Bios 101 Lecture 3: Experimental Designs

1. Bios 101 Lecture 3: Experimental Designs Shankar Viswanathan, DrPH. Division of Biostatistics Department of Epidemiology and Population Health Albert Einstein College of Medicine, NY October 11, 2011

2. Analytical Studies has comparison group Grimes et al. Lancet 2002;359:57-61

3. Clinical Trial • Clinical trial: A properly planned experiment and executed clinical trial is a powerful experimental technique for assessing the effectiveness of an intervention. -Friedman, Furer and Demets • A clinical trial • must employ one or more intervention or technique that may be prophylactic, diagnostic or therapeutic agents, devices, regimens, procedures etc. • A clinical trial must contain a control group against which the intervention is compared. • At baseline control group must be similar in relevant respects to intervention group so that differences in outcome may reasonably be attributed to action of intervention.

4. Efficacy and Effectiveness Efficacy Does treatment work under ideal circumstances? EffectivenessDoes offering treatment work under ordinary circumstances? INTERNAL VALIDITY Co-morbidity, age Cooperation Skill of providers Financial barriers GENERALIZABILITY

5. Types of Clinical Trials • Therapeutic trials: A therapeutic agent or procedure is given in an attempt to relieve the symptoms and / or improve the survivorship of those with the disease. • E.g. Laser treatment for diabetic retinopathy, simple mastectomy for breast cancer • Intervention trials:The investigator intervenes before a disease has developed in individuals with characteristics that increase their risk of developing the disease. • E.g. Antihypertensive drug to prevent stroke, physical exercise to decrease MI • Preventive trial:All attempt is made to determine the efficacy of a preventive agent or procedure; these are also referred to as prophylactic trials. • E.g. HPV vaccination to prevent cervical cancer

6. Further Classifications Pre-clinical Studies   Phase I Dose finding  Phase II Preliminary efficacy   Phase III Comparative trial  Phase IV Post-marketing surveillance

7. Phase I Trials: Clinical pharmacology and toxicity • primarily concerned with drug safety, dose finding and schedule of administration • not efficacy and usually performed on healthy human volunteers (sample size ~ 20-80 subjects) • Phase I objectives include • Acceptable single drug dosage • Drug metabolism • Bioavailability • Dose ranging

8. Phase I Trial: Example • Example 1: Industry sponsored phase I trial of R7128 for treatment of chronic hepatitis C. Inhibits HCV RNA polymerase, enzyme necessary for hepatitis C viral replication • Study designed to assess safety, tolerability, pharmacokinetics of R7128. •  Single oral doses were administered to 46 healthy volunteers in five sequential dose groups under fasting conditions and one food effect group. • “Single ascending doses of R7128 were generally safe and well-tolerated…no clinically significant dose-related AEs or laboratory abnormalities. We are pleased with these results and look forward to the continued development of R7128 for HCV”. Slide Courtesy: Dr. Mimi Kim, Ph.D.

9. Phase I trials: Outcomes/Goals • In cancer studies of cytotoxic drugs, • to establish Maximum Tolerated Dose: the highest level of a dose that can be tolerated with an acceptable level of toxicity • Dose Limiting Toxicity (DLT): unacceptable level of toxic response

10. Phase II Trials: initial clinical investigation for treatment effect • Obtain preliminary evidence of efficacy, small-scale investigation into the effectiveness and safety of a drug and screen out ineffective drugs • Require close monitoring of each patient. Approximately 100 – 200 patients on drug • Study:“A Phase II, Open Label, Single Arm Study of the 48-Week Virologic and Immunologic Response to Lopinavir/Ritonavir (Kaletra) as a Single Agent in a Cohort of HIV+ Adult Patients”  • Objective: to conduct a Phase II study to assess the antiviral activity of Kaletra taken twice a day in antiretroviral-naïve HIV patients   • Target enrollment: 40 patients  • Primary outcome: Proportion of patients with plasma HIV-1 RNA < 400 copies/ml at week 48 Slide Courtesy: Dr. Mimi Kim, Ph.D.

11. Phase II Trials: Designs • Single Stage Design • Enroll Npatients •  If Rresponses  treatment ineffective  • If > R responses  treatment is effective • Two Stage Designs: Allow for early stopping for lack of efficacy Simon 2-stage Design (Simon, R. Optimal two-stage designs for phase II clinical trials. Controlled Clinical Trials 10: 1-10, 1989)  • Terminates at first stage if treatment appears ineffective  • Does not permit early stopping for efficacy •  Have to determine sample sizes of two stages and decision rules Slide Courtesy: Dr. Mimi Kim, Ph.D.

12. Phase III Trials • To compare (evaluate) the drug with the current standard treatment (s) for the same condition in a large trial involving substantial number of patient • Ideal clinical trial includes both randomization of subjects and blinding of subjects and care providers • Objective (Type) of Trial • Superiority , Equivalence, Non-inferiority, Bio-equivalence

13. Phase III Trials: Objective • Superiority: To demonstrate whether there is evidence of a statistical difference in comparison of interest between the drugs • Equivalence: To demonstrate that two (more) treatments have no clinically meaningful difference i.e. they are equivalent • Non-inferiority:To demonstrate that a given treatment is not clinicallyinferior compared to another i.e. they are equivalent Julious, Sample size for clinical trials, 2010

14. Phase III Trials: Designs • Parallel or concurrent • Cross-over designs • Factorial designs • Other experimental designs • 2k experimental designs • Sequential or adaptive designs (interim analysis) • Group randomized designs Slide Courtesy: Dr. Mimi Kim, Ph.D.

15. Poor designs • Historical controls • Controls obtained from the literature, registries or databases • Subject to great potential biases • Changes in subject identification and patient management • Disease evolution and trends • Technological improvements in measurement and diagnosis • Accuracy and completeness of control data • Testing lacks statistical validity

16. Poor designs • Nonrandomized concurrent controls • Two separate institutions concurrently performing the study using different interventions • Subject to non-comparability of the groups • Testing lacks statistical validity as not-randomized  Almost always a randomization process must be used in assigning subjects to the intervention arms

17. Most basic design of a clinical trial 2-arm parallel Event Target population Group A No event Consenting eligible Randomization Event Group B No event

18. Cross-over design Event Event Int. A Consenting eligible Int. B No event No event Randomization Wash-out Event Event Int. B Int. A No event No event All interventions are administered to all subjects at different times

19. Cross-over design • Advantages • Can lead to increased precision and efficiency • Each subject functions as their own control • Variability within a subject is less than among subjects • In the absence of a carry-over effect, it is more efficient • If responses among subjects are positively correlated, the intervention comparison statistics will have lower variability

20. Cross-over design • Advantages • Can help recruitment and adherence • All subjects receive the ‘active’ intervention • If the control intervention is placebo, subjects may be willing to participate since if assigned to placebo, essentially only ‘delaying active intervention’

21. Cross-over design • Limitations • Carry-over effects must be considered in the design (by including a wash-out period) and in the analysis • May not be feasible • Carry-over effects are confounded with the intervention*period interaction • Studies last longer • May not be feasible • Increased chance of adverse events, drop-outs

22. Factorial design • Considered when have multiple possible interventions • Considered when have an interest in the interaction between interventions • All interventions are systematically applied

23. Factorial design Actually just like a parallel design A no, B no A no, B yes 4 n eligible A yes, B no A yes, B yes

24. Factorial design • Advantages • In the absence of interactions, we increase the efficiency of the trial to study the main effects of each of the interventions • It is the only trial design that permits studying the interactions of the interventions

25. Factorial design • Limitations • Interventions must have different mechanisms of action (modalities) • Interventions must be able to be administered jointly • Without modification • Without cumulative adverse effects • Should be ethical to administer the ‘no-no’ • There should be an interest in studying the interaction (synergistic) effect of the two interventions

26. Example: Morgan & Anderson (2002) Amer J Hypert • Combination cross-over and factorial design Randomization

27. Example: Morgan & Anderson (2002) Amer J Hypert • Factorial aspect • A=placebo • B=Felodipine • C=Candesartan • D=Felodipine+Candesartan • Cross-over aspect • Subjects receive all 4 possible interventions • Requires appropriate wash-out periods

28. Randomization • Objective (unbiased) approach to assignment • Remove allocation control from the investigator • Add credibility – impartiality, non-discoverable assignment • Make groups comparable at baseline • On known prognostic factors - covariates or potential confounders • On unknown factors • Make statistical testing valid • Quantify errors attributable to chance

29. Randomization • Simple - unconstrained • Constrained • Blocks • Stratified • Clustered • Adaptive

30. Masking • Make sure randomization is done fairly • Discourage bias after randomization • Increase chances that subjects will stay in randomized groups • Not have to depend on good intentions • Single blinding / masking: (Subjects) : prevent participant from introducing bias into the observations, and is usually accomplished by means of a placate • Double blinding (Subjects & Investigator): seeks to remove biases that occur as a result of either subject or the investigator of the subject. • Triple blinding: Subjects, investigator of the subject and the person analyzing the data are all masked with regard to the group to which a specific individual belongs.

31. Masking • Desirable: makes many biases impossible • Not always possible • When tried, not always successful

32. Types of Analysis • Intention to treat analysis: compares outcomes according to initial group assignments. • Per Protocol analysis: compares outcomes only in those subjects who appear to be compliant • As treated analysis: compares observed outcomes according to the treatment received.