Bowel surveillance patterns after a diagnosis of colorectal cancer in Medicare beneficiaries.

BACKGROUND: Postoperative colon surveillance has been recommended for patients with a diagnosis of local/regional colorectal cancer. The extent to which these recommendations are followed in practice is poorly characterized. Patterns of surveillance after surgery for colorectal cancer were determined by using a large population-based database. METHODS: This is a retrospective cohort study with cancer registry data linked to Medicare claims. Identified were 52,283 patients treated for local/regional colorectal cancer between 1986 and 1996, and surveillance patterns through 1998 were determined. Surveillance patterns were analyzed by using survival analysis and by computing the proportion of surviving patients who underwent procedures during 4 time periods after treatment: 2 to 14 months, 15 to 50 months, 51 to 86 months and more than 87 months. RESULTS: Median times to first through fifth surveillance events were 20, 14, 15, 15, and 15 months, respectively. For 17% of the cohort there was no surveillance event. Younger patients were more likely to undergo surveillance. Surveillance patterns were not affected by stage. The proportions of the cohort that underwent no surveillance during the 4 respective time periods were 54%, 52%, 60%, and 69%. The percentages of patients who underwent surveillance annually or more frequently in the latter 3 time periods, respectively, were 19%, 10%, and 5%, or 11% overall, treating the data for the 3 events as a whole. Over the period from 1986 to 1998, the proportion of patients who had no surveillance procedures gradually decreased, whereas the proportion of those who underwent procedures annually or more frequently remained relatively constant. CONCLUSIONS: During the period from 1986 to 1998 there was low utilization of postdiagnosis colon surveillance in a substantial proportion of elderly patients with a diagnosis of local/regional colorectal cancer. Over time there was a trend toward increasing receipt of any surveillance procedures. The percentages of patients undergoing surveillance annually or more frequently did not change between earlier and later periods.

Impact of screening on incidence and mortality of prostate cancer in the United States.

The potential confounding influence of changing treatment patterns and misattribution bias make a definitive conclusion about the link between PSA screening and mortality rates tentative at best. At least some of the mortality decline since 1991 appears likely to be due to screening, but the precise magnitude of the screening effect is difficult to estimate. The possible reduction in mortality due to screening, while uncertain, must be weighed against the substantial decrements in treatment-specific health outcomes (32-34) among men treated for clinically localized tumors typically detected by screening. Population data and ongoing screening trials in the United States and Europe (24, 35) will be complementary in the final determination of the relative contribution of the impact of screening versus other causes on recent mortality trends.

Evaluating the impact of population changes in diet, physical activity, and weight status on population risk for colon cancer (United States).

OBJECTIVE: To estimate the effects of observed population-level changes in risk factors on population risk and incidence of disease. METHODS: Trends in a set of risk factors for colon cancer (vegetable intake, red meat intake, alcohol consumption, physical activity levels, and weight status) were modeled for the US adult population over the years 1975-1995 and combined with relative risk estimates from epidemiologic studies and a probability distribution for the induction period to estimate the percentage change in incidence rates from 1985 to 1995 due to the five risk factors. A sensitivity analysis was performed to account for imprecision related to estimates of trends in behavior and epidemiologic risk. RESULTS: Increased vegetable intake and decreased intakes of red meat and alcohol reduced risk, while reduced physical activity and increased body mass index increased risk for colon cancer. When all five factors were considered together, change in the average population relative risk was small and the risk factors accounted for little of the recently observed decline in incidence. CONCLUSIONS: Although these factors have the potential to greatly affect risk of colon cancer and incidence rates, little of that potential was realized since adverse trends neutralized what progress had been made in the areas of vegetables, red meat, and alcohol consumption.

The changing face of cancer survivorship.

OBJECTIVES: To provide a review of who is surviving cancer diagnosed within the last 20 years and key areas for research development related to cancer survivorship. DATA SOURCES: Articles, studies, and Surveillance, Epidemiology and End Results statistics. CONCLUSIONS: The information we have on today's survivors must be periodically revisited and revised to equip cancer patients with the knowledge and tools they need to master the new realities of their survivorship. IMPLICATIONS FOR NURSING PRACTICE: With the increasing numbers of individuals being cured of or living long periods of time following a diagnosis of cancer, oncology nurses who work with cancer survivors must maintain their knowledge of the issues and practices critical to the well-being of the patient.

Cumulative cause-specific mortality for cancer patients in the presence of other causes: a crude analogue of relative survival.

A common population-based cancer progress measure for net survival (survival in the absence of other causes) of cancer patients is relative survival. Relative survival is defined as the ratio of a population of observed survivors in a cohort of cancer patients to the proportion of expected survivors in a comparable set of cancer-free individuals in the general public, thus giving a measure of excess mortality due to cancer. Relative survival was originally designed to address the question of whether or not there is evidence that patients have been cured. It has proven to be a useful survival measure in several areas, including the evaluation of cancer control efforts and the application of cure models. However, it is not representative of the actual survival patterns observed in a cohort of cancer patients. This paper suggests a measure for cumulative crude (in the presence of other causes) cause-specific probability of death for a population diagnosed with cancer. The measure does not use cause of death information which can be unreliable for population cancer registries. Point estimates and variances are derived for crude cause-specific probability of death using relative survival instead of cause of death information. Examples are given for men diagnosed with localized prostate cancer over the age of 70 and women diagnosed with regional breast cancer using Surveillance, Epidemiology and End Results (SEER) Program data. The examples emphasize the differences in crude and net mortality measures and suggest areas where a crude measure is more informative. Estimates of this type are especially important for older patients as new screening modalities detect cancers earlier and choice of treatment or even 'watchful waiting' become viable options. Published in 2000 by John Wiley & Sons, Ltd.

Cancer prevalence estimates based on tumour registry data in the Surveillance, Epidemiology, and End Results (SEER) Program.

BACKGROUND: The Connecticut Tumor Registry (CTR) has collected cancer data for a sufficiently long period of time to capture essentially all prevalent cases of cancer, and to provide unbiased estimates of cancer prevalence. However, prevalence proportions estimated from Connecticut data may not be representative of the total US, particularly for racial/ethnic subgroups. The purpose of this study is to apply the modelling approach developed by Capocaccia and De Angelis to cancer data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute to obtain more representative US site-specific cancer prevalence proportion estimates for white and black patients. METHODS: Incidence and relative survival were modelled and used to obtain estimated completeness indices of SEER prevalence proportions for all cancer sites combined, stomach, cervix uteri, skin melanomas, non-Hodgkin's lymphomas, lung and bronchus, colon/rectum, female breast, and prostate. For validation purposes, modelled completeness indices were computed for Connecticut and compared with empirical completeness indices (the ratio of Connecticut based prevalence proportion estimates using 1973-1993 data to 1940-1993 data). The SEER-based modelled completeness indices were used to adjust SEER prevalence proportion estimates for white and black patients. RESULTS: Model validation showed that the adjusted SEER cancer prevalence proportions provided reasonably unbiased prevalence proportion estimates in general, although more complex modelling of the completeness indices is necessary for female cancers of the colon, melanoma, breast, cervix, and all cancers combined. The SEER-based cancer prevalence proportions are incomplete for most cancer sites, more so for women, whites, and at older ages. For all cancers combined, prevalence proportions tended to be higher for whites than blacks. For the site-specific cancers this was true for stomach, prostate, cervix uteri, and lung and bronchus (men only). For colon/rectal cancers the prevalence proportions were higher for blacks through ages 59 (men) and 64 (women), and then for the remaining ages they were higher for whites. Prevalence proportions were lowest for stomach cancer and highest for prostate and female breast cancers. Men experienced higher prevalence proportions than women for skin melanomas, non-Hodgkin's lymphomas, lung and bronchus, and colon/rectal cancers. CONCLUSION: The modelling approach applied to SEER data generally provided reasonable estimates of cancer prevalence. These estimates are useful because they are more representative of cancer prevalence than previously obtained and reported in the US.

Partitioning linear trends in age-adjusted rates.

OBJECTIVE: Surveillance of chronic diseases includes monitoring trends in age-adjusted rates in the general population. Statistics that are calculated to describe and compare trends include the annual percent change and the percent change for a specified time period. However, it is also of interest to determine the contribution specific diseases make to an overall trend in order to better understand the impact of interventions and changes in the prevalence of risk factors. The objective here is to provide a method for partitioning a linear trend in age-adjusted rates into disease-specific components. METHODS: The method presented is based on linear regression. The decreasing trend in age-adjusted cancer mortality rates for the total United States during the period 1991-96 is analyzed to illustrate the method. RESULTS: Trends in mortality for cancers of the colon/rectum, breast, lung/bronchus, and prostate are found to be responsible for 75% of the decreasing trend in cancer mortality. CONCLUSIONS: It is possible to partition an overall trend in age-adjusted rates under the assumption that it and the trends for all mutually exclusive and exhaustive subgroups of interest are linear.

Parametric cure models of relative and cause-specific survival for grouped survival times.

With parametric cure models, we can express survival parameters (e.g. cured fraction, location and scale parameters) as functions of covariates. These models can measure survival from a specific disease process, either by examining deaths due to the cause under study (cause-specific survival), or by comparing all deaths to those in a matched control population (relative survival). We present a binomial maximum likelihood algorithm to be used for actuarial data, where follow-up times are grouped into specific intervals. Our algorithm provides simultaneous maximum likelihood estimates for all the parameters of a cure model and can be used for cause-specific or relative survival analysis with a variety of survival distributions. Current software does not provide the flexibility of this unified approach.

Permutation tests for joinpoint regression with applications to cancer rates.

The identification of changes in the recent trend is an important issue in the analysis of cancer mortality and incidence data. We apply a joinpoint regression model to describe such continuous changes and use the grid-search method to fit the regression function with unknown joinpoints assuming constant variance and uncorrelated errors. We find the number of significant joinpoints by performing several permutation tests, each of which has a correct significance level asymptotically. Each p-value is found using Monte Carlo methods, and the overall asymptotic significance level is maintained through a Bonferroni correction. These tests are extended to the situation with non-constant variance to handle rates with Poisson variation and possibly autocorrelated errors. The performance of these tests are studied via simulations and the tests are applied to U.S. prostate cancer incidence and mortality rates.

Role of transurethral resection of the prostate in population-based prostate cancer incidence rates.

The extensive pool of asymptomatic prostate disease in the population, which increases substantially with age, suggests that the frequent use of transurethral resection of the prostate (TURP) in recent decades has had a large effect on prostate cancer incidence. The authors identified the effect of TURP-detected prostate cancer on the observed incidence rates between 1973 and 1993 for men aged 65 years and older. They linked population-based cancer registry data from the Surveillance, Epidemiology, and End Results Program to Medicare records between 1986 and 1993 to determine whether a TURP occurred sufficiently close to the time of a prostate cancer diagnosis for them to assume that it led to the diagnosis. TURP-detected cases prior to 1986 were calculated using an indirect method that involved multiplying the TURP procedure rate in the general population (from the National Hospital Discharge Survey) by estimates of the proportion of TURPs resulting in a prostate cancer diagnosis (from Medicare data and the literature). TURP explained much of the observed increase in overall prostate cancer incidence between 1973 and 1986 and possibly all of it in men aged 70 years and older. However, its influence on the trend and overall magnitude of the rates diminished between 1987 and 1993. The changing role of TURP in detecting prostate cancer is attributed to changes in medical technology and screening practices. The declining influence of TURP on prostate cancer incidence is likely to have continued beyond the study period due to the recent introduction and increasing use of medications for treating obstructive uropathy.

On the use of survival analysis techniques to estimate medical care costs.

Measurement of treatment costs is important in the evaluation of medical interventions. Accurate cost estimation is problematic, when cost records are incomplete. Methods from the survival analysis literature have been proposed for estimating costs using available data. In this article, we clarify assumptions necessary for validity of these techniques. We demonstrate how assumptions needed for valid survival analysis may be violated when these methods are applied to cost estimation. Our observations are confirmed through simulations and empirical data analysis. We conclude that survival analysis approaches are not generally appropriate for the analysis of medical costs and review several valid alternatives.

Cancer surveillance series: interpreting trends in prostate cancer--part I: Evidence of the effects of screening in recent prostate cancer incidence, mortality, and survival rates.

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.

Cancer surveillance series: interpreting trends in prostate cancer--part II: Cause of death misclassification and the recent rise and fall in prostate cancer mortality.

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.

Cancer surveillance series: interpreting trends in prostate cancer--part III: Quantifying the link between population prostate-specific antigen testing and recent declines in prostate cancer mortality.

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.

Comparison of risk estimates for selected diseases and causes of death.

BACKGROUND: Lifetime risk estimates of disease are limited by long-term data extrapolations and are less relevant to individuals who have already lived a period of time without the disease, but are approaching the age at which the disease risk becomes common. In contrast, short-term age-conditional risk estimates, such as the risk of developing a disease in the next 10 years among those alive and free of the disease at a given age, are less restricted by long-term extrapolation of current rates and can present patients with risk information tailored to their age. This study focuses on short-term age-conditional risk estimates for a broad set of important chronic diseases and nondisease causes of death among white and black men and women. METHODS: The Feuer et al. (1993, Journal of the National Cancer Institute) [15] method was applied to data from a variety of sources to obtain risk estimates for select cancers, myocardial infarction, diabetes mellitus, multiple sclerosis, Alzheimer's, and death from motor vehicle accidents, homicide or legal intervention, and suicide. RESULTS: Acute deaths from suicide, homicide or legal intervention, and fatal motor vehicle accidents dominate the risk picture for persons in their 20s, with only diabetes mellitus and end-stage renal disease therapy (for blacks only) having similar levels of risk in this age range. Late in life, cancer, acute myocardial infarction, Alzheimer's, and stroke become most common. The chronic diseases affecting the population later in life present the most likely diseases someone will face. Several interesting differences in disease and death risks were derived and reported among age-specific race and gender subgroups of the population. CONCLUSION: Presentation of risk estimates for a broad set of chronic diseases and nondisease causes of death within short-term age ranges among population subgroups provides tailored information that may lead to better educated prevention, screening, and control behaviors and more efficient allocation of health resources.

Asymptomatic incidence and duration of prostate cancer.

Prostate cancer is known as a disease with an extremely high prevalence relative to its clinical incidence in the population. The combination of preclinical incidence and duration that could yield this phenomenon is of tremendous interest to researchers trying to understand the natural history of the disease and to develop efficient screening strategies. In this article, the authors present estimates of the age-specific asymptomatic incidence and average preclinical duration of prostate cancer. The methodological approach is to first estimate the age-specific incidence of new (stage AI) prostate cancers using preclinical prevalence data from autopsy studies performed between 1941 and 1964 and clinical incidence data for the years 1960-1986 from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. Then, the preclinical prevalence estimates are divided by the derived preclinical incidence estimates to yield estimates of the average duration of asymptomatic disease. The estimated mean duration among white men is between 11 and 12 years and appears to be approximately 1 year shorter for blacks than for whites. Comparison of the lifetime risks of preclinical and clinical disease suggests that approximately 75% of prostate cancers will never become diagnosed if clinical incidence remains at levels observed in 1984-1986, prior to the introduction of prostate-specific antigen (PSA) screening in the population.

Estimating lifetime and age-conditional probabilities of developing cancer.

Lifetime and age-conditional risk estimates of developing cancer provide a useful summary to the public of the current cancer risk and how this risk compares with earlier periods and among select subgroups of society. These reported estimates, commonly quoted in the popular press, have the potential to promote early detection efforts, to increase cancer awareness, and to serve as an aid in study planning. However, they can also be easily misunderstood and frightening to the general public. The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute and the American Cancer Society have recently begun including in annual reports lifetime and age-conditional risk estimates of developing cancer. These risk estimates are based on incidence rates that reflect new cases of the cancer in a population free of the cancer. To compute these estimates involves a cancer prevalence adjustment that is computed cross-sectionally from current incidence and mortality data derived within a multiple decrement life table. This paper presents a detailed description of the methodology for deriving lifetime and age-conditional risk estimates of developing cancer. In addition, an extension is made which, using a triple decrement life table, adjusts for a surgical procedure that removes individuals from the risk of developing a given cancer. Two important results which provide insights into the basic methodology are included in the discussion. First, the lifetime risk estimate does not depend on the cancer prevalence adjustment, although this is not the case for age-conditional risk estimates. Second, the lifetime risk estimate is always smaller when it is corrected for a surgical procedure that takes people out of the risk pool to develop the cancer. The methodology is applied to corpus and uterus NOS cancers, with a correction made for hysterectomy prevalence. The interpretation and limitations of risk estimates are also discussed.

Improvement in the prognosis of breast cancer from 1965 to 1984.

PURPOSE: The prognosis of breast cancer has improved over the past three decades. It is uncertain, however, whether this improvement results from an increase in the cure rate, extension of the life span of uncured patients, or some combination. METHODS: From the Connecticut Tumor Registry, we obtained data on 25,091 patients with localized (node-negative) and regionally metastatic (node-positive) breast cancer who were diagnosed over the two decades between 1965 and 1984, with follow-up through 1993. The data for these patients were analyzed using a variety of parametric models to quantitate likelihood of cure and median survival time among uncured patients. These models incorporate the assumption that time to death from breast cancer follows a specific distribution. RESULTS: For patients with node-negative disease, parametric analysis revealed no significant difference in cured-fraction or median survival time over the two decades studied. For patients with node-positive disease, however, a significant increase in median survival time (P < .001) was found during the second decade (1970 to 1979). There was also a trend toward a higher cured-fraction over time, but this was not statistically significant. CONCLUSION: This study confirms that patients with node-positive disease had an improved prognosis over the two decades studied. Parametric analysis suggests that this improvement reflects primarily an increase in the median survival time for uncured patients, although there is a trend toward an increase in the likelihood of cure.

The role of prostate-specific antigen (PSA) testing patterns in the recent prostate cancer incidence decline in the United States.

OBJECTIVES: Trends in first-time and later PSA procedure rates are ascertained using longitudinal data from a population-based cohort. These trends are compared to trends in prostate cancer incidence to determine the role of PSA in the recent decline in prostate cancer incidence. METHODS: Medicare data were linked with tumor registry data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program. A 5 percent random sample (n = 39985) of Medicare beneficiaries from the SEER areas without a previous diagnosis of prostate cancer as of January 1, 1988 was followed through 1994. Trends in first-time PSA use were distinguished from those of second or later for men without diagnosed prostate cancer. RESULTS: Trends in the rate of first-time PSA procedures track closely with trends in prostate cancer incidence rates, increasing until 1992 and decreasing thereafter. Similar patterns were observed by race and age group. Geographic variability in the dissemination of PSA screening was observed, yet the association between testing and incidence remained. Men in the cohort had a 4.7 percent chance of being diagnosed within three months of an initial PSA test, with the percentage falling for subsequent tests. CONCLUSIONS: It is informative to distinguish first from later tests when assessing the effect of the diffusion of a test in a population. Taking this approach was useful in illuminating the role of PSA testing in a reversal of a long-term increase in prostate cancer incidence rates.