Clinical Trial Designs

Abstract

“To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination - he may be able to say what the experiment dies of.” R.A. Fisher The delivery of an intervention whether drug, a dietary change, a lifestyle change, or a psychological therapy session counts as an intervention and hence must be dealt as a clinical trial [Figure 1]. Clinical trial design is an important aspect of interventional trials that serves to optimize, ergonomise and economize the clinical trial conduct. The purpose of the clinical trial is assessment of efficacy, safety, or risk benefit ratio. Goal may be superiority, non-inferiority, or equivalence. A well-conducted study with a good design based on a robust hypothesis evolved from clinical practice goes a long way in facilitating the implementation of the best tenets of evidence-based practice. A robust well-powered trial adds to the meta-analyzable evidence base and contributes huge quanta to our knowledge of dermatological practice. This article sets out to describe the various trial designs and modifications and attempts to delineate the pros and cons of each design and attempts to provide illustrative samples for the same where possible.Figure 1: Basic framework of clinical trialsUncontrolled Trials This design incorporates no control arm. This design is usually utilized to determine pharmacokinetic properties of a new drug (Phase 1 trials). Uncontrolled trials are known to produce greater mean effect estimates than a controlled trial, thereby inflating the expectations from the intervention. There is a threat of inherent bias and results are considered less valid than RCT. Another issue is use of this design in spontaneously resolving maladies that might again overstate the effect [Figure 2].Figure 2: Single arm trial schematicIllustrative example In immunotherapy in warts, it is imperative to avoid an uncontrolled study. Warts can be self-resolving and hence the efficacy of immunotherapy as opposed to the self-resolution compromises the validity of the results. Control Arm Options in Controlled Trials Controlled trials allow discrimination of the patient outcome from an outcome caused by other factors (such as natural history or observer or patient expectation). Choosing a right control at the right dose and right frequency is pivotal to trial success. The controls which can be used are: Placebo concurrent control – Placebo is a form of inert substance, or an intervention designed to simulate medical therapy, without specificity for the condition being treated. The placebo must share the same appearance, frequency, and formulation as the active drug. Placebo control helps to discriminate outcomes due to intervention (new product) from outcomes due to other factors. This design is used to demonstrate superiority or equivalence. This design must be adopted only when no effective treatment exits, and it will be deemed unethical to use a placebo control if an effective standard of care exits. Placebo must only be used if no permanent harm (death or irreversible morbidity) accrues by delaying available active treatment for the duration of the trial and is preferable for a minimal risk, short-term study “No treatment” concurrent control – No intervention will be administered in control arm in this design. Study end points must be objective in this design. The downsides are potential for observer bias and difficulty in blinding in this design Active treatment concurrent control – This design involves comparison of a new drug to a standard drug or compare combination of new and standard therapies vis a vis standard therapy alone. A therapeutic modality that should preferably be the current standard of care against which the active drug to be studied is compared with. This design can be used to demonstrate equivalence, non-inferiority, and superiority. This design is most ethical whenever approved drugs are available for the disease under study. The Declaration of Helsinki mandates the use of standard treatment as controls Dose-comparison concurrent control – Different doses or regimens of same treatment are used as active arm and control arm in this design. The purpose is to establish a relationship between dose and efficacy/safety of the intervention. This design may include active and placebo groups also in addition to the different dose groups. This design may be inefficient if the therapeutic range of the drug is not known Historical control (external and non-concurrent) – Source of controls are external to the present study and were treated at an earlier time (earlier therapeutic gold standard) or in a different setting. The advantage of historical controls is in studying rare conditions where sample size generation is difficult. The downside is that no randomization or blinding is possible in this design. A disadvantage is that the co-interventions evolve in due course of time thereby reducing the comparability of the present intervention versus historic control. Another deficiency of this design is the difference between baseline characteristics of subjects in trial arm versus historical arm. For example, toxic epidermal necrolysis, where clinical outcomes in cyclosporine treated patients can be compared with historical controls treated in the same center with IVIg in the past. Variants of Placebo Controlled Trial Designs Add-on design – This design denotes a placebo-controlled comparison on top of a standard treatment given to all patients. If the improvement that is achievable in addition to that obtained from the standard treatment is small, the size of such trial may need to be very large Early escape design – The early escape design using a placebo control allows a patient to be withdrawn from the study as soon as a predefined negative efficacy criterion has been attained. This reduces the time on placebo or in treatment failure. This design analyses failure rate, so minimizes exposure to ineffective treatment. The time for withdrawal is then used as the primary outcome variable. The patient could then be switched over to another therapy, including the test treatment if appropriate. The attendant limitations are sacrifice of study power with increased “escape” cases and evaluation of only short-term efficacy. If the drug has a slow and deliberate effect on long-term use then that might be missed in this design Unbalanced assignment of patients to placebo and test treatment. By this design it is implied that a smaller number of patients could be assigned to the placebo group compared to the test treatment group (e.g., 2/3 case arm, 1/3 placebo arm) Double-dummy design [Figure 3] – This design is of great utility if the comparator interventions are of different natureIllustrative example – Comparison of oral acitretin versus injection purified protein derivative (PPD) in extensive verruca vulgaris. So, blinding of patients is not feasible in this scenario. But this issue can be circumvented by administering acitretin orally with a dummy injection like normal saline to one study group and injection PPD along with placebo capsule identical in size and appearance to the acitretin capsule to the comparator armPlacebo run-in design – Placebo run-in period is a period before a clinical trial is commenced, when placebo is administered for all study subjects. The clinical data from this stage of a trial are only occasionally of value but can serve a valuable role in screening out ineligible or non-compliant participants, in ensuring that participants are in a stable condition, and also helps in providing baseline observations. After the run-in phase, randomisation is done, patients are randomized into study arms where different active interventions are added to the placebo in each study arm [Figure 4]. Figure 3: Double dummy trial designFigure 4: Run in designRandomized Clinical Trials (RCT) In randomized controlled trials, trial participants are randomly assigned to either treatment or control arms. The process of randomly assigning a trial participant to treatment or control arms is called “randomization”. Different tools can be used to randomize (closed envelopes, computer generated sequences, random numbers). There are two components to randomization: the generation of a random sequence and the implementation of that random sequence, ideally in a way that keeps participants unaware of the sequence (allocation concealment). Randomization removes potential for systematic error or bias. The biggest upside of an RCT is the balancing of both the known and unknown confounding factors which leads to wrong conclusions. Randomization Schemes in Randomized Controlled Trials to Eliminate Confounding Factors Stratified randomization – This refers to the situation in which strata are constructed based on values of prognostic variables and a randomization scheme is implemented separately within each stratum. The objective of stratified randomization is to ensure balance of the treatment groups with respect to the various combinations of the prognostic variables. This method can be used to achieve balance among groups in terms of subjects' baseline characteristics (covariates). Specific covariates must be identified by the researcher who understands the potential influence each covariate has on the dependent variable. To avoid strata with very less patients, the number of strata should be kept minimum. After all the subjects have been identified and assigned into strata, simple randomization is performed within each stratum to assign subjects to either case or control groups Block randomization – Blocking is the arranging of experimental units in groups (blocks) that are similar to one another. Typically, a blocking factor is a source of variability that is not of primary interest to the experimenter. An example of a blocking factor might be the sex of a patient; by blocking on sex, this source of variability is controlled for, thus leading to greater accuracy. The block randomization method is designed to randomize subjects into groups that result in equal sample sizes. This method is used to ensure a balance in sample size across groups over time. Blocks are small and balanced with predetermined group assignments, which keeps the numbers of subjects in each group similar at all times Randomization by body halves or paired organs (Split Body trials) – This is a scenario most often used in dermatology and ophthalmic practice where one intervention is administered to one half of the body and the comparator intervention is assigned to other half of the body. This can be implemented only if experimental treatment acts locally. Randomization is used to select which side of the body receives which drug. The upside is the elimination of confounding factors between trial arms, as the baseline characteristics of both arms are the same. The downside is difficulty in blinding the investigator, statistical analysis, and influence of therapy administered in one half of the body influencing disease on the other side as the halves of the human body is a continuum and not entirely independent entities (carryover of the experimental treatment to control half). Allocation between paired organs/split skin can obscure systemic adverse events. Paired data statistical analytic tests need to be done in this scenario Cluster randomization – Study patients and treating interventionists do not exist in isolation. Sometimes interventions need to be applied at ward level, village level, hospital level, or group practice level. Hence intervention is administered to clusters by randomization to prevent contamination. Each cluster forms a unit of the trial and either active or comparator intervention is administered for each cluster Allocation by randomized consent (Zelen trials) – Eligible patients are allocated to one of the two trial arms prior to informed consent. This is utilized when informed consent process acts as an impediment to study subject accrual. However, this design raises serious ethical uncertainties and must only be used in severely flagging trials in terms of insufficient sample size of great public health importance and is not recommended in routine clinical trial design Minimization – Stratification based on multiple co-variates (age, sex, gender, baseline severity of disease, personal habits, co-morbidities, treatment naivety, etc.) leads to excessive number of strata with smaller number of patients at times in each strata. Hence, an alternate strategy to control for prognostic variables to avoid such small strata is minimization. After identification of these variables, they are dichotomized at some break point in case of continuous variables or based on presence or absence of a categorical variable. Then each dichotomized half is given a value of 0 or 1 (e.g., male = 0, female = 1; age <50 years = 0, age >50 years = 1). Thus, in a female of age 55, the total will be 1 + 1 = 2. A male of age 65 will be allocated 0 + 1 = 1 point, a female of age 45 will have score of 1 + 0 = 1 point, etc. For example, patient number 1 with score 2 is randomized to control arm. Patient no. 2 has 1 point and to minimize the difference in total scores between the study arms, he is allocated to case arm. So now the control arm total score is 2 and case arm score is 1. Patient 3 is a female with score 1 and will be allocated to case arm and thus the cumulative score in both groups will be balanced at 2 points. Once the running scores in both arms are tied, the next recruited subject is again randomly allocated and the whole cycle repeats. Thus, minimization is a viable alternative to randomization for known prognostic factors, but does not factor in the unknown prognostic confounding variables. Hence, it can be considered a platinum standard to the gold standard of random allocation. RCT Designs a. Parallel group trial design Parallel arm design is the most commonly used study design. In this design, subjects are randomized to one or more study arms and each study arm will be allocated a different intervention. After randomization each participant will stay in their assigned treatment arm for the duration of the study [Figure 5]. 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