Statistical issues on the diagnostic multivariate index assay for targeted clinical trials

Journal of Biopharmaceutical Statistics

Volumn 18, Issue 1, 2008, Pages 167-182

  Liu, Jen Pei ^a,b   Chow, Shein Chung ^c  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b NATIONAL HEALTH RESEARCH INSTITUTES   (Taiwan)

^c DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Genomic composite biomarker classifier; Multivariate index assay; Pharmacogenomics; Targeted clinical trials

Indexed keywords

BIOLOGICAL MARKER;

ALGORITHM; ARTICLE; CLINICAL STUDY; CLINICAL TRIAL; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST; DIAGNOSTIC VALUE; GENE EXPRESSION; GENE TARGETING; HUMAN; IN VITRO DIAGNOSTIC MULTIVARIATE INDEX ASSAY; IN VITRO STUDY; MULTIVARIATE ANALYSIS; POPULATION RESEARCH; PRIORITY JOURNAL; SAMPLE SIZE; STATISTICAL ANALYSIS;

CLINICAL TRIALS AS TOPIC; HUMANS; MULTIVARIATE ANALYSIS; REPRODUCIBILITY OF RESULTS;

EID: 37549027260     PISSN: 10543406     EISSN: 15205711     Source Type: Journal    
DOI: 10.1080/10543400701668316     Document Type: Article

References (44)

1. Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of Royal Statistical Society, Series B 57:289-300.
2. Canales, R. D., Luo, Y., Willey, J. C., et al. (2006). Evaluation of DNA microarray results with quantitative gene expression platforms. Nature Biotechnology 24:1115-1122.
3. Casciano, D. A., Woodcock, J. (2006). Empowering microarrays in the regulatory setting. Nature Biotechnology 24:1103.
4. Chow, S. C., Liu, J. P. (2004). Design and Analysis of Clinical Trials. New York: John Wiley and Sons.
5. Dalton, W. S., Friend, S. H. (2006). Cancer Biomarkers - an invitation to the table. Science 312:1165-1168.
6. Dempster, A. P., Laird, N. M., Rubin, D. B. (1997). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society 39:1-38.
7. Dobbin, K. K., Beer, D. G., Meyerson, M., Yeatman, T. J., Gerald, W. L., Jacobson, J. W., et al. (2005). Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays. Clinical Cancer Research 11:565-573.
8. Dudoit, S., Yang, Y. H., Callow, M. J., Speed, T. P. (2002). Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Statistica Sinica 12:111-139.
9. FDA (2003). Draft Guidance on Multiplex Tests for Heritable DNA Markers, Mutations and Expression Patterns. The U.S. Food and Drug Administration. Rockville, Maryland.
10. FDA (2005). Draft concept paper on Drug-Diagnostic Co-Development. The U.S. Food and Drug Administration. Rockville, Maryland.
11. FDA (2006). Draft Guidance on In Vitro Diagnostic Multivariate Index Assays. The U.S. Food and Drug Administration. Rockville, Maryland.
12. Frueh, F. W. (2006). Impact of microarray data quality on genomic data submissions to the FDA. Nature Biotechnology 24:1105-1107.
13. Gelfand, A. E., Smith, A. F. M. (1990). Sampling-based approaches to calculating densities. Journal of the American Statistical Association 85:398-409.
14. Hochberg, Y., Tamhane, A. C. (1987). Multiple Comparison Procedures. New York: Wiley.
15. Irizarry, R. A., Warren, D., Spencer, F., Kim, I. F., Biswal, S., Frank, B. C., et al. (2005). Multi-laboratory comparison of microarray platforms. Nature Methods 2:345-349.
16. Ji, H., Davis, R. W. (2006). Data quality in genomics and microarray. Nature Biotechnology 24:1112-1113.
17. Larkin, J. E., Frank, B. C., Gavras, H., Sultana, R., Quackenbush, J. (2005). Independence and reproducibility across microarray platforms. Nature Methods 2:337-343.
18. Li, C. R., Liao, C. T., Liu, J. P. (2006). On the exact interval estimation for the difference in paired areas under the ROC curves. Statistics in Medicine, Published on-line on December 1, 2006.
19. Liao, C. T., Lin, C. Y., Liu, J. P. (2006). Non-inferiority tests based on concordance correlation coefficient for assessment of the agreement for gene expression data from microarray experiments. Journal of Biopharmaceutical Statistics 17:309-327.
20. Lin, L. I. (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255-268.
21. Lin, L. I. (1992). Assay validation using the concordance correlation coefficient. Biometrics 48:599-604.
22. Lin, L. I., Hedayat, A. S., Sinha, B., Yang, M. (2002). Statistical methods in assessing agreement: models, issues, and tools. Journal of the American Statistical Association 97:257-270.
23. Liu, J. P., Hsueh, H. M., Hsieh, E., Chen, J. J. (2002). Tests for equivalence or non-inferiority for paired binary data. Statistics in Medicine 21:231-245.
24. Liu, J. P., Ma, M. C., Wu, C. Y., Tai, J. Y. (2006). Tests of equivalence and non-inferiority for diagnostic accuracy based on the paired areas under ROC curves. Statistics in Medicine 25:1219-1238.
25. Maitournam, A., Simon, R. (2005). On the efficiency of targeted clinical trials. Statistics in Medicine 24:329-339.
26. MAQC Consortium (2006). The MAQC project shows inter- and intraplatform reproducibility of gene expression measurements. Nature Biotechnology 24:1151-1161.
27. Members of the Toxicogenomic Research Consortium (2005). Standardization of global gene expression analysis between laboratories and across platforms. Nature Methods 2:351-356.
28. MINDACT Design and MINDACT trial overview. (2006). http://www. breastinternationalgroup.org/transbig.html. Accessed on June 5, 2006.
29. Paik, S., Shak, S., Tang, G., et al. (2004). A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. New England Journal of Medicine 351:2817-2826.
30. Paik, S., Tang, G., Shak, S., et al. (2006). Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. Journal of Clinical Oncology 24:1-12.
31. Patterson, T. A., Lobenhofer, E. K., Fulmer-Smentek, S. B., et al. (2006). Performance comparison of one-color and two-color platforms with the MAQC project. Nature Biotechnology 24:1140-1150.
32. Reiser, B., Faraggi, D. (1997). Confidence intervals for the general ROC criterion. Biometrics 53:644-652.
33. Shippy, R., Fulmer-Smentek, S., Jensen, R. V., et al. (2006). Using RNA sample titrations to assess microarray platform performance and normalization techniques. Nature Biotechnology 24:1123-1131.
34. Simon, R., Maitournam, A. (2004). Evaluating the efficiency of targeted designs for randomized clinical trials. Clinical Cancer Research 10:6759-6763.
35. Simon, R. M., Korn, E. L., McShane, L. M., Radmacher, M. D., Wright, G. W., Zhao, Y. (2003). Design and Analysis of DNA Microarray Investigations. New York: Springer.
36. Sprarano, J., Hayes, D., Dees, E., et al. (2006). Phase III randomized study of adjuvant combination chemotherapy and hormonal therapy vs. adjuvant hormonal therapy alone in women with previously resected axillary node-negative breast cancer with various levels of risk for recurrence (TAILORX Trial). http://www.cancer.gov/clinicaltrials/ECOG- PACCT-1. Accessed on June 5 2006.
37. Su, J. Q., Liu, J. S. (1993). Linear combination of multiple diagnostic markers. Journal of the American Statistical Association 88:1350-1355.
38. Swain, S. M. (2006). A step in the right direction. Journal of Clinical Oncology 24(23):1-2.
39. Tong, W., Lucas, A. B., Shippy, R., et al. (2006). Evaluation of external RNA controls for the assessment of microarray performance. Nature Technology 24:1132-1139.
40. Tusher, V. G., Tibshirani, R., Chu, G. (2001). Significance analysis of microarrays applied to ionizing radiation response. Proceedings of National Academy of Sciences 98:5116-5121.
41. van't Veer, L. J., Dai, H., van de Vijver, M. J., et al. (2002). Gene expression profiling predicts clinical outcome of breast cancer. Nature 415:530-536.
42. Van de Vijver, M. J., He, Y. D., van't Veer, L. J., et al. (2002). A gene-expression signature as a predictor of survival in breast cancer. New England Journal of Medicine 347:1999-2009.
43. Varmus, H. (2006). The new era in cancer research. Science 312:1162-1165.
44. Wang, S., Ethier, S. (2004). A generalized likelihood ratio test to identify differentially expressed genes from microarray data. Bioinformatics 20:100-104.