3. Fixed-sample Clinical Trial Design

Transcription

1 3. Fixed-sample Clinical Trial Design Review of course organization 1. Scientific Setting 1.1 Introduction and overview 1.2 Phases of investigation 1.3 Case Study 2. From scientific setting to statistical design 2.1 Refining the scientific questions to statistical hypotheses 2.2 From statistical hypotheses to scientific decisions 2.3 Case study 3. Fixed-sample clinical trial design 3.1 On choosing the sample size 3.2 Frequentist evaluation of a fixed-sample trial 3.3 Case study 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 1

2 4. Group sequential clinical trial design 4.1 Interim analyses (motivation) 4.2 Group sequential stopping rules 4.3 Group sequential design families 4.4 Frequentist evaluation of sequential trials 4.5 Bayesian evaluation of sequential trials 4.6 On the use of stochastic curtailment 4.7 Case study 5. Development of a study protocol 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 2

3 3. Fixed-sample Clinical Trial Design 3.1 On Choosing the Sample Size 3.2 Frequentist Evaluation of a Fixed-Sample Clinical Trial 3.3 Case study 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 3

4 (i) Importance of adequate information (ii) Key elements of information (iii) Evaluation of information (iv) Addressing inadequate information 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 4

5 (i) The importance of adequate information A trial requires adequate information to answer the design questions (i.e., to inform science and clinical practice). Without adequate information the trial cannot answer the relevant questions. A trial that cannot answer the design question is not ethical. 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 5

6 (ii) Key elements of information: Information is often measured by: Confidence interval width Power Fisher information: N/σ 2. Sample size equation contains key elements of information: ( ) zα + z 2 β N = V θ + θ Sample size (N): Number of subjects in the trial. Variance (V ): Inherent variability ( noise ) in the outcome measure. Statistical and scientific operating characteristics: Specificity (z α): statistical standard for evidence. Sensitivity (z β ): power 6 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10

7 Smallest important difference (θ+ θ 0 ): Variously defined as: Smallest important effect: Smaller differences are not clinically important. Most likely effect: Anticipated effect based on past experience in a disease setting. Effect observed previously: Magnitude observed in an earlier study. Self-designing trials: Alter θ + θ 0 based on observed effects in the midst of the current trial. Detectable difference: θ + θ 0 is often called the detectable difference. 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 7

8 (iii) Evaluation of information Frequentist: Power Design alternative hypothesis with power β Sample size Bayesian: Predicted power Sample size (Loss functions in decision-theroetic constructions) Scientific: Confidence interval width (97.5% power point) Sample size in relation to previous studies. 3. Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10 8

9 (iv) Addressing inadequate information During trial design (before trial starts) Reduce variability: Standardize endpoint measurement procedures Central endpoint adjudication Reduce non-compliance with a carefully-selected study population Increase sample size: Expand the number of centers participating in the trial. Large simple trial : fewer measurements on more people. Time-to-event trials: increase duration to get more events. Increase retention: The best retention plan is a good recruitment plan. Reduce participant burden. Allow treatment termination, but retain for measurement. Change endpoints: Use a different endpoint with higher power. This likely means changing the scientific objectives Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10

10 (iv) Addressing inadequate information During trial conduct (after trial starts) Routine problems: Poor recruitment: Many trials fail due to poor recruitment Excessive dropout or loss to follow-up: May also introduce bias Excessive non-compliance: May inflate variation Solutions that preserve the scientific design: Expand recruitment efforts Expand the trial to other centers Fix problems with retention Extend the planned trial duration to allow additional recruitment Solutions that may alter the scientific design: Change eligibility criteria: This will alter the study population and could render the trial uninterpretable. Change treatments to encourage recruitment (esp. control treatment) Institute ancillary treatments to improve tolerability and retention Fixed-Sample Design () 3.1 On Choosing the Sample Size 28 Feb / 10