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Combining Censored and Uncensored Data in a U-Statistic: Design and Sample Size Implications for Cell Therapy Research

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Listed:
  • Moyé Lemuel A
  • Lai Dejian
  • Jing Kaiyan
  • Baraniuk Mary Sarah
  • Kwak Minjung
  • Penn Marc S.
  • Wu Colon O.

Abstract

The assumptions that anchor large clinical trials are rooted in smaller, Phase II studies. In addition to specifying the target population, intervention delivery, and patient follow-up duration, physician-scientists who design these Phase II studies must select the appropriate response variables (endpoints). However, endpoint measures can be problematic. If the endpoint assesses the change in a continuous measure over time, then the occurrence of an intervening significant clinical event (SCE), such as death, can preclude the follow-up measurement. Finally, the ideal continuous endpoint measurement may be contraindicated in a fraction of the study patients, a change that requires a less precise substitution in this subset of participants.A score function that is based on the U-statistic can address these issues of 1) intercurrent SCE’s and 2) response variable ascertainments that use different measurements of different precision. The scoring statistic is easy to apply, clinically relevant, and provides flexibility for the investigators’ prospective design decisions. Sample size and power formulations for this statistic are provided as functions of clinical event rates and effect size estimates that are easy for investigators to identify and discuss. Examples are provided from current cardiovascular cell therapy research.

Suggested Citation

  • Moyé Lemuel A & Lai Dejian & Jing Kaiyan & Baraniuk Mary Sarah & Kwak Minjung & Penn Marc S. & Wu Colon O., 2011. "Combining Censored and Uncensored Data in a U-Statistic: Design and Sample Size Implications for Cell Therapy Research," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-29, July.
    • Handle: RePEc:bpj:ijbist:v:7:y:2011:i:1:n:29
    DOI: 10.2202/1557-4679.1286
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    References listed on IDEAS

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    1. Dei-In Tang & Nancy L. Geller, 1999. "Closed Testing Procedures for Group Sequential Clinical Trials with Multiple Endpoints," Biometrics, The International Biometric Society, vol. 55(4), pages 1188-1192, December.
    2. Ming Tan & Hong-Bin Fang & Guo-Liang Tian & Peter J. Houghton, 2002. "Small-Sample Inference for Incomplete Longitudinal Data with Truncation and Censoring in Tumor Xenograft Models," Biometrics, The International Biometric Society, vol. 58(3), pages 612-620, September.
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