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An Approach to Evaluating and Comparing Biomarkers for Patient Treatment Selection

Author

Listed:
  • Janes Holly

    (Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N M2 C200, Seattle, WA 98109, USA)

  • Brown Marshall D.

    (Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N M2 C200, Seattle, WA 98109, USA)

  • Huang Ying

    (Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N M2 C200, Seattle, WA 98109, USA)

  • Pepe Margaret S.

    (Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N M2 B500, Seattle, WA 98109, USA University of Washington, Seattle, WA, USA)

Abstract

Despite the heightened interest in developing biomarkers predicting treatment response that are used to optimize patient treatment decisions, there has been relatively little development of statistical methodology to evaluate these markers. There is currently no unified statistical framework for marker evaluation. This paper proposes a suite of descriptive and inferential methods designed to evaluate individual markers and to compare candidate markers. An R software package has been developed which implements these methods. Their utility is illustrated in the breast cancer treatment context, where candidate markers are evaluated for their ability to identify a subset of women who do not benefit from adjuvant chemotherapy and can therefore avoid its toxicity.

Suggested Citation

  • Janes Holly & Brown Marshall D. & Huang Ying & Pepe Margaret S., 2014. "An Approach to Evaluating and Comparing Biomarkers for Patient Treatment Selection," The International Journal of Biostatistics, De Gruyter, vol. 10(1), pages 99-121, May.
    • Handle: RePEc:bpj:ijbist:v:10:y:2014:i:1:p:23:n:4
    DOI: 10.1515/ijb-2012-0052
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    References listed on IDEAS

    as
    1. Baqun Zhang & Anastasios A. Tsiatis & Eric B. Laber & Marie Davidian, 2012. "A Robust Method for Estimating Optimal Treatment Regimes," Biometrics, The International Biometric Society, vol. 68(4), pages 1010-1018, December.
    2. Ying Huang & Margaret Sullivan Pepe & Ziding Feng, 2007. "Evaluating the Predictiveness of a Continuous Marker," Biometrics, The International Biometric Society, vol. 63(4), pages 1181-1188, December.
    3. Xiao Song & Margaret Pepe, 2004. "Evaluating Markers for Selecting a Patient's Treatment," UW Biostatistics Working Paper Series 1029, Berkeley Electronic Press.
    4. Stuart G. Baker & Barnett S. Kramer, 2005. "Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 941-954, November.
    5. Ying Huang & Peter B. Gilbert & Holly Janes, 2012. "Assessing Treatment-Selection Markers using a Potential Outcomes Framework," Biometrics, The International Biometric Society, vol. 68(3), pages 687-696, September.
    6. Xiao Song & Margaret Sullivan Pepe, 2004. "Evaluating Markers for Selecting a Patient's Treatment," Biometrics, The International Biometric Society, vol. 60(4), pages 874-883, December.
    Full references (including those not matched with items on IDEAS)

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