Introduction to Clinical Trials Afshin Ostovar Bushehr University of Medical Sciences Bushehr, 2011
Research Design Epidemiology • Descriptive Studies • Case Reports • Case Series • Cross Sectional Survey • Analytic Studies • Observational Studies • Case-Control or Case-Comparison • Cohort Studies • Intervention Studies • Clinical Trials
Definition • A clinical trial is defined as a prospective study comparing the effect and value of intervention(s) against a control in human beings. • They need not all be followed from an identical calendar date. In fact, this will occur only rarely. Each participant, however, must be followed from a well-defined point, which becomes time zero or baseline for the study.
Definition “cont’d” • A clinical trial must employ one or more intervention techniques. These may be "prophylactic, diagnostic or therapeutic agents, devices, regimens, procedures, etc.“ • Intervention techniques should be applied to participants in a standard fashion in an effort to change some aspect of the participants. • Follow-up of people over time without active intervention may measure the natural history of a disease process, but it does not constitute a clinical trial. Without active intervention the study is observational because no experiment is being performed.
Definition “cont’d” • A clinical trial must contain a control group against which the intervention group is compared. • At baseline, the control group must be sufficiently similar in relevant respects to the intervention group so that differences in outcome may reasonably be attributed to the action of the intervention. • Most often a new intervention is compared with best current standard therapy. If no such standard exists, the people in the intervention group may be compared with people who are on no active intervention. "No active intervention" means that the participant may receive either a placebo or no intervention at all.
Counterfactual concept • The effect of any treatment for a given patient is the difference between what happened to the patient as a result of giving the treatment and what would have happened had treatment been denied. (counterfactual view)
Phases of Clinical Trials • Phase I • Phase II • Phase III • Phase IV
Case series Before After Intervention
Parallel Group Designs Randomization
Parallel Group Designs (Adventages) • Simple and easy to implement • Universally accepted • Applicable to acute conditions • Analysis is less complicated and interpretation of the results is straightforward
Parallel Group Designs (Types) • Group comparison (parallel-group) design • Two-group design For ethical consideration with control (placebo), we can allocate patients unequally to treatment groups (at random) to allow more patients to receive the treatment. • Three-group design • Matched pairs parallel designs • Power increased • Two drawbacks: • The prognostic characteristics are not easily defined • Patient recruitment is usually slow
Parallel group designs (run in periods) • Advantages • Acts as a washout period to remove effects of previous therapy • Can be used to obtain baseline data and to evaluate if patient fulfills study entry criteria • Can be used as a training period for patients and investigators • Helps in identifying placebo responders • Provides useful information regarding patient compliance • Disadvantage: • Increases the length of a study: • Extra visit and costs • Decreases in enthusiasm of patients and investigators
Crossover Designs • A crossover design is a modified randomized block design in which each block receives more than one treatment at different periods. • A p × q crossover design: there are p sequences of treatments administered at q different periods
Standard 2 × 2 Crossover Design washout
Crossover Designs Advantages: • Allows within-patients comparisons of treatments • Removes intrapatient variability • Provides the best unbiased estimates for the differences between treatments • Decreases number of patients needed
Factorial Design Treatment A + - + Treatment B -
Factorial Design Two applications: • Quantifying the interaction between the two treatments • Opportunistic situations Treatments groups: AO BO AB OO
Designs with ethical considerations • Adaptive Randomization • Zelen design • Variations of placebo-controlled trials: • Add-on design • Replacement design • Randomized Withdrawal design • Sequential analysis
Multicenter trials • The limitations of patient population in a single center and/or sources and capacity in a single center make a multicenter trial justified. • A multicenter study is a single study involving several study centers. The data collected from these centers are intended to be analyzed as a whole. • At each center an identical study protocol is used. A center or site is considered a natural blocking or stratified variable. • A rule of thumb is that the number of patients in each center should not be less than the number of centers
The Randomization Process • The randomized clinical trial is the standard by which all trials are judged • In the simplest case, randomization is a process by which each participant has the same chance of being assigned to either intervention or control
Purposes of Randomization • To generate comparative groups • To enable valid statistical tests
Blindness • Open label (unblinding) • Single blinding (patients only) • Double blinding (patients and investigators) • Triple blinding (patients and investigators and Monitoring investigators)
Classic classification of Randomization • Simple • Systematic • Balanced block • Stratified
Complete randomization(Simple randomization) • Random allocation It is a form of restricted randomization It randomly selects the N/2 out of a total of N patients without replacement and assigns these N/2 patients to receive the test drug and the other half to receive the placebo.
Permuted block randomization(Balanced block randomization) • One of the major disadvantages of simple randomization is that treatment imbalance can occur periodically • If the demographic factors or baseline characteristics change over time, it is quite possible to have a serious covariate imbalance between treatment groups.
Treatment adaptive randomization • The Treatment adaptive randomization adjusts for the assigning probability of the current patient with respect to the number of patients who have been randomized to each treatment group. • Methods: • biased coin randomization • A constant assigning probability is used during the entire course of the study • Urn randomization • The probability of the assignment of the current patient is a function of the current treatment imbalance • It requires a much more complicated analysis
Steps in Analysis • Baseline data analysis • Main analysis • Protocol deviation • Intention to treat and per protocol approaches • Covariates analysis • Multiple outcomes analysis • Subgroup analysis • Multiplicity in analysis of clinical trials
Baseline Data Analysis • To: • Check generalizability • Check comparability of treatment groups • The variables should be considered: • The characteristics of the disease (type, severity, duration, …) • Prognostic variables • Other coincidence diseases • Previous treatments • Use of statistical tests!
Main analysis • Three approaches: • Outcome analysis • Change score analysis • Analysis of Covariance (ANCOVA)
Covariates analysis • Covariate = prognostic factor = confounder • In the case where covariates are not balanced between the treatment groups, to obtain a valid inference of treatment effect, it is necessary to adjust for covariates • An adjustment of covariates not only provides unbiased statistical inference but also increases precision of the statistical inference
Study Protocol • The study protocol can be viewed as a written agreement between the investigator, the participants, and the scientific community. • The contents provide the background, specify the objectives and describe the design and organization of the trial. • Every detail explaining how the trial is carried out does not need to be included, provided that the comprehensive manual of procedures contains such information.
Study Protocol • The protocol serves as a document to assist communication among those working in the trial. • It should be also be made available to others on request. • The protocol should be developed before the beginning of participant enrollment and should remain essentially unchanged except perhaps for minor updates.
Study Protocol • Careful thought and justification should go into any changes. • Major revisions that alter the direction of the trial should be rare. • If they occur, the rational behind such changes need to be clearly descried.
A. Background of the study 1. Reviewing the related articles. 2. Why is the results of this trial needed? 3. How does the study provide evidence for decision making?
B. Objectives • Primary question and response variable • Secondary question and response variables • Subgroup hypothesis • Adverse effects
C. Design of the study • Study population • Inclusion criteria • Exclusion Criteria
Population Without Condition Definition of Condition With Condition But Ineligible Entry Criteria Eligible But Not Enrolled Enrollment
C. Design of the study 2. Sample Size assumptions and estimates
C. Design of the study 3. Enrollment of participants • Informed consent • Assessment of eligibility • Baseline examination • Intervention allocation (e.g., Randomization method)
C. Design of the study 4. Intervention • Description and schedule • Measures of compliance
C. Design of the study 5. Follow-up visit description and schedule
C. Design of the study 6. Ascertainment of response variables • Training • Data collection • Quality control
C. Design of the study 7. Data analysis • Interim monitoring • Final analysis
C. Design of the study 8. Termination policy
D. Organization 1. Participating Investigators • Statistical unit or data coordinating center • Laboratories and other special units • Clinical center(s)
D. Organization 2. Study administration • Steering committees and subcommittees • Data monitoring committee • Funding organization
Appendix • Definitions of eligibility criteria • Definition of response variables
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