IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v168y2005i4p657-677.html
   My bibliography  Save this article

A review of cancer screening evaluation techniques, with some particular examples in breast cancer screening

Author

Listed:
  • Jane Warwick
  • Stephen W. Duffy

Abstract

Summary. The instigation of mass screening for breast cancer has, over the last three decades, raised various statistical issues and led to the development of new statistical approaches. Initially, the design of screening trials was the main focus of research but, as the evidence in favour of population‐based screening programmes mounts, a variety of other applications have also been identified. These include administrative and quality control tasks, for monitoring routine screening services, as well as epidemiological modelling of incidence and mortality. We review the commonly used methods of cancer screening evaluation, highlight some current issues in breast screening and, using examples from randomized trials and established screening programmes, illustrate the role that statistical science has played in the development of clinical research in this field.

Suggested Citation

  • Jane Warwick & Stephen W. Duffy, 2005. "A review of cancer screening evaluation techniques, with some particular examples in breast cancer screening," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 657-677, November.
  • Handle: RePEc:bla:jorssa:v:168:y:2005:i:4:p:657-677
    DOI: 10.1111/j.1467-985X.2005.00371.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-985X.2005.00371.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1467-985X.2005.00371.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tony H. H. Chen & H. S. Kuo & M. F. Yen & M. S. Lai & L. Tabar & S. W. Duffy, 2000. "Estimation of Sojourn Time in Chronic Disease Screening Without Data on Interval Cases," Biometrics, The International Biometric Society, vol. 56(1), pages 167-172, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sungwook Yoon & Duk Bin Jun & Sungho Park, 2020. "The effect of general health checks on healthcare utilization: accounting for self‐selection bias," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 3-36, January.
    2. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi‐Ying Wu & Ming‐Fang Yen & Cheng‐Ping Yu & Hsiu‐Hsi Chen, 2014. "Risk Assessment of Multistate Progression of Breast Tumor with State‐Dependent Genetic and Environmental Covariates," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 367-379, February.
    2. Yen, Amy Ming-Fang & Chen, Hsiu-Hsi, 2013. "Stochastic models for multiple pathways of temporal natural history on co-morbidity of chronic disease," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 570-588.
    3. Paul S. Albert & Joanna H. Shih, 2003. "Modeling Tumor Growth with Random Onset," Biometrics, The International Biometric Society, vol. 59(4), pages 897-906, December.
    4. Paul F. Pinsky, 2004. "An Early- and Late-Stage Convolution Model for Disease Natural History," Biometrics, The International Biometric Society, vol. 60(1), pages 191-198, March.
    5. Hsiu-Hsi Chen & Amy Ming-Fang Yen & Laszlo Tabár, 2012. "A Stochastic Model for Calibrating the Survival Benefit of Screen-Detected Cancers," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1339-1359, December.
    6. Rui Chen & Menggang Yu, 2021. "Tailored optimal posttreatment surveillance for cancer recurrence," Biometrics, The International Biometric Society, vol. 77(3), pages 942-955, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssa:v:168:y:2005:i:4:p:657-677. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.