003

Age-conditional probabilities of developing cancer.

We propose an estimator of the probability of developing a disease in a given age range, conditional on never having developed the disease prior to the beginning of the age range. Our estimator improves the one described by Wun, Merrill and Feuer ( Lifetime Data Analysis 1998; 4, 169-186) that is currently used by the U.S. National Cancer Institute for the SEER Cancer Statistics Review. Both estimators use cross-sectional disease rates and provide an interpretation of these rates in terms of the age-conditional probability of developing disease in a hypothetical cohort. The difficulty of this problem is that rates are not available per person-years alive and disease free, but only per person-years alive. Wun et al. used ad hoc methods to handle this problem which did not properly account for competing risks, did not provide a measure of variability, and only allowed age ranges using prespecified 5-year age intervals. Here we solve the problem under a unified competing risks framework, which allows the calculation of the age-conditional probabilities for any age range. We generalize gamma confidence intervals to apply to our new statistic. Although our new method provides estimates which are numerically similar to that of Wun et al., this paper provides a comprehensive theoretical basis for estimation and inference about the age-conditional probability of developing a disease.

Age of Onset↗

PubMed2002

Trends in use of adjuvant multi-agent chemotherapy and tamoxifen for breast cancer in the United States: 1975-1999.

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 217 508 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.

Aged↗

PubMed2002

Impact of reporting delay and reporting error on cancer incidence rates and trends.

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.

Adult↗

PubMed2002

Modeling the impact of the decline in distant stage disease on prostate carcinoma mortality rates.

BACKGROUND: The incidence of distant stage prostate carcinoma was relatively flat until 1991 and then started declining rapidly. This decline probably was caused by the shift to earlier stage disease associated with the rapid dissemination of prostate specific antigen (PSA) screening. Prostate carcinoma mortality rates started falling at approximately the same time. In this article, the authors model the potential impact of this stage shift on prostate carcinoma mortality rates given various assumptions concerning the survival of patients with screen-detected local-regional disease. METHODS: The authors used the CAN*TROL 2 computer model to shift each deficit in the number of patients with distant stage disease to local-regional stage disease and modeled the implications on mortality using a set of base, optimistic, and pessimistic survival assumptions. A base survival assumes that a patient with screen-detected local-regional disease of a certain histologic grade has the same prognosis as a patient with clinically detected local-regional disease of same grade (i.e., an assumption of no length bias for patients with screen-detected disease), whereas the optimistic and pessimistic scenarios assume that survival is better or worse, respectively, than the base survival (i.e., complete cure for patients with favorable grade for the optimistic scenario and no improvements in survival for patients with unfavorable grade for the pessimistic scenario). RESULTS: Model results were compared with observed mortality trends. Rising age-adjusted mortality rates peaked in 1991 for white males and in 1993 for black males and then fell 21% and 13% for white males and black males, respectively, from 1990 through 1999. Under the modeled stage-shift intervention, mortality rates would fall 18%, 8%, and 19% for both white males and black males under the base, pessimistic, and optimistic assumptions, respectively. CONCLUSIONS: It is impossible to know what the mortality trends would have been in the absence of the introduction of PSA screening. However, under the base assumption, it appears that the decline in distant stage disease can have a fairly sizable and rapid impact on population mortality. The optimistic scenario is not much improved over the base scenario, which is indicative of the facts that the survival of patients diagnosed with clinical local-regional prostate carcinoma is quite good and that further survival improvements can have only a marginal impact. Under the pessimistic scenario, it appears that something else must be responsible for much of the decline in mortality. Screening trial results from the United States and Europe may verify and isolate the size of any mortality benefit associated with PSA screening. Trial results eventually can be put back into these population models to help quantify the impact of screening, treatment, and other factors on population trends.

Computer Simulation↗

PubMed2002

Overdiagnosis due to prostate-specific antigen screening: lessons from U.S. prostate cancer incidence trends.

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.

Aged↗

PubMed2002

Changing area socioeconomic patterns in U.S. cancer mortality, 1950-1998: Part I--All cancers among men.

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.

Adolescent↗

PubMed2002

Projecting SEER cancer survival rates to the US: an ecological regression approach.

OBJECTIVES: Cancer survival information is available only in areas covered by cancer registration. The objective of this study is to project cancer survival for the entire US as well as states from survival data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program. METHODS: Five-year breast, prostate, and colorectal cancer relative survival rates from SEER are regressed on socioeconomic, demographic, and health variables at the county level. These models are first validated by comparing the observed rates with projected rates for counties not used in the estimation process. RESULTS: Education was the best indicator of longer cancer survival. Other important predictors of the geographical variability of survival varied by cancer site. Better survival was predicted for breast and prostate than for colorectal cancer. CONCLUSIONS: Data from cancer registries can be used in ecological models to provide national and state estimates of patients' survival rates. These estimates are useful in targeting areas in which to promote earlier diagnosis or improved access to care, and may also aid in monitoring the quality of survival data collected by individual cancer registries.

Adult↗

PubMed2002

Estimating the variance of disease-prevalence estimates from population-based registries.

We propose a new Poisson method to estimate the variance for prevalence estimates obtained by the counting method described by Gail et al. (1999, Biometrics 55, 1137-1144) and to construct a confidence interval for the prevalence. We evaluate both the Poisson procedure and the procedure based on the bootstrap proposed by Gail et al. in simulated samples generated by resampling real data. These studies show that both variance estimators usually perform well and yield coverages of confidence intervals at nominal levels. When the number of disease survivors is very small, however, confidence intervals based on the Poisson method have supranominal coverage, whereas those based on the procedure of Gail et al. tend to have below-nominal coverage. For these reasons, we recommend the Poisson method, which also reduces the computational burden considerably.

Analysis of Variance↗

PubMedDate not supplied

A new method of predicting US and state-level cancer mortality counts for the current calendar year.

Every January for more than 40 years, the American Cancer Society (ACS) has estimated the total number of cancer deaths that are expected to occur in the United States and individual states in the upcoming year. In a collaborative effort to improve the accuracy of the predictions, investigators from the National Cancer Institute and the ACS have developed and tested a new prediction method. The new method was used to create the mortality predictions for the first time in Cancer Statistics, 2004 and Cancer Facts & Figures 2004. The authors present a conceptual overview of the previous ACS method and the new state-space method (SSM), and they review the results of rigorous testing to determine which method provides more accurate predictions of the observed number of cancer deaths from the years 1997 to 1999. The accuracy of the methods was compared using squared deviations (the square of the predicted minus observed values) for each of the cancer sites for which predictions are published as well as for all cancer sites combined. At the national level, the squared deviations were not consistently lower for every cancer site for either method, but the average squared deviations (averaged across cancer sites, years, and sex) was substantially lower for the SSM than for the ACS method. During the period 1997 to 1999, the ACS estimates of deaths were usually greater than the observed numbers for all cancer sites combined and for several major individual cancer sites, probably because the ACS method was less sensitive to recent changes in cancer mortality rates (and associated counts) that occurred for several major cancer sites in the early and mid 1990s. The improved accuracy of the new method was particularly evident for prostate cancer, for which mortality rates changed dramatically in the late 1980s and early 1990s. At the state level, the accuracy of the two methods was comparable. Based on these results, the ACS has elected to use the new method for the annual prediction of the number of cancer deaths at the national and state levels.

Cause of Death↗

PubMedDate not supplied

Cancer statistics, 2004.

Each year, the American Cancer Society estimates the number of new cancer cases and deaths expected in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival rates based on incidence data from the National Cancer Institute and mortality data from the National Center for Health Statistics. Incidence and mortality rates are age standardized to the 2000 US standard million population. A total of 1,368,030 new cancer cases and 563,700 deaths are expected in the United States in 2004. Incidence rates stabilized among men from 1995 through 2000 but continued to increase among females by 0.4% per year from 1987 through 2000. Mortality rates have decreased by 1.5% per year since 1992 among men, but have stabilized from 1998 through 2000 among women. Cancer death rates continued to decrease from the three major cancer sites in men (lung and bronchus, colon and rectum, and prostate) and from female breast and colorectal cancers in women. In analyses by race and ethnicity, African-American men and women have 40% and 20% higher death rates from all cancers combined compared with White men and women, respectively. Cancer incidence and mortality rates are lower in other racial and ethnic groups than in Whites and African Americans for all sites combined and for the four major cancer sites. However, these groups generally have higher rates for stomach, liver, and cervical cancers than do Whites. Furthermore, minority populations are more likely to be diagnosed with advanced stage disease than are Whites. Progress in reducing the burden from cancer can be accelerated by applying existing cancer control knowledge into practice among all segments of the population.

Cause of Death↗

PubMedDate not supplied

Cancer statistics, 2005.

Each year, the American Cancer Society estimates the number of new cancer cases and deaths expected in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival based on incidence data from the National Cancer Institute and mortality data from the National Center for Health Statistics. Incidence and death rates are age-standardized to the 2000 US standard million population. A total of 1,372,910 new cancer cases and 570,280 deaths are expected in the United States in 2005. When deaths are aggregated by age, cancer has surpassed heart disease as the leading cause of death for persons younger than 85 since 1999. When adjusted to delayed reporting, cancer incidence rates stabilized in men from 1995 through 2001 but continued to increase by 0.3% per year from 1987 through 2001 in women. The death rate from all cancers combined has decreased by 1.5% per year since 1993 among men and by 0.8% per year since 1992 among women. The mortality rate has also continued to decrease from the three most common cancer sites in men (lung and bronchus, colon and rectum, and prostate) and from breast and colorectal cancers in women. Lung cancer mortality among women has leveled off after increasing for many decades. In analyses by race and ethnicity, African American men and women have 40% and 20% higher death rates from all cancers combined than White men and women, respectively. Cancer incidence and death rates are lower in other racial and ethnic groups than in Whites and African Americans for all sites combined and for the four major cancer sites. However, these groups generally have higher rates for stomach, liver, and cervical cancers than Whites. Furthermore, minority populations are more likely to be diagnosed with advanced stage disease than are Whites. Progress in reducing the burden of suffering and death from cancer can be accelerated by applying existing cancer control knowledge across all segments of the population.

Adolescent↗