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On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials

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DOI: 10.4236/ojs.2013.34A005    3,350 Downloads   4,642 Views  

ABSTRACT

Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

S. Brummel and D. Gillen, "On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials," Open Journal of Statistics, Vol. 3 No. 4A, 2013, pp. 41-54. doi: 10.4236/ojs.2013.34A005.

References

[1] B. D. Cheston, et al., “National Cancer Institute-Sponsored Working Group Guidelines for Chronic Lymphocytic Leuemia: Revised Guidelines for Diagnosis and Treatment,” Blood, Vol. 87, No. 12, 1996, pp. 4990-4997.
[2] L. E. Dodd, et al., “Blinded Independent Central Review of Progression-Free Survival in Phase III Clinical Trials: Important Design Element or Unnecessary Expense?” Journal of Clinical Oncology, Vol. 26, No. 22, 2008, pp. 3791-3796. doi:10.1200/JCO.2008.16.1711
[3] S. S. Emerson, J. M. Kittelson and D. L. Gillen, “Frequentist Evaluation of Group Sequential Designs,” Statistics in Medicine, Vol. 26, No. 28, 2007, pp. 5047-5080. doi:10.1002/sim.2901
[4] D. L. Demets and G. K. K. Lan, “An Overview of Sequential Methods and Their Application in Clinical Trials,” Communications in Statistics-Theory and Methods, Vol. 13, No. 19, 1984, pp. 2315-2338. doi:10.1080/03610928408828829
[5] B. E. Burington and S. S. Emerson, “Flexible Implementations of Group Sequential Stopping Rules Using Constrained Boundaries,” Biometrics, Vol. 59, No. 4, 2003, pp. 770777. doi:/10.1111/j.0006-341X.2003.00090.x
[6] R. Ford, et al., “Lessons Learned from Independent Central Review,” European Journal of Cancer, Vol. 45, No. 2, 2009, pp. 268-274. doi:/10.1016/j.ejca.2008.10.031
[7] S. J. Pocock, “Group Sequential Methods in the Design and Analysis of Clinical Trials,” Biometrika, Vol. 64, No. 2, 1997, pp. 191-199. doi:10.1093/biomet/64.2.191
[8] P. C. O’Brien and T. R. Fleming, “A multiple Testing Procedure for Clinical Trials,” Biometrics, Vol. 35, No. 3, 1979, pp. 549-556. doi:10.2307/2530245
[9] G. K. K. Lan and D. L. DeMets, “Discrete Sequential Boundaries for Clinical Trials,” Biometrika, Vol. 70, No. 3, 1983, pp. 659-663. doi:10.2307/2336502
[10] S. Pampallona, A. A. Tsiatis and K. Kim, “Spending Functions for Type I and Type II Error Probabilities,” Technical Report, Harvard School of Public Health, Deptartment of Biostatistics, Boston, 1995 (unpublished).
[11] A. P. Dempster, N. M. Laird and D. B. Rubin, “Maximum Likelihood from Incomplete Data via the EM Algorithm,” Journal of the Royal Statistical Society, Vol. 39, No. 1, 1977, pp. 1-38.
[12] D. B. Rubin, “Inference and Missing Data,” Biometrica Trust, Vol. 63, No. 3, 1976, pp. 581-592. doi:/10.1093/biomet/63.3.581.

  
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