Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels

Statistics in Medicine

Volumn 35, Issue 12, 2016, Pages 1972-1984

  Zebrowska, Magdalena ^a   Posch, Martin ^a   Magirr, Dominic ^a  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

Author keywords

Adaptive clinical trials; Blinded interim analysis; Block randomization; Random allocation; Sample size reassessment; Type I error rate control

Indexed keywords

CHEMICAL BINDING; CLINICAL TRIAL; CONTROLLED CLINICAL TRIAL; EFFECT SIZE; EXPERIMENTAL THERAPY; HUMAN; NULL HYPOTHESIS; PARALLEL DESIGN; RANDOMIZATION; RANDOMIZED CONTROLLED TRIAL; SAMPLE SIZE; SINGLE BLIND PROCEDURE; BIOASSAY; DRUG LABELING; METHODOLOGY; MULTIPLE SCLEROSIS; PHASE 3 CLINICAL TRIAL (TOPIC); PROCEDURES; RANDOMIZED CONTROLLED TRIAL (TOPIC); STANDARDS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

FINGOLIMOD;

CLINICAL TRIALS, PHASE III AS TOPIC; DRUG LABELING; ENDPOINT DETERMINATION; FINGOLIMOD HYDROCHLORIDE; HUMANS; MODELS, STATISTICAL; MULTIPLE SCLEROSIS, RELAPSING-REMITTING; RANDOM ALLOCATION; RANDOMIZED CONTROLLED TRIALS AS TOPIC; RESEARCH DESIGN; SAMPLE SIZE; SINGLE-BLIND METHOD;

EID: 84952701035     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6848     Document Type: Article

References (34)

1. ICH Topic E9: Notes for guidance on statistical principles for clinical trials, European Agency for the Evaluation of Medical Products: London, UK, 1998.
2. Proschan MA, Hunsberger SA. Designed extension of studies based on conditional power. Biometrics. 1995; 51: 1315-1324.
3. Graf AC, Bauer P. Maximum inflation of the type 1 error rate when sample size and allocation rate are adapted in a pre-planned interim look. Statistics in Medicine. 2011; 30: 1637-1647.
4. Bauer P, Köhne K. Evaluation of experiments with adaptive interim analyses. Biometrics. 1994; 50: 1029-1041.
5. Posch M, Bauer P, Brannath W. Issues in designing flexible trials. Statistics in Medicine. 2003; 23: 953-969.
6. Bretz F, König F, Brannath W, Glimm E, Posch M. Adaptive designs for confirmatory clinical trials. Statistics in Medicine. 2003; 28: 1181-1217.
7. EMEA. Reflection paper on methodological issues in confirmatory clinical trials planned with an adaptive design. EMEA Doc. Ref. CHMP/EWP/2459/02, 2007. Available at http://www.emea.europa.eu/pdfs/human/ewp/245902enadopted.pdf.
8. Guidance for industry: adaptive design clinical trials for drugs and biologics (Draft guidance), CDER, FDA: Rockville, MD, USA, 2010.
9. Guidance for industry: adaptive designs for medical device clinical studies (Draft guidance), CBER, FDA: Rockville, MD, USA, 2015.
10. Kieser M, Friede T. Simple procedures for blinded sample size adjustment that do not affect the type I error rate. Statistics in Medicine. 2003; 22: 3571-3581.
11. Proschan M. Two-stage sample size re-estimation based on a nuisance parameter: a review. Journal of Biopharmaceutical Statistics. 2005; 15: 559-574.
12. Proschan MA, Lan KKG, Wittes JT. Statistical Monitoring of Clinical Trials: A Unified Approach. Springer: New York, 2006.
13. Friede T, Kieser M. Sample size recalculation for binary data in internal pilot study designs. Pharmaceutical Statistics. 2004; 3: 269-279.
14. Friede T, Schmidli H. Blinded sample size reestimation with count data: methods and applications in multiple sclerosis. Statistics in Medicine. 2010; 29: 1145-1156.
15. Posch M, Proschan MA. Unplanned adaptations before breaking the blind. Statistics in Medicine. 2012; 31: 4146-4153.
16. Proschan M, Glimm E, Posch M. Connections between permutation and t-tests: relevance to adaptive methods. Statistics in Medicine. 2014; 33(27): 4734-4742.
17. Friede T, Kieser M. Blinded sample size reassessment in non-inferiority and equivalence trials. Statistics in Medicine. 2003; 22: 995-1007.
18. Elsäßer A, Regnstrom J, Vetter T, Koenig F, Hemmings RJ, Greco M, Papaluca-Amati M, Posch M. Adaptive clinical trial designs for european marketing authorization: a survey of scientific advice letters from the european medicines agency. Trials. 2014; 15: 383.
19. Hastings WK. Monte carlo sampling methods using markov chains and their applications. Biometrika. 1970; 57(1): 97-109.
20. Lehmann EL. Elements of Large-Sample Theory, Springer Texts in Statistics. Springer: New York, 1998.
21. Miller F, Friede T, Kieser M. Blinded assessment of treatment effects utilizing information about the randomization block length. Statistics in Medicine. 2009; 28: 1690-1706.
22. A service of the U.S. National Institutes of Health. Efficacy and safety of Fingolimod in patients with relapsing-remitting multiple sclerosis (FREEDOMS). ClinicalTrials.gov, Bethesda, MD, USA. 2006. Identifier:NCT00289978.
23. Kappos L, Radue EW, O'Connor P, Polman C, Hohlfeld R, Calabresi P, Selmaj K, Agoropoulou C, Leyk M, Zhang-Auberson L, Burtin P. A placebo-controlled trial of oral fingolimod in relapsing multiple sclerosis. New England Journal of Medicine. 2010; 362(5): 387-401.
24. Boulton C, Meiser K, David OJ, Schmouder R. Pharmacodynamic effects of steady-state fingolimod on antibody response in healthy volunteers: a 4-week, randomized, placebo-controlled, parallel-group, multiple-dose study. The Journal of Clinical Pharmacology. 2012; 52: 1879-1890.
25. Lee JY, Wang Y. Use of a biomarker in exposure-response analysis to support dose selection for fingolimod. Pharmacometrics and Systems Pharmacology. 2013; 2(8): e67.
26. Francis G, Kappos L, OConnor P, Collins W, Tang D, Mercier F, Cohen JA. Temporal profile of lymphocyte counts and relationship with infections with fingolimod therapy. Multiple Sclerosis Journal. 2014; 20(4): 471-480.
27. Gould AL, Shih WJ. Sample size re-estimation without unblinding for normally distributed outcomes with unknown variance. Communications in Statistics, Part A. Theory and Methods. 1992; 21: 2833-2853.
28. Teel C, Park T, Sampson AR. Em estimation for finite mixture models with known mixture component size. Communications in Statistics - Simulation and Computation. 2015; 44(6).
29. Friede T, Kieser M. On the inappropriateness of an EM algorithm based procedure for blinded sample size re-estimation. Statistics in Medicine. 2002; 21: 165-176.
30. CPMP Q6 working party on efficacy of medicinal products note for guidance iii/3630/92-en. Biostatistical methodology in clinical trials in applications for marketing authorizations for medicinal products. Statistics in Medicine. 1995; 14(15): 1659-1682.
31. Wang SJ, Brannath W, Brückner M, James Hung HM, Koch A. Unblinded adaptive statistical information design based on clinical endpoint or biomarker. Statistics in Biopharmaceutical Research. 2013; 5: 293-310.
32. Ellenberg SS, Fleming TR, DeMets DL. Appendix A: The Data Monitoring Committee Charter. John Wiley & Sons, Ltd: The Atrium, Southern Gate, Chichester, West Sussex PO198SQ, England, 2003; 175-183.
33. Brannath W, Posch M, Bauer P. Recursive combination tests. Journal of the American Statistical Association. 2002; 97: 236-244.
34. Müller HH, Schäfer H. A general statistical principle for changing a design any time during the course of a trial. Statistics in Medicine. 2004; 23: 2497-2508.