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RANDOMIZED CONTROLLED TRIAL. Instructor : Fabrizio D’Ascenzo fabrizio.dascenzo@gmail.com www.emounito.org www.metcardio.org Role MD. CONFLICT OF INTEREST. None. AIM OF THE COURSE. A critical appraisal Theorical Practical of RCT. SOME HISTORY.
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RANDOMIZED CONTROLLED TRIAL Instructor: Fabrizio D’Ascenzo fabrizio.dascenzo@gmail.com www.emounito.org www.metcardio.org Role MD
CONFLICT OF INTEREST None
AIM OF THE COURSE A critical appraisal • Theorical • Practical of RCT
SOME HISTORY - 600 B.C.:Daniel of Judah compared the health effects of the vegetarian diet with those of a royal Babylonian diet over a 10-day period. (Book of Daniel 1:1–21) -1952 The Medical Research Council trials on streptomycin for pulmonary tuberculosis are rightly regarded as a landmark that ushered in a new era of medicine. (Hill AB. The clinical trial. N Engl J Med 1952; 247:113–119)
RANDOMIZED • It prevents selection bias and insures against accidental bias. • It produces comparable groups, and eliminates the source of bias in treatment assignments.
RANDOMIZATION • It permits the use of probability theory to express the likelihood of chance as a source for the difference between outcomes. • It facilitates blinding (masking) of the identity of treatments from investigators, participants, and assessors, including the possible use of a placebo
RANDOMIZATION • Produces groups that are not systematically different with regard to known and unknown prognostic factors • Permits a valid analysis • Permutation test is justified by randomization • Standard analyses are valid approximations of the correct permutation test
CRUCIAL CONCEPTS • PHASE • STRUCTURE • SUPERIORITY AND INFERIORITY • RANDOMIZATION • BLINDING • SAMPLE SIZE • AD INTERIM ANALYSIS • ITT VS AT • SUBGROUP ANALYSIS
PHASE Phase I trials Objective to determine a safe drug dose Design usually dose escalation/de-escalation Subjects healthy volunteers or patients with disease Phase II trials Objective to determine a safe drug dose Design often single arm Subjects patients with disease Phase III trials Objective to compare efficacy of the new treatment with the standard regimen Design usually randomized control Subjects patients with disease
STRUCTURE • Parallel group • Cluster randomized • Crossover • Factorial
PARALLEL Most randomized controlled trials have parallel designs in which each group of participants is exposed to only one of the study interventions.
CLUSTER RANDOMIZED A cluster randomized trial is a trial in which individuals are randomized in groups (i.e. the group is randomized, not the individual).
CROSSOVER This design, obviously, is appropriate only for chronic conditions that are fairly stable over time and for interventions that last a short time within the patient and that do not interfere with one another.
CROSSOVER Removing patient variation in this way makes crossover trials potentially more efficient than similar sized, parallel group trials in which each subject is exposed to only one treatment In theory treatment effects can be estimated with greater precision given the same number of subjects.
CROSSOVER The principal drawback of the crossover trial is that the effects of one treatment may “carry over” and alter the response to subsequent treatments. The usual approach to preventing this is to introduce a washout (no treatment) period between consecutive treatments which is long enough to allow the effects of a treatment to wear off.
FACTORIAL DESIGN two or more experimental interventions are not only evaluated separately but also in combination and against a control
FACTORIAL DESIGN Itallows evaluation of the interaction that may exist between two treatments.
FACTORIAL DESIGN two or more experimental interventions are not only evaluated separately but also in combination and against a control
SUPERIORITY AND INFERIORITY • FDA’s regulations on adequate and well-controlled studies (21 CFR 314.126) describe four kinds of concurrently controlled trials that provide evidence of effectiveness. • Three are superiority controlled trials: • placebo • no treatment • dose-response controlled trials
SUPERIORITY A properly designed and conducted superiority trial, is entirely interpretable without further assumptions (other than lack of bias or poor study conduct)
INFERIORITY The difference between the new and active control treatment is enough to support the conclusion that the new test drug is also effective
INFERIORITY LIMIT M 1 = the largest clinically acceptable difference (degree of inferiority) of the test drug compared to the active control
INFERIORITY LIMIT • The critical problem, and the major focus of this guidance, is determining M 1 , which is not measured in the NI study (there is no concurrent placebo group). • It must be estimated (really assumed) based on the past performance of the active control and by comparison of prior test conditions to the current test environment
INFERIORITY LIMIT • One approach is to specify the equivalence margin on the basis of a clinical notion of a minimally important effect. BUT clearly subjective • The equivalence margin is often chosen with reference to the effect of the active control in historical placebo-controlled trials.
INFERIORITY LIMIT Someones claims that a positive noninferiority trial implies that the new treatment is superior to placebo. However, this claim requires an assumption that the effect of the active control in the current trial is similar to its effect in the historical trials.
INFERIORITY LIMIT Differences with respect to design features or by an inconsistency in the effect of the active controls among the historical placebo-controlled trials (beyond that expected by random chance) > is often based on the lower bound of a confidence interval for that effect(accounting for within-trial and trial-to-trial variability)
LIMIT OF INFERIORITY • Non-inferiority studies are not conservative in nature since limits in the design and conduct of the study will tend to bias the results towards a conclusion of similarity. • Poor compliance with the study medication, poor diagnostic criteria, excessive variability of measurements, and biased end-point assessment.
RANDOMIZATION 1- To conceal 2- To generate
TO CONCEAL Allocation concealment prevents investigators from influencing which participants are assigned to a given intervention group > Increasing risk of selection bias
Evidence shows that reports of trials reporting inadequate allocation concealment are associated with exaggerated treatment effects
TO GENERATE Use of computer or random number table http://www.randomization.com/
TO GENERATE Balanced randomisation involves selecting certain baseline covariates (called balancing variables) and incorporating them into the randomisation scheme in a way
SIMPLE (UNRESTRICTED) RANDOMISATION No other allocation generation approach, irrespective of its complexity and sophistication, surpasses the unpredictability and bias prevention of simple randomisation.
SIMPLE (UNRESTRICTED) RANDOMIZATION With small sample sizes, simple randomisation (one-to-one allocation ratio) can yield highly disparate sample sizes in the groups by chance, although becoming negligible with trial sizes greater than 200. BUT However, interim analyses with sample sizes of less than 200 might result in disparate group sizes.
RESTRICTED RANDOMISATION It controls the probability of obtaining an allocation sequence with an undesirable sample size imbalance in the intervention groups
BLOCKING METHODS Blocks may be fixed or variable If the block size is fixed, especially if small (six participants or less), the block size could be deciphered in a not double-blinded trial. Longer block sizes—eg, ten or 20—rather than smaller block sizes—four or six—and random variation of block sizes help preserve unpredictability.
RANDOM ALLOCATION RULE For example, for a total study size of 200, placing 100 group A balls and 100 group B balls in a hat and drawing them randomly without replacement symbolises the random allocation rule. It is usually reported as use of envelopes
LIMITS OF RANDOMIZATION Balanced randomisation introduces correlation between treatment groups, which violates the statistical assumption that all patients are independent
Balanced (simple) randomisation forces the outcomes between treatment arms to be similar (apart from any treatment effect)