IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v33y1984i2p176-195.html
   My bibliography  Save this article

Regression Models and Non‐Proportional Hazards in the Analysis of Breast Cancer Survival

Author

Listed:
  • Sheila M. Gore
  • Stuart J. Pocock
  • Gillian R. Kerr

Abstract

The Western General breast cancer series of 3922 patients sets research methodology for survival data in practical perspective and illustrates that the waning of covariate effects through time is an important phenomenon in medical applications. Non‐monotone convergent hazard functions are associated with most clinical covariates in breast cancer; an unusual hazard pattern according to menopausal state is also reported. These features contraindicate the use of standard regression models for survival such as Weibull and proportional hazards. Inferences about covariate effects are compared under these and a log‐logistic model which implies proportionality of the cumulative odds on death. Regression models are shown to be useful in exploratory analysis. In particular, a step‐function proportional hazards model elucidates the time‐dependent influence of initial covariates and leads to a more appropriate final model, but one whose virtues are balanced by computational difficulty.

Suggested Citation

  • Sheila M. Gore & Stuart J. Pocock & Gillian R. Kerr, 1984. "Regression Models and Non‐Proportional Hazards in the Analysis of Breast Cancer Survival," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(2), pages 176-195, June.
    • Handle: RePEc:bla:jorssc:v:33:y:1984:i:2:p:176-195
    DOI: 10.2307/2347444
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2347444
    Download Restriction: no
    File URL: https://libkey.io/10.2307/2347444?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
    ---><---

    Citations

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


    Cited by:

    1. Devarajan, Karthik & Ebrahimi, Nader, 2011. "A semi-parametric generalization of the Cox proportional hazards regression model: Inference and applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 667-676, January.
    2. D. Stogiannis & C. Caroni & C. E. Anagnostopoulos & I. K. Toumpoulis, 2011. "Comparing first hitting time and proportional hazards regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1483-1492, June.
    3. Ofosu, Yaw., 1993. "Socio-economic change and evolution of cultural models of reproduction in Ghana: implications for population policy," ILO Working Papers 992920673402676, International Labour Organization.
    4. Gupta, Ramesh C. & Gupta, Pushpa L., 2000. "On the crossings of reliability measures," Statistics & Probability Letters, Elsevier, vol. 46(3), pages 301-305, February.
    5. Qin, Fei, 2015. "Global talent, local careers: Circular migration of top Indian engineers and professionals," Research Policy, Elsevier, vol. 44(2), pages 405-420.
    6. Congdon, Peter, 2008. "A bivariate frailty model for events with a permanent survivor fraction and non-monotonic hazards; with an application to age at first maternity," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4346-4356, May.
    7. Chengyuan Lu & Jelle Goeman & Hein Putter, 2023. "Maximum likelihood estimation in the additive hazards model," Biometrics, The International Biometric Society, vol. 79(3), pages 1646-1656, September.
    8. Ian W. McKeague & Mourad Tighiouart, 2000. "Bayesian Estimators for Conditional Hazard Functions," Biometrics, The International Biometric Society, vol. 56(4), pages 1007-1015, December.
    9. repec:ilo:ilowps:292067 is not listed on IDEAS

    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:jorssc:v:33:y:1984:i:2:p:176-195. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.