IDEAS home Printed from https://ideas.repec.org/a/spr/stabio/v15y2023i1d10.1007_s12561-022-09349-3.html
   My bibliography  Save this article

Using Controlled Feeding Study for Biomarker Development in Regression Calibration for Disease Association Estimation

Author

Listed:
  • Cheng Zheng

    (University of Nebraska Medical Center)

  • Yiwen Zhang

    (University of Wisconsin-Milwaukee)

  • Ying Huang

    (Fred Hutchinson Cancer Research Center)

  • Ross Prentice

    (Fred Hutchinson Cancer Research Center)

Abstract

Correction for systematic measurement error in self-reported data is an important challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been used for this purpose when an objectively measured biomarker is available. However, a big limitation of the regression calibration method is that biomarkers have only been developed for a few dietary components. We propose new methods to use controlled feeding studies to develop valid biomarkers for many more dietary components and to estimate the diet disease associations. Asymptotic distribution theory for the proposed estimators is derived. Extensive simulation is performed to study the finite sample performance of the proposed estimators. We applied our method to examine the associations between the sodium/potassium intake ratio and cardiovascular disease incidence using the Women’s Health Initiative cohort data. We discovered positive associations between sodium/potassium ratio and the risks of coronary heart disease, nonfatal myocardial infarction, coronary death, ischemic stroke, and total cardiovascular disease.

Suggested Citation

  • Cheng Zheng & Yiwen Zhang & Ying Huang & Ross Prentice, 2023. "Using Controlled Feeding Study for Biomarker Development in Regression Calibration for Disease Association Estimation," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 57-113, April.
    • Handle: RePEc:spr:stabio:v:15:y:2023:i:1:d:10.1007_s12561-022-09349-3
    DOI: 10.1007/s12561-022-09349-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12561-022-09349-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12561-022-09349-3?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiao Song & Yijian Huang, 2005. "On Corrected Score Approach for Proportional Hazards Model with Covariate Measurement Error," Biometrics, The International Biometric Society, vol. 61(3), pages 702-714, September.
    2. Zucker, David M., 2005. "A PseudoPartial Likelihood Method for Semiparametric Survival Regression With Covariate Errors," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1264-1277, December.
    3. Ross L. Prentice & Ying Huang, 2018. "Nutritional epidemiology methods and related statistical challenges and opportunities," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 2(1), pages 2-10, January.
    4. Chengcheng Hu & D. Y. Lin, 2002. "Cox Regression with Covariate Measurement Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(4), pages 637-655, December.
    5. Pamela A. Shaw & Ross L. Prentice, 2012. "Hazard Ratio Estimation for Biomarker-Calibrated Dietary Exposures," Biometrics, The International Biometric Society, vol. 68(2), pages 397-407, June.
    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. Li-Pang Chen & Grace Y. Yi, 2021. "Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 481-517, June.
    2. Yanqing Sun & Qingning Zhou & Peter B. Gilbert, 2023. "Analysis of the Cox Model with Longitudinal Covariates with Measurement Errors and Partly Interval Censored Failure Times, with Application to an AIDS Clinical Trial," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(2), pages 430-454, July.
    3. Pamela A. Shaw & Ross L. Prentice, 2012. "Hazard Ratio Estimation for Biomarker-Calibrated Dietary Exposures," Biometrics, The International Biometric Society, vol. 68(2), pages 397-407, June.
    4. Chi-Chung Wen, 2010. "Semiparametric maximum likelihood estimation in Cox proportional hazards model with covariate measurement errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 72(2), pages 199-217, September.
    5. Torben Martinussen & Klaus K. Holst & Thomas H. Scheike, 2016. "Cox regression with missing covariate data using a modified partial likelihood method," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(4), pages 570-588, October.
    6. Yi Li & Louise Ryan, 2004. "Survival Analysis With Heterogeneous Covariate Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 724-735, January.
    7. Menggang Yu & Bin Nan, 2010. "Regression Calibration in Semiparametric Accelerated Failure Time Models," Biometrics, The International Biometric Society, vol. 66(2), pages 405-414, June.
    8. Yih-Huei Huang & Chi-Chung Wen & Yu-Hua Hsu, 2015. "The Extensively Corrected Score for Measurement Error Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 911-924, December.
    9. Chen, Yurong & Feng, Yanqin & Sun, Jianguo, 2015. "Regression analysis of multivariate current status data with auxiliary covariates under the additive hazards model," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 34-45.
    10. Yanyan Liu & Haibo Zhou & Jianwen Cai, 2009. "Estimated Pseudopartial-Likelihood Method for Correlated Failure Time Data with Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 65(4), pages 1184-1193, December.
    11. Yuhang Xu & Yehua Li & Xiao Song, 2016. "Locally Efficient Semiparametric Estimators for Proportional Hazards Models with Measurement Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 558-572, June.
    12. Li‐Pang Chen & Grace Y. Yi, 2021. "Analysis of noisy survival data with graphical proportional hazards measurement error models," Biometrics, The International Biometric Society, vol. 77(3), pages 956-969, September.
    13. Thomas H. Scheike & Torben Martinussen & Jeremy D. Silver, 2010. "Estimating Haplotype Effects for Survival Data," Biometrics, The International Biometric Society, vol. 66(3), pages 705-715, September.
    14. Xiaomei Liao & David M. Zucker & Yi Li & Donna Spiegelman, 2011. "Survival Analysis with Error-Prone Time-Varying Covariates: A Risk Set Calibration Approach," Biometrics, The International Biometric Society, vol. 67(1), pages 50-58, March.
    15. Yu-Jen Cheng & Mei-Cheng Wang, 2015. "Causal estimation using semiparametric transformation models under prevalent sampling," Biometrics, The International Biometric Society, vol. 71(2), pages 302-312, June.
    16. Frank Eriksson & Thomas Scheike, 2015. "Additive gamma frailty models with applications to competing risks in related individuals," Biometrics, The International Biometric Society, vol. 71(3), pages 677-686, September.
    17. Yanqin Feng & Ling Ma & Jianguo Sun, 2015. "Regression Analysis of Current Status Data Under the Additive Hazards Model with Auxiliary Covariates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 118-136, March.
    18. Ying Yan & Grace Y. Yi, 2016. "A Class of Functional Methods for Error-Contaminated Survival Data Under Additive Hazards Models with Replicate Measurements," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 684-695, April.
    19. Yuxue Jin & Tze Leung Lai, 2017. "A new approach to regression analysis of censored competing-risks data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 605-625, October.
    20. Xiao Song & C. Y. Wang, 2008. "Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients," Biometrics, The International Biometric Society, vol. 64(2), pages 557-566, June.

    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:spr:stabio:v:15:y:2023:i:1:d:10.1007_s12561-022-09349-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.