Skip to main content

Timing and Frequency of Interim Analyses in Confirmatory Trials

  • Chapter
  • First Online:
Practical Considerations for Adaptive Trial Design and Implementation

Part of the book series: Statistics for Biology and Health ((SBH))

Abstract

In many pivotal clinical trials, timing and frequency of interim analyses are important for ethical treatment of patients and for practical and regulatory purposes. It is often desirable to evaluate a large trial of a new treatment that has some safety risk in order to stop or modify the trial based on the emerging risk–benefit profile compared to control treatment. Statistical considerations would suggest not stopping too soon in order to avoid large Type I or Type II error or basing a decision on inadequate data. Regulators often prefer to minimize interim analyses of efficacy due to presumed bias created by early stopping and an inability to adequately evaluate important secondary efficacy endpoints, safety, or the general risk–benefit profile for the new treatment. For practical purposes, analyses must be done soon enough to have a meaningful impact on the trial. For the same reason, limiting enrollment rates and ensuring prompt collection and analysis of data are important. We discuss tradeoffs between these factors in deciding when to perform interim analyses. In addition to formal evaluations for early positive efficacy findings, there are different considerations for trials early in the development process, for safety monitoring during a trial, and for futility analyses. We consider logistical and regulatory issues throughout.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Anderson KM (2012) gsdesign: Group sequential design. R package version 2.9.2

    Google Scholar 

  • Bauer P, Koenig F, Brannath W, Posch M (2010) Selection and bias – two hostile brothers. Stat Med 29:1–13

    MathSciNet  Google Scholar 

  • Center for Drug Evaluation and Research and Center for Biologics Evaluation and Research (2010) Guidance for industry. Adaptive design clinical trials for drugs and biologics. Draft guidance. United States Department of Health and Human Services, U.S. Food and Drug Administration, URL http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm201790.pdf

  • Demetri GD, van Oosterom AT, Garrett CR, Blackstein ME, Shah MH, Verweij J, McArthur G, Judson IR, Heinrich MC, Morgan JA, Desai J, Fletcher CD, George S, Bello CL, Huang X, Baum CM, Casali PG (2006) Efficacy and safety of sunitinib in patients with advanced gastrointestinal stromal tumour after failure of imatinib: a randomised controlled trial. Lancet 368:1329–1338. doi: 10.1016/ S0140-6736(06)69446-4

    Google Scholar 

  • Dragalin V (2006) Adaptive designs: terminology and classification. Drug Inform J 40:425–435. doi: 0092-8615/2006

    Google Scholar 

  • EPILOG Investigators (1996) Platelet glycoprotein iib/iiia receptor blockade and low-dose heparin during percutaneous coronary revascularization. New Engl J Med 336:1689–1696

    Google Scholar 

  • Jennison C, Turnbull BW (2000) Group sequential methods with applications to clinical trials. Chapman and Hall/CRC, Boca Raton

    MATH  Google Scholar 

  • Ji Y, Liu P, Li Y, Bekele BN (2010) A modified toxicity probability interval method for dose-finding trials. Clin Trials 7:653–663. doi: 10.1177/ 1740774510382799

    Article  Google Scholar 

  • Lan KKG, DeMets DL (1983) Discrete sequential boundaries for clinical trials. Biometrika 70:659–663

    Article  MathSciNet  MATH  Google Scholar 

  • Lee JJ, Liu DD (2008) A predictive probability design for phase ii cancer clinical trials. Clin Trials 5:93–106

    Article  Google Scholar 

  • Mehta C, Tsiatis AA (2001) Flexible sample size considerations using information-based interim monitoring. Drug Inform J 35:1095–1112

    Article  Google Scholar 

  • O’Brien PC, Fleming TR (1979) A multiple testing procedure for clinical trials. Biometrika 35:549–556

    Article  Google Scholar 

  • O’Quigley J, Pepe M, Fisher L (1990) Continual reassessment method for phase i clinical trials in cancer. Biometrics 46:33–48

    Article  MathSciNet  MATH  Google Scholar 

  • Scharfstein DO, Tsiatis AA, Robins JM (1997) Semiparametric efficiency and its implication on the design and analysis of group-sequential studies. J Am Stat Assoc 92:1342–1350

    Article  MATH  Google Scholar 

  • Siegmund D (1985) Sequential analysis. Tests and confidence intervals. Spring, New York

    Book  MATH  Google Scholar 

  • Simon R (1989) Optimal two-stage designs for phase ii clinical trials. Contr Clin Trials 10:1–10

    Article  Google Scholar 

  • The Coronary Drug Project Research Group (1981) Practical aspects of decision making in clinical trials: The coronary drug project as a case study. Contr Clin Trials 1:363–376

    Google Scholar 

  • The PURSUIT Investigators (1998) Inhibition of platelet glycoprotein iib/iiia with eptifibatide in patients with acute coronary syndromes. New Engl J Med 339:436–443

    Google Scholar 

  • The REST Study Group (2006) Safety and efficacy of a pentavalent humaâĂŞbovine (wc3) reassortant rotavirus vaccine. New Engl J Med 354:23–33

    Article  Google Scholar 

  • Tsiatis AA (2006) Information-based monitoring of clinical trials. Stat Med 25:3236–3244. doi: 10.1002

    Google Scholar 

  • Wald A (1945) Sequential tests of statistical hypotheses. Ann Math Stat 16:117–186. doi: 10.1214/aoms/1177731118

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Keaven M. Anderson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this chapter

Cite this chapter

Anderson, K.M. (2014). Timing and Frequency of Interim Analyses in Confirmatory Trials. In: He, W., Pinheiro, J., Kuznetsova, O. (eds) Practical Considerations for Adaptive Trial Design and Implementation. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1100-4_6

Download citation

Publish with us

Policies and ethics