Monitoring mortality at interim analyses while testing a composite endpoint at the final analysis.

Mortality is often used as the clinical endpoint in clinical trials for acute diseases and takes precedence over any other outcome. A composite outcome such as death plus disease occurrence (or recurrence) or death plus hospitalization may also be considered, sometimes even as the primary outcome due to practical sample size issues. That is, a composite endpoint should have a higher event rate and thus a smaller sample size than for mortality alone to reach the same power. Two different scenarios are considered: in Scenario 1, the composite outcome is the primary endpoint and the mortality outcome is secondary; in Scenario 2, the mortality outcome is the primary endpoint and the composite outcome is secondary. In either scenario, the trial will be stopped if the simple mortality outcome shows an adverse effect or a significant benefit at an interim analysis, while the composite outcome will be tested at the final analysis if the mortality outcomes fails to show significance. These scenarios are typical in many trials sponsored by industry for regulatory approval. We refer to them as a switching the primary endpoint process. Two switching-endpoint procedures are proposed to calculate the efficacy boundary for the composite test statistic at the final analysis. The Bonferroni method is used in Method 1. In Method 2, the calculation is based upon the joint distribution of the test statistics for the simple mortality and the composite outcomes. A completed clinical trial, prospective randomized amlodipine survival evaluation (PRAISE-1), is used to illustrate the two switching-endpoint procedures. A simulation study shows that the two switching-endpoint procedures allow a trial to be stopped early due to a clinically relevant benefit in the mortality while preserving the overall alpha level.

[1]  R J Cook,et al.  Guidelines for monitoring efficacy and toxicity responses in clinical trials. , 1994, Biometrics.

[2]  L. Fisher Carvedilol and the Food and Drug Administration (FDA) approval process: the FDA paradigm and reflections on hypothesis testing. , 1999, Controlled clinical trials.

[3]  J Gong,et al.  Estimating significance level and power comparisons for testing multiple endpoints in clinical trials. , 2000, Controlled clinical trials.

[4]  Fach,et al.  Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in-Congestive Heart Failure (MERIT-HF) , 1999, The Lancet.

[5]  P. O'Brien,et al.  A multiple testing procedure for clinical trials. , 1979, Biometrics.

[6]  R J Cook,et al.  Coupled error spending functions for parallel bivariate sequential tests. , 1996, Biometrics.

[7]  N L Geller,et al.  The analysis of multiple endpoints in clinical trials. , 1987, Biometrics.

[8]  B W Turnbull,et al.  Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. , 1993, Biometrics.

[9]  L. Moyé,et al.  End-point interpretation in clinical trials: the case for discipline. , 1999, Controlled clinical trials.

[10]  Nancy L. Geller,et al.  Design of Group Sequential Clinical Trials with Multiple Endpoints , 1989 .

[11]  Eter,et al.  EFFECT OF AMLODIPINE ON MORBIDITY AND MORTALITY IN SEVERE CHRONIC HEART FAILURE , 2000 .

[12]  Danyu Lin,et al.  Nonparametric sequential testing in clinical trials with incomplete multivariate observations , 1991 .

[13]  Anastasios A. Tsiatis,et al.  The asymptotic joint distribution of the efficient scores test for the proportional hazards model calculated over time , 1981 .

[14]  Anastasios A. Tsiatis,et al.  Repeated Significance Testing for a General Class of Statistics Used in Censored Survival Analysis , 1982 .

[15]  L. Fisher Carvedilol and the Food and Drug Administration-Approval Process , 1999 .

[16]  J. Whitehead Supplementary analysis at the conclusion of a sequential clinical trial. , 1986, Biometrics.

[17]  N E Breslow,et al.  Group sequential designs for monitoring survival probabilities. , 1996, Biometrics.

[18]  S. Pocock Group sequential methods in the design and analysis of clinical trials , 1977 .

[19]  E. Gumbel Bivariate Exponential Distributions , 1960 .

[20]  M. Schervish Multivariate normal probabilities with error bound , 1984 .

[21]  D. Cox,et al.  Analysis of Survival Data. , 1986 .

[22]  J. Cohn,et al.  The effect of carvedilol on morbidity and mortality in patients with chronic heart failure. U.S. Carvedilol Heart Failure Study Group. , 1996, The New England journal of medicine.

[23]  K. K. Lan,et al.  Discrete sequential boundaries for clinical trials , 1983 .

[24]  D L Demets,et al.  Group sequential procedures: calendar versus information time. , 1989, Statistics in medicine.

[25]  P. O'Brien Procedures for comparing samples with multiple endpoints. , 1984, Biometrics.

[26]  John Whitehead,et al.  Confidence intervals for secondary parameters following a sequential test , 2000 .

[27]  R J Cook,et al.  Interim monitoring of bivariate responses using repeated confidence intervals. , 1994, Controlled clinical trials.