Sample size determination in clinical trials with multiple co-primary binary endpoints

Statistics in Medicine

Volumn 29, Issue 21, 2010, Pages 2169-2179

  Sozu, Takashi ^a,b   Sugimoto, Tomoyuki ^b   Hamasaki, Toshimitsu ^a,b  

^a OSAKA UNIVERSITY   (Japan)

^b OSAKA UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

Author keywords

Arcsine transformation; Association measures; Continuity correction; Correlated endpoints; Fisher's exact method; Multivariate Bernoulli

Indexed keywords

ARTICLE; CALCULATION; CLINICAL TRIAL; EFFECT SIZE; FISHER EXACT TEST; MULTIPLE CO PRIMARY BINARY ENDPOINT; POWER ANALYSIS; SAMPLE SIZE; STATISTICAL DISTRIBUTION; YATES CONTINUITY CORRECTION;

ALGORITHMS; BINOMIAL DISTRIBUTION; ENDPOINT DETERMINATION; HUMANS; MIGRAINE DISORDERS; MODELS, STATISTICAL; MONTE CARLO METHOD; ODDS RATIO; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SAMPLE SIZE; TREATMENT OUTCOME;

EID: 77956899112     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3972     Document Type: Article

References (26)

1. Pocock SJ. Clinical trials with multiple outcomes: a statistical perspective on their design, analysis and interpretation. Controlled Clinical Trials 1997; 18:530-545.
2. Bloch DA, Lai TL, Su Z, Tubert-Bitter P. A combined superiority and non-inferiority approach to multiple endpoints in clinical trials. Statistics in Medicine 2007; 26:1193-1207. DOI: 10.1002/sim.2611.
3. International Conference on Harmonization (ICH) of Technical Requirements for Regulations of Pharmaceuticals for Human use. ICH Tripartite Guideline E-9 Documents, Statistical Principles for Clinical Trials, 5 February 1998.
4. Chuang-Stein C, Stryszak P, Dmitrienko A, Offen W. Challenge of multiple co-primary endpoints: a new approach. Statistics in Medicine 2007; 26:1181-1192. DOI: 10.1002/sim.2604.
5. Eaton ML, Muirhead RJ. On a multiple endpoints testing problem. Journal of Statistical Planning and Inference 2007; 137:3416-3429. DOI: 10.1016/j.jspi.2007.03.021.
6. Offen W, Chuang-Stein C, Dmitrienko A, Littman G, Maca J, Meyerson L, Muirhead R, Stryszak P, Boddy A, Chen K, Copley-Merriman K, Dere W, Givens S, Hall D, Henry D, Jackson JD, Krishen A, Liu T, Ryder S, Sankoh AJ, Wang J, Yeh CH. Multiple co-primary endpoints: medical and statistical solutions. Drug Information Journal 2007; 41:31-46.
7. Ho TW, Ferrari MD, Dodick DW, Galet V, Kost J, Fan X, Leibensperger H, Froman S, Assaid C, Lines C, Koppen H, Winner PK. Efficiency and tolerability of MK-0974 (telcagepant) a new oral antagonist of calcitonin gene-related peptide receptor, compared with Zolmitriptan for acute migraine: a randomised, placebo-controlled, parallel-treatment trial. The Lancet 2008; 37:2115-2123. DOI: 10.1016/S0140-6736(08)61626-8.
8. Hung HM, Wang SJ. Some controversial multiple testing problems in regulatory applications. Journal of Biopharmaceutical Statistics 2009; 19:1-11. DOI: 10.1080/10543400802541693.
9. Phillips A, Ebbutt A, France L, Morgan D. The International conference on harmonization guideline 'Statistical Principles for Clinical Trials': Issue in applying the guideline in practice. Drug Information Journal 2000; 34:337-348.
10. Committee for Proprietary Medicinal Products (CPMP). Points to Consider on Multiplicity Issues in Clinical Trials (CPMP/EWP/908/99). EMEA: London, 2002.
11. Sankoh AJ, D'Agostino RB, Huque MF. Efficacy endpoint selection and multiplicity adjustment method in clinical trials with inherent multiple endpoint issues. Statistics in Medicine 2003; 22(20):3133-3150. DOI: 10.1002/sim1557.
12. Xiong C, Yu K, Gao F, Yan Y, Zhang Z. Power and sample size for clinical trials when efficacy is required in multiple endpoints: application to an Alzheimer's treatment trial. Clinical Trials 2005; 2:387-393. DOI: 10.1191/1740774505cn112oa. (Pubitemid 41586023)
13. Sozu T, Kanou T, Hamada C, Yoshimura I. Power and sample size calculations in clinical trials with multiple primary variables. Japanese Journal of Biometrics 2006; 27:83-96.
14. Prentice RL. Correlated binary regression with covariates specific to each binary observarion. Biometrics 1988; 44:1033-1048.
15. Emrich LJ, Piedmonte MR. A method for generating high-dimensional multivariate binary variates. The American Statistician 1991; 45:302-304.
16. Bahadur RR. A representation of the joint distribution of responses to n dichotomous items. In Studies in Item Analysis and Prediction, Vol. VI, Stanford Mathematical Studies in the Social Sciences, Solomon H (ed.). Stanford University Press: Stanford, CA, 1961; 158-168.
17. le Cessie S, van Houwelingen JC. Logistic regression for correlated binary data. Applied Statistics 1994; 43:95-108.
18. Dale JR. Global cross-ratio models for bivariate, discrete, ordered responses. Biometrics 1986; 42:909-917.
19. Pearson K. Mathematical contributions to the theory of evolution. VII. On the correlation of characters not quantitatively measurable. Philosophical Transactions of the Royal Society, Series A 1900; 195:1-47.
20. 2 test. Journal of the Royal Statistical Society, Supplement 1934; 1:217-235.
21. Bartlett MS. The use of transformations. Biometrics 1947; 3:39-52.
22. Walters DE. In defence of the arc sine approximation. The Statistician 1979; 28:219-222.
23. SAS Institute, Inc., SAS Online Doc 9.1.3. SAS Institute, Inc.: Cary, NC, 2006.
24. Ury HK. Continuity-corrected approximations to sample size or power when comparing two proportions: Chi-squared or arc sine? The Statistician 1981; 30:199-203.
25. Sahai H, Khurshid A. Formulae and tables for the determination of sample sizes and power in clinical trials for testing differences in proportions for the two-sample design: a review. Statistics in Medicine 1996; 15(1):1-21. (Pubitemid 26016007)
26. Chow SC, Shao J, Wang H. Sample Size Calculations in Clinical Research (2nd edn). Chapman and Hall/CRC: Boca Raton, FL, 2007.