IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0025141.html
   My bibliography  Save this article

Estimation of Recurrence of Colorectal Adenomas with Dependent Censoring Using Weighted Logistic Regression

Author

Listed:
  • Chiu-Hsieh Hsu
  • Yisheng Li
  • Qi Long
  • Qiuhong Zhao
  • Peter Lance

Abstract

In colorectal polyp prevention trials, estimation of the rate of recurrence of adenomas at the end of the trial may be complicated by dependent censoring, that is, time to follow-up colonoscopy and dropout may be dependent on time to recurrence. Assuming that the auxiliary variables capture the dependence between recurrence and censoring times, we propose to fit two working models with the auxiliary variables as covariates to define risk groups and then extend an existing weighted logistic regression method for independent censoring to each risk group to accommodate potential dependent censoring. In a simulation study, we show that the proposed method results in both a gain in efficiency and reduction in bias for estimating the recurrence rate. We illustrate the methodology by analyzing a recurrent adenoma dataset from a colorectal polyp prevention trial.

Suggested Citation

  • Chiu-Hsieh Hsu & Yisheng Li & Qi Long & Qiuhong Zhao & Peter Lance, 2011. "Estimation of Recurrence of Colorectal Adenomas with Dependent Censoring Using Weighted Logistic Regression," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-8, October.
    • Handle: RePEc:plo:pone00:0025141
    DOI: 10.1371/journal.pone.0025141
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0025141
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0025141&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0025141?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. Richard Peto, 1973. "Experimental Survival Curves for Interval‐Censored Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 22(1), pages 86-91, March.
    Full references (including those not matched with items on IDEAS)

    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. Faustino Prieto & Jos'e Mar'ia Sarabia & Enrique Calder'in-Ojeda, 2020. "The risk of death in newborn businesses during the first years in market," Papers 2011.11776, arXiv.org.
    2. Meei Pyng Ng, 2002. "A Modification of Peto's Nonparametric Estimation of Survival Curves for Interval-Censored Data," Biometrics, The International Biometric Society, vol. 58(2), pages 439-442, June.
    3. Wang, Tong & Jin, Hailong & Sieverding, Heidi & Kumar, Sandeep & Miao, Yuxin & Rao, Xudong & Obembe, Oladipo & Mirzakhani Nafchi, Ali & Redfearn, Daren & Cheye, Stephen, 2023. "Understanding farmer views of precision agriculture profitability in the U.S. Midwest," Ecological Economics, Elsevier, vol. 213(C).
    4. Enrico A. Colosimo & Liciana V. A. S. Chalita & Clarice G. B. Demétrio, 2000. "Tests of Proportional Hazards and Proportional Odds Models for Grouped Survival Data," Biometrics, The International Biometric Society, vol. 56(4), pages 1233-1240, December.
    5. Kenichi Hayashi & Yasutaka Shimizu, 2018. "Estimation of a Concordance Probability for Doubly Censored Time-to-Event Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 546-567, December.
    6. C. P. Farrington, 2000. "Residuals for Proportional Hazards Models with Interval-Censored Survival Data," Biometrics, The International Biometric Society, vol. 56(2), pages 473-482, June.
    7. Peter Bacchetti & Christopher Quale, 2002. "Generalized Additive Models with Interval-Censored Data and Time-Varying Covariates: Application to Human Immunodeficiency Virus Infection in Hemophiliacs," Biometrics, The International Biometric Society, vol. 58(2), pages 443-447, June.
    8. Angel G. Angelov & Magnus Ekström, 2019. "Maximum likelihood estimation for survey data with informative interval censoring," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 217-236, June.
    9. Pao-Sheng Shen, 2020. "Nonparametric estimators of survival function under the mixed case interval-censored model with left truncation," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 624-637, July.
    10. Dianne M. Finkelstein & William B. Goggins & David A. Schoenfeld, 2002. "Analysis of Failure Time Data with Dependent Interval Censoring," Biometrics, The International Biometric Society, vol. 58(2), pages 298-304, June.
    11. Wei Pan, 2000. "A Multiple Imputation Approach to Cox Regression with Interval-Censored Data," Biometrics, The International Biometric Society, vol. 56(1), pages 199-203, March.

    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:plo:pone00:0025141. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.