Article

Projecting the number of patients with colorectal carcinoma by phases of care in the US: 2000-2020.

Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA.
Cancer Causes and Control (Impact Factor: 2.96). 01/2007; 17(10):1215-26. DOI: 10.1007/s10552-006-0072-0
Source: PubMed

ABSTRACT This study provides projections of colorectal cancer prevalence by phases of care (initial, monitoring, and last year of life) to the year 2020 and describes the estimation method.
Cancer prevalence by phase of care was estimated from colorectal cancer incidence and survival from the Surveillance, Epidemiology, and End Results (SEER) Program data, population estimates and projections from the US Census Bureau, and all cause mortality data from the Human Mortality Life Tables. Assumptions of constant incidence and survival were used for projections from 2000 to 2020. Modeled and directly observed patient months by phase of care were compared for 1996 -1998 to provide validation of estimates.
Prevalence of colorectal cancer is estimated to increase from 1,002,786 (0.36%) patients to 1,522,348 (0.46%) patients between 2000 and 2020. The estimated number of person-months in the initial and last year of life phases of care will increase 43%, while the monitoring phase of care will increase 54%. Modeled person-months by phase of care were consistent with directly observed measures of person months by phase of care in 1996-1998.
Under assumptions of current cancer control strategies we project that colorectal cancer prevalence will increase more rapidly than the US population, largely due to the aging of the US population. This suggests that considerable resources will be needed in the future for initial, continuing and last year of life treatment of colorectal cancer patients unless notable breakthroughs in primary prevention occur in the future years.

0 Bookmarks
 · 
85 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: We propose a Bayesian hierarchical model for the calculation of incidence counts from mortality data by a convolution equation that expresses mortality through its relationship with incidence and the survival probability density. The basic idea is to use mortality data together with an estimate of the survival distribution from cancer incidence to cancer mortality to reconstruct the numbers of individuals who constitute previously incident cases that give rise to the observed pattern of cancer mortality. This model is novel because it takes into account the uncertainty from the survival distribution; thus, a Bayesian-mixture cure model for survival is introduced. Furthermore, projections are obtained starting from a Bayesian age-period-cohort model. The main advantage of the proposed approach is its consideration of the three components of the model: the convolution equation, the survival mixture cure model and the age-period-cohort projection within a directed acyclic graph model. Furthermore, the estimation are obtained through the Gibbs sampler. We applied the model to cases of women with stomach cancer using six age classes [15–45], [45–55], [55–65], [65–75], [75–85] and [85–95] and validated it by using data from the Tuscany Cancer Registry. The model proposed and the program implemented are convenient because they allow different cancer disease to be analysed because the survival time is modelled by flexible distributions that are able to describe different trends. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 06/2014; · 2.04 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The number of cancer survivors continues to increase due to the aging and growth of the population and improvements in early detection and treatment. In order for the public health community to better serve these survivors, the American Cancer Society and the National Cancer Institute collaborated to estimate the number of current and future cancer survivors using data from the Surveillance, Epidemiology, and End Results (SEER) program registries. In addition, current treatment patterns for the most common cancer types are described based on information in the National Cancer Data Base and the SEER and SEER-Medicare linked databases; treatment-related side effects are also briefly described. Nearly 14.5 million Americans with a history of cancer were alive on January 1, 2014; by January 1, 2024, that number will increase to nearly 19 million. The 3 most common prevalent cancers among males are prostate cancer (43%), colorectal cancer (9%), and melanoma (8%), and those among females are cancers of the breast (41%), uterine corpus (8%), and colon and rectum (8%). The age distribution of survivors varies substantially by cancer type. For example, the majority of prostate cancer survivors (62%) are aged 70 years or older, whereas less than one-third (32%) of melanoma survivors are in this older age group. It is important for clinicians to understand the unique medical and psychosocial needs of cancer survivors and to proactively assess and manage these issues. There are a growing number of resources that can assist patients, caregivers, and health care providers in navigating the various phases of cancer survivorship. CA Cancer J Clin 2014. © 2014 American Cancer Society.
    CA A Cancer Journal for Clinicians 06/2014; · 153.46 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background: Information on the current and future numbers of Australian men living with prostate cancer is limited. We describe a method for estimating complete prevalence of prostate cancer to provide a measure of the burden of prostate cancer in Australia. Methods: Prostate cancer data from the New South Wales (NSW) Central Cancer Registry were used with PIAMOD (Prevalence and Incidence Analysis MODel) software to estimate future prostate cancer prevalence in NSW. We first fitted parametric incidence and survival models then used the modelled incidence and survival estimates to calculate complete prevalence. The estimated and projected prevalence incorporate past observed trends and take into account different assumptions about future survival trends. These models were validated against observed prevalence from the counting method. Results: Based on data for 1996–2007, the number of men living with prostate cancer in NSW was estimated to rise by 59% to 73%, from 38,322 in 2007 to 60,910–66,160 in 2017. The increasing incidence rates and the ageing population were the major contributors to this estimated increase. Validation suggested that these projections were reasonable, as the estimated prevalence in 1996–2007 was in good agreement with the corresponding prevalence calculated using the direct counting method, and the incidence models were supported by the recent data on prostate-specific antigen testing. Conclusions: As the number of men living with prostate cancer is expected to increase dramatically in the next decade in Australia, representing a significant challenge to the health system, careful planning and development of a healthcare system able to respond to this increased demand is required. These projections are useful for addressing the challenge in meeting the cancer care needs of men with prostate cancer.
    Cancer Epidemiology 12/2014; 39(1). · 2.56 Impact Factor