Journal of the Formosan Medical Association
Volume 107, Issue 12, Supplement , Pages S35-S42, December 2008

Statistical Methods for Targeted Clinical Trials under Enrichment Design

  • Jen-Pei Liu

      Affiliations

    • Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, Taipei, Taiwan
    • Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan, Taiwan
    • Corresponding Author InformationCorrespondence to: Dr Jen-Pei Liu, Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, 1, Section 4, Roosevelt Road, Taipei, Taiwan
    • ,
  • Jr-Rung Lin

      Affiliations

    • Division of Biometry, Graduate Institute of Agronomy, National Taiwan University, Taipei, Taiwan

Received 30 July 2008; received in revised form 17 September 2008; accepted 26 September 2008.

Article Outline

Background/Purpose

After completion of the Human Genome Project, disease targets at the molecular level can be identified. Treatment for these specific targets can be developed with the individualized treatment of patients becoming a reality. However, the accuracy of diagnostic devices for molecular targets is not perfect and statistical inference for treatment effects of the targeted therapy is biased. We developed statistical methods for an unbiased inference for the targeted therapy in patients who truly have the molecular targets.

Methods

Under the enrichment design, for binary data, we propose using the expectation maximization (EM) algorithm with the bootstrap method, to incorporate the inaccuracy of the diagnostic device for detection of the molecular targets for inference of the treatment effects. A simulation study was conducted to empirically investigate the performance of the proposed estimation and testing procedures. A numerical example illustrates the application of the proposed method.

Results

Simulation results demonstrated that the proposed estimation method was unbiased, with adequate precision, and the confidence interval provided satisfactory coverage probability. The proposed testing procedure adequately controlled the size with sufficient power. The numerical example showed that a statistically significant treatment effect could be obtained when the inaccuracy of the diagnostic device was taken into account.

Conclusion

Our proposed estimation and testing procedures are adequate statistical methods for the inference of the treatment effect for patients who truly have the molecular targets.

Key Words:  diagnostic accuracy , enrichment design , targeted treatment

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PII: S0929-6646(09)60007-3

doi:10.1016/S0929-6646(09)60007-3

Journal of the Formosan Medical Association
Volume 107, Issue 12, Supplement , Pages S35-S42, December 2008

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