IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v12y2012i4p623-638.html
   My bibliography  Save this article

Fitting and modeling cure in population-based cancer studies within the framework of flexible parametric survival models

Author

Listed:
  • Therese M.-L. Andersson

    (Karolinska Institutet)

  • Paul C. Lambert

    (University of Leicester
    Karolinska Institutet)

Abstract

When the mortality among a cancer patient group returns to the same level as in the general population, that is, when the patients no longer experi- ence excess mortality, the patients still alive are considered “statistically cured”. Cure models can be used to estimate the cure proportion as well as the survival function of the “uncured”. One limitation of parametric cure models is that the functional form of the survival of the uncured has to be specified. It can some- times be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagno- sis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Here we use flexible parametric survival models that incorporate cure as a special case to estimate the cure proportion and the survival of the uncured. Flexible parametric survival models use splines to model the underlying hazard function; therefore, no parametric distribution has to be specified. We have updated the stpm2 command for flexible parametric models to enable cure modeling.

Suggested Citation

  • Therese M.-L. Andersson & Paul C. Lambert, 2012. "Fitting and modeling cure in population-based cancer studies within the framework of flexible parametric survival models," Stata Journal, StataCorp LP, vol. 12(4), pages 623-638, December.
    • Handle: RePEc:tsj:stataj:v:12:y:2012:i:4:p:623-638
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj12-4/st0165_1/
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0165_1
    File Function: link to article download
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. P. C. Lambert & P. W. Dickman & C. L. Weston & J. R. Thompson, 2010. "Estimating the cure fraction in population‐based cancer studies by using finite mixture models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 35-55, January.
    2. Patrick Royston, 2001. "Flexible alternatives to the Cox model, and more," Stata Journal, StataCorp LP, vol. 1(1), pages 1-28, November.
    3. Paul C. Lambert & Patrick Royston, 2009. "Further development of flexible parametric models for survival analysis," Stata Journal, StataCorp LP, vol. 9(2), pages 265-290, June.
    4. Paul C. Lambert, 2007. "Modeling of the cure fraction in survival studies," Stata Journal, StataCorp LP, vol. 7(3), pages 351-375, September.
    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. Sun, Ruohan & Zhou, Nan & Zhang, Bing, 2023. "Can bank branch establishment help SMEs survive? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 88(C).

    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. Enzo Coviello, 2009. "Covariate-adjusted cumulative incidence in the presence of competing risks," Italian Stata Users' Group Meetings 2009 02, Stata Users Group.
    2. Amin Moniri-Morad & Mohammad Pourgol-Mohammad & Hamid Aghababaei & Javad Sattarvand, 2019. "Reliability-based covariate analysis for complex systems in heterogeneous environment: Case study of mining equipment," Journal of Risk and Reliability, , vol. 233(4), pages 593-604, August.
    3. Sambit Bhattacharyya & Michael Keller, 2021. "Resource Discovery and the Political Fortunes of National Leaders," Economica, London School of Economics and Political Science, vol. 88(349), pages 129-166, January.
    4. Erin E. Gabriel & Michael C. Sachs & Dean A. Follmann & Therese M‐L. Andersson, 2020. "A unified evaluation of differential vaccine efficacy," Biometrics, The International Biometric Society, vol. 76(4), pages 1053-1063, December.
    5. Patrick Royston, 2012. "Tools to simulate realistic censored survival-time distributions," Stata Journal, StataCorp LP, vol. 12(4), pages 639-654, December.
    6. Noori Akhtar-Danesh, 2015. "A Comparison of Modeling Scales in Flexible Parametric Models," 2015 Stata Conference 15, Stata Users Group.
    7. Ewa Cukrowska-Torzewska & Magdalena Grabowska, 2023. "The sex preference for children in Europe: Children’s sex and the probability and timing of births," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(8), pages 203-232.
    8. Joshua S Davis & Vincent He & Nicholas M Anstey & John R Condon, 2014. "Long Term Outcomes Following Hospital Admission for Sepsis Using Relative Survival Analysis: A Prospective Cohort Study of 1,092 Patients with 5 Year Follow Up," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-14, December.
    9. Martin Gaksch & Rolf Jorde & Guri Grimnes & Ragnar Joakimsen & Henrik Schirmer & Tom Wilsgaard & Ellisiv B Mathiesen & Inger Njølstad & Maja-Lisa Løchen & Winfried März & Marcus E Kleber & Andreas Tom, 2017. "Vitamin D and mortality: Individual participant data meta-analysis of standardized 25-hydroxyvitamin D in 26916 individuals from a European consortium," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-15, February.
    10. Patrick Royston, 2007. "Profile likelihood for estimation and confidence intervals," Stata Journal, StataCorp LP, vol. 7(3), pages 376-387, September.
    11. Herrera Dappe,Matias & Melecky,Martin & Turkgulu,Burak, 2022. "Fiscal Risks from Early Termination of Public-Private Partnerships in Infrastructure," Policy Research Working Paper Series 9972, The World Bank.
    12. Li-Jen Liao & Hsu-Wen Chou & Chi-Te Wang & Chen-Shuan Chung & Mei-Shu Lai, 2013. "The Impact of Second Primary Malignancies on Head and Neck Cancer Survivors: A Nationwide Cohort Study," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-6, April.
    13. Michael J. Crowther & Keith R. Abrams & Paul C. Lambert, 2013. "Joint modeling of longitudinal and survival data," Stata Journal, StataCorp LP, vol. 13(1), pages 165-184, March.
    14. Ghanbariamin, Roksana & Chung, Bobby W., 2020. "The effect of the National Kidney Registry on the kidney-exchange market," Journal of Health Economics, Elsevier, vol. 70(C).
    15. Tien Vu, 2014. "One male offspring preference: evidence from Vietnam using a split-population model," Review of Economics of the Household, Springer, vol. 12(4), pages 689-715, December.
    16. Jonathan Karnon & Orla Caffrey & Clarabelle Pham & Richard Grieve & David Ben‐Tovim & Paul Hakendorf & Maria Crotty, 2013. "Applying Risk Adjusted Cost‐Effectiveness (Rac‐E) Analysis To Hospitals: Estimating The Costs And Consequences Of Variation In Clinical Practice," Health Economics, John Wiley & Sons, Ltd., vol. 22(6), pages 631-642, June.
    17. Nan Liu, 2021. "Market buoyancy, information transparency and pricing strategy in the Scottish housing market," Urban Studies, Urban Studies Journal Limited, vol. 58(16), pages 3388-3406, December.
    18. Márton Varga, 2014. "The effect of education, family size, unemployment and childcare availability on birth stopping and timing," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 13(2), pages 95-115, August.
    19. Patricia Guyot & Anthony E. Ades & Matthew Beasley & Béranger Lueza & Jean-Pierre Pignon & Nicky J. Welton, 2017. "Extrapolation of Survival Curves from Cancer Trials Using External Information," Medical Decision Making, , vol. 37(4), pages 353-366, May.
    20. Eddie Gibson & Ian Koblbauer & Najida Begum & George Dranitsaris & Danny Liew & Phil McEwan & Amir Abbas Tahami Monfared & Yong Yuan & Ariadna Juarez-Garcia & David Tyas & Michael Lees, 2017. "Modelling the Survival Outcomes of Immuno-Oncology Drugs in Economic Evaluations: A Systematic Approach to Data Analysis and Extrapolation," PharmacoEconomics, Springer, vol. 35(12), pages 1257-1270, December.

    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:tsj:stataj:v:12:y:2012:i:4:p:623-638. 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: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    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.