Sage Journals: Discover world-class research

Abstract

The design of a randomized, controlled, confirmatory efficacy clinical trial is influenced by multiple competing factors, including ethical, scientific, economic, and regulatory interests. Design elements, including choice of end points, study duration, and interim monitoring plans, need to be adapted to specific circumstances. The Weekly Intervention With Zithromax for Atherosclerosis and Its Related Disorders (WIZARD) study design was initially intended to meet the sponsor's scientific goals while being subject to practical constraints. In response to changing circumstances, modifications to the study design were required. The WIZARD trial demonstrates the substantial flexibility in the design and conduct of group-sequential randomized trials not only during the design stage but also after the trial is under way, effectively satisfying evolving and competing demands while preserving the statistical and scientific validity of the study.

Keywords

Composite end points Event-driven trials Group sequential testing Adaptive design Conditional power

Get full access to this article

View all access options for this article.

References

Dunne

. Rationale and design of a secondary prevention trial of antibiotic use in patients after myocardial infarction: the WIZARD ([Weekly Intervention with Zithromax Azithromycin] for Atherosclerosis and Its Related Disorders) trial. J Infect Dis. 2000;181(suppl 3):S572–S578.

O'Connor

Dunne

Pfeffer

A double-blind, randomized, placebo controlled trial of azithromycin for the secondary prevention of coronary heart disease: the WIZARD trial. JAMA. 2003;290:1459–1466.

EaSt-2000: Software for the Design and Interim Monitoring of Group Sequential Clinical Trials. Cambridge, MA: Cytel Software Corporation; 2000.

O'Brien

Fleming

. A multiple testing procedure for clinical trials. Biometrics. 1979;35:549–556.

Lan

KKG

DeMets

. Discrete sequential boundaries for clinical trials. Biometrika. 1983;70:659–663.

Lan

KKG

Wittes

. The B-value: a tool for monitoring data. Biometrics. 1988;44:579–585.

Tsiatis

. The asymptotic joint distribution of the efficient scores test for the proportional hazards model calculated over time. Biometrika. 1981;68:311–315.

Bauer

Köhne

. Evaluation of experiments with adaptive interim analyses. Biometrics. 1994;50:1029–1041.

Lehmacher

Wassmer

. Adaptive sample size calculations in group sequential trials. Biometrics. 1999;55:1286–1290.

10.

Müller

Schäfer

. Adaptive group sequential designs for clinical trials: combining the advantages of adaptive and of classical group sequential approaches. Biometrics 2001;57:886–891.

11.

Proschan

Hunsberger

. Designed extension of studies based on conditional power. Biometrics. 1995;51:1315–1324.

12.

Lan

KKG

Trost

. Estimation of parameters and sample size re-estimation. In: ASA Proceedings of the Biopharmaceutical Section. Alexandria, VA: American Statistical Association; 1997:48–51.

13.

Fisher

. Self-designing clinical trials. Stat Med. 1998;17:1551–1562.

14.

Shen

Fisher

. Statistical inference for self-designing clinical trials with a one-sided hypothesis. Biometrics. 1999;55:190–197.

15.

Cui

Hung

HMJ

Wang

. Modification of sample size in group sequential clinical trials. Biometrics. 1999;55:853–857.

16.

Shih

Xie

. A sample size adjustment procedure for clinical trials based on conditional power. Biostatistics. 2002;3:277–287.

17.

Wittes

Brittain

. The role of internal pilot studies in increasing the efficiency of clinical trials (with comments). Stat Med. 1990;9:65–72.

18.

Gould

Shih

. Modifying the design of ongoing trials without unblinding. Stat Med. 1998;17:89–100.

19.

Friede

Kieser

. Sample size recalculation for binary data in internal pilot study designs. Pharm Stat. 2004;3:269–279.

20.

Cook

. Methods for mid-course corrections in clinical trials with survival outcomes. Stat Med. 2003;22:3431–3447.

21.

Lakatos

. Sample size determination in clinical trials with time-dependent rates of losses and noncompliance. Controlled Clin Trials. 1986;7:189–199.

22.

Lakatos

. Sample sizes based on the log-rank statistic in complex clinical trials. Biometrics. 1988;44:229–241.

23.

Armitage

McPherson

Rowe

. Repeated significance tests on accumulating data. J R Stat Soc Ser A. 1969;132:235–244.

24.

Reboussin

DeMets

Kim

Lan

KKG

. Computations for group sequential boundaries using the Lan-DeMets spending function method. Controlled Clin Trials. 2000;21:190–207.

The WIZARD Trial as a Case Study of Flexible Clinical Trial Design

Abstract

Keywords

Get full access to this article

References