Abstract
Over the past three decades, clinical trials have become one of the major standards for evaluating new therapies and interventions in medicine [1–3]. Numerous clinical trials have been conducted during this period across a wide variety of diseases, evaluating drugs, procedures, devices, and biologic materials. The fundamentals of the design, conduct, and analyses of clinical trials have been developed and refined during this period as well. One such fundamental is that clinical data should be carefully monitored during the course of the trial so that unexpected or unacceptable toxicity can be detected as soon as possible in order to minimize patient exposure; in addition, trials should not be continued longer than necessary to prove the benefits of the therapy or intervention under study, or to understand the trade-offs between the benefits and risks of the therapy. In order to accomplish this goal, the National Institutes of Health sponsored a committee in the 1960s to develop guidelines for the conduct of clinical trials. The chair of this committee was Dr. Bernard Greenberg from the University of North Carolina, and the report, which was issued in 1967, has become known as the Greenberg Report [4], although it was only recently published in the literature. This report endorses the concept of interim review of data by an independent Data and Safety Monitoring Board (DSMB), a committee that has no conflict of interest for the study. This typically means that committee members should not be investigators entering patients into the trial. The Coronary Drug Project (CDP) [5] was one of the first trials to implement the Greenberg model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Friedman L, Furburg C, DeMets DL (1985). Fundamentals of Clinical Trials, 2nd edition. Littleton, MA: PSG.
Pocock SJ (1983). Clinical Trials: A Practical Approach. New York: Wiley.
Peto R, Pike MC, Armitage P, et al. (1976). Design and analysis of randomized clinical trials requiring prolonged observations of each patient. I. Introduction and design. Br J Cancer 34:585–612.
Heart Special Project Committee (1988). Organization, review and administration of cooperative studies (Greenberg Report): A report from the Heart Special Project Committee to the National Advisory Council, May 1967. Controlled Clin Trials 9:137–148.
Coronary Drug Project Research Group (1981). Practical aspects of decision making in clinical trials: The Coronary Drug Project as a case study. Controlled Clin Trials 1:363–376.
Beta-Blocker Heart Attack Trial Research Group (1982). A randomized trial of propranolol in patients with acute myocardial infarction. I. Mortality results. JAMA 247: 1707–1714.
Cardiac Arrhythmia Suppression Trial (CAST) Investigators (1989). Preliminary report: Effect of encainide and flecainide on mortality in a randomized trial of arrhythmia suppression after myocardial infarction. N Engl J Med 321(6):406–412.
DeMets DL (1990). Data monitoring and sequential analysis-An academic perspective. J AIDS 3 (Suppl 2):S124–S133.
DeMets DL (1984). Stopping guidelines vs. stopping rules: A practitioner’s point of view. Comm Stat (A) 13(19):2395–2417.
DeMets DL, Hardy R, Friedman LM, Lan KKG (1984). Statistical aspects of early termination in the Beta-Blocker Heart Attack Trial. Controlled Clin Trials 5:362–372.
Pawitan Y, Hallstrom A (1990). Statistical interim monitoring of the cardiac arrhythmia suppression trial. Stat Med 9:1081–1090.
Fleming T, DeMets DL (1993). Monitoring of clinical trials: Issues and recommendations. Controlled Clin Trials 14:183–197.
Pocock SJ (1993). Statistical and ethical issues in monitoring clinical trials. Stat Med 12:1459–1469.
Pocock SJ (1992). When to stop a clinical trial. Br Med J 305:235–240.
Emerson SS, Fleming TR (1990). Interim analyses in clinical trials. Oncology 4:126–133.
Task Force of the Working Group on Arrhythmias of the European Society of Cardiology (in press). The early termination of clinical trials: Causes, consequences, and control-with special reference to trials in the field of arrhythmias and sudden death. Eur Heart J.
Lai TL (1984). Incorporating scientific, ethical and economic considerations into the design of clinical trials in pharmaceutical industry: A sequential approach. Comm Stat (A) 13: 2355–2368.
Wald A (1947). Sequential Analysis. New York: Wiley.
Bross I (1952). Sequential medical plans. Biometrics 8:188–205.
Anscombe FJ (1963). Sequential Medical Trials. J Am Stat Assoc 58:365–383.
Armitage P (1975). Sequential Medical Trials, 2nd edition. New York: John Wiley & Sons.
Armitage P, McPherson CK, Rowe BC (1969). Repeated significance tests on accumulating data. J R Stat Soc A 132:235–244.
Robbins H (1970). Statistical methods related to the law or iterated logarithm. Ann Math Stat 41:1397–1409.
Meier P (1975). Statistics and medical examination. Biometrics 31:511–529.
Canner PL (1977). Monitoring treatment differences in long-term clinical trials. Biometrics 33:603–615.
Whitehead J (1991). The Design and Analysis of Sequential Clinical Trials, 2nd edition. Chichester: Ellis Horwood.
Haybittle JL (1971). Repeated assessment of results in clinical trials of cancer treatment. Br J Radiol 44:793–797.
Pocock SJ (1977). Group sequential methods in the design and analysis of clinical trials. Biometrika 64:191–199.
O’Brien PC, Fleming TR (1979). A multiple testing procedure for clinical trials. Biometrics 35:549–556.
Lan KKG, DeMets DL (1983). Discrete sequential boundaries for clinical trials. Biometrika 70:659–663.
DeMets DL (1987). Practical aspects in data monitoring: A brief review. Stat Med 6: 753–760.
Jennison C, Turnbull BW (1990). Statistical approaches to interim monitoring of medical trials: A review and commentary. Stat Sci 5:299–317.
DeMets DL, Lan KKG (in press). Interim analyses: The alpha spending function approach. Stat Med.
Lan KKG, DeMets DL, Halperin M (1984). More flexible sequential and non-sequential designs in long-term clinical trials. Comm Stat (A) 13(19):2339–2353.
Lan KKG, Zucker D (1993). Sequential monitoring of clinical trials: the role of information in Brownian motion. Stat Med 12:753–765.
Hwang IK, Shih WJ (1990). Group sequential designs using a family of type I error probability spending function. Stat Med 9:1439–1445.
Kim K, DeMets DL (1987). Design and analysis of group sequential tests based on the type I error spending rate function. Biometrika 74:149–154.
DeMets DL, Ware JH (1982). Asymmetric group sequential boundaries for monitoring clinical trials. Biometrika 69:661–663.
Emerson SS, Fleming TR (1989). Symmetric group sequential test designs. Biometrics 45:905–932.
Lan KKG, DeMets DL (1989). Group sequential procedures: calendar versus information time. Stat Med 8:1191–1198.
Lan KKG, Reboussin DM, DeMets DL (in press). Information and information fractions for design and sequential monitoring of clinical trials. Comm Stat (A).
Lan KK, Wittes J (in press). Data monitoring in complex clinical trials: which treatment is better? J Stat Planning Inference.
Li Z, Geller NL (1991). On the choice of times for date analysis in group sequential trials. Biometrics 47:745–750.
Lan KKG, DeMets DL (1989). Changing frequency of interim analyses in sequential monitoring. Biometrics 45:1017–1020.
Proschan MA, Follman DA, Waclawiw MA (1992). Effects of assumption violations on type I error rate in group sequential monitoring. Biometrics 48:1131–1143.
Kim K, DeMets DL (1992). Sample size determination for group sequential clinical trials with immediate response. Stat Med 11:1391–1399.
Fleming TR, Harrington DP (1991). Counting Processes and Survival Analysis. New York: Wiley.
Tarone R, Ware J (1978). On distribution free tests for equality of survival distributions. Biometrika 64:167–179.
Gail MH, DeMets DL, Slud EV (1992). Simulation studies on increments of the two-sample logrank score test for survival time data, with application to group sequential boundaries. In Survival Analysis, J Crowley, R Johnson (eds.), vol. 2. Hayward, CA: IMS Lecture Note Series.
Tsiatis AA (1982). Repeated significance testing for a general class of statistics used in censored survival analysis. J Am Stat Assoc 77:855–861.
Slud E, Wei LJ (1982). Two-sample repeated significance tests based on the modified Wilcoxon statistic. J Am Stat Assoc 77:862–868.
DeMets DL, Gail MH (1985). Use of logrank tests and group sequential methods at fixed calendar times. Biometrics 41:1039–1044.
Lan KKG, Lachin J (1990). Implementation of group sequential logrank tests in a maximum duration trial. Biometrics 46:759–770.
Sellke T, Siegmund D (1983). Sequential analysis of the proportional hazards model. Biometrika 70:315–326.
Kim K, Tsiatis AA (1990). Study duration for clinical trials with survival response and early stopping rule. Biometrics 46:81–92.
Kim K (1992). Study duration for group sequential clinical trials with censored survival data adjusting for stratification. Stat Med 11:1477–1488.
Lan KKG, Rosenberger WF, Lachin JM (1993). Use of spending functions for occasional or continuous monitoring of data in clinical trials. Stat Med 12:2214–2231.
Lee, JW (1994). Group sequential testing in clinical trials with multivariate observations: a review. Stat Med 13:101–111.
Laird NM, Ware JH (1983). Random effects models for longitudinal data. Biometrics 38:963–974.
Lee JW, DeMets DL (1991). Sequential comparison of change with repeated measurement data. J Am Stat Assoc 86:757–762.
Lee JW, DeMets DL (1992). Sequential rank tests with repeated measurements in clinical trials. J Am Stat Assoc 87:136–142.
Wu MC, Lan KKG (1992). Sequential monitoring for comparison of changes in a response variable in clinical trials. Biometrics 48:765–779.
Wei LJ, Su JQ, Lachin JM (1990). Interim analyses with repeated measurements in a sequential clinical trial. Biometrika 77(2):359–364.
Su JQ, Lachin J (1992). Group sequential distribution-free methods for the analysis of multivariate observations. Biometrics 48:1033–1042.
Smith E, Sempos CT, Smith PE, Gilligan C (1989). Calcium supplementation and bone loss in middle-aged women. Am J Clin 50:833–842.
Reboussin D, Lan KKG, DeMets DL (1992). Group sequential testing of longitudinal data. Technical Report #72, Department of Biostatistics, University of Wisconsin, Madison, WI.
Jennison C, Turnbull BW (1984). Repeated confidence intervals for group sequential trials. Controlled Clin Trials 5:33–45.
Jennison C, Turnbull BW (1989). Interim analyses: The repeated confidence interval approach. J R Stat Soc B 51:305–361.
DeMets DL, Lan KKG (1989). Discussion of: Interim analyses: The repeated confidence interval approach by C. Jennison and B.W. Turnbull. J R Stat Soc B 51:362.
Fleming TR, Watelet LF (1989). Approaches to monitoring clinical trial. J Natl Cancer Inst 81(3):188–193.
Fleming TR (1990). Evaluation of active control trials in AIDS. J AIDS 3 (Suppl):S82–S87.
Fleming TR (1978). Treatment evaluation in active control studies. Cancer Treat Rep 17(11):1061–1065.
Siegmund D (1978). Estimation following sequential tests. Biometrika 65:341–349.
Tsiatis AA, Rosner GL, Mehta CR (1984). Exact confidence intervals following a group sequential test. Biometrics 40:797–803.
Rosner GL, Tsiatis AA (1988). Exact confidence intervals following a group sequential trial: A comparison of methods. Biometrika 75:723–729.
Kim K (1989). Point estimation following group sequential tests. Biometrics 45:613–617.
Kim K, DeMets DL (1987). Confidence intervals following group sequential tests in clinical trials. Biometrics 4:857–864.
Whitehead J (1986). On the bias of maximum likelihood estimation following a sequential test. Biometrika 73:573–581.
Emerson SS, Fleming TR (1990). Parameter estimation following group sequential hypothesis testing. Biometrika 77:875–892.
Pocock SJ, Hughes MD (1989). Practical problems in interim analyses, with particular regard to estimation. Controlled Clin Trials 10:2094–2215.
Chang MN, O’Brien PC (1986). Confidence intervals following group sequential tests. Controlled Clin Trials 7:18–26.
Whitehead J, Facey KM (1991). Analysis after a sequential trial: a comparison of orderings of the sample space. Presented at the Joint Society for Clinical Trials/International Society for Clinical Biostatistics, Brussels.
Hughes MD, Pocock SJ (1988). Stopping rules and estimation problems in clinical trials. Stat Med 7:1231–1241.
Whitehead J (1992). Overrunning and underrunning in sequential trials. Controlled Clin Trials 13:106–121.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1995 Springer Science+Business Media New York
About this chapter
Cite this chapter
DeMets, D.L., Lan, G. (1995). The alpha spending function approach to interim data analyses. In: Thall, P.F. (eds) Recent Advances in Clinical Trial Design and Analysis. Cancer Treatment and Research, vol 75. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2009-2_1
Download citation
DOI: https://doi.org/10.1007/978-1-4615-2009-2_1
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5830-5
Online ISBN: 978-1-4615-2009-2
eBook Packages: Springer Book Archive