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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
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    References listed on IDEAS

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    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.
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