Randomized Clinical Trial

RCTs (see Controlled and Uncontrolled Clinical Trials) are studies in which participants are assigned to either an experimental or a control group at random. Randomization (also known as randomization in the United Kingdom and the United States) assures that neither the patient nor the doctor is aware of the treatment assignment prior to the procedure. In RCTs, the only difference between the control and experimental groups should be the variable outcome under research. Randomized Clinical Trial is recognized as one of the highest standards of evidence in clinical practice due to their high degree of confidence and robustness in data production.

RCTs are often used to assess the efficacy or effectiveness of a therapy in terms of:

  • Superiority: determining if a new treatment is superior to a placebo or a standard intervention.
  • Non-inferiority: The innovative treatment is not worse than a placebo or a standard therapy.
  • Equivalence is identical to non-inferiority, except that the innovative intervention is assumed to be no better than a placebo or a traditional intervention. Multiple treatment methods, doses, or intensities of the same therapy may be compared against no treatment or a placebo in these studies.

RCT designs are growing increasingly diverse as new methodologies are proposed to evaluate more complex scientific hypotheses. The majority of trial components in traditional RCTs, such as randomization assignments and the number of research arms, stay unchanged throughout the trial. Adaptive designs, in which data acquired during testing is used to change a test component, are gaining favor. These designs may allow patients to be enrolled in one of the treatment groups with the worst results while simultaneously adding more patients to the arm that seems to be more promising.

The Advantages of RCTs

  • Good randomization can remove any demographic bias.
  • They are easier to blind or hide than observational studies.
  • The results may be analyzed using well-known statistical tools.
  • Individuals who take part are categorically identified in their populations.

The drawbacks of RCT

  • They are expensive in terms of both time and money.
  • The participating population is “selected” by definition, distinguishing it from real clinical practice and maybe not representing the whole community.
  • They are carried out in a clinical trial environment, which obviously differs from the context in which the general population receives their usual therapy (more specialized, greater patient control, and more intensive results in the visits made). They cannot, however, be generalized or compared to a general practice setting.
  • A drop in follow-up might be due to the course of treatment.

The Most Common Randomization Techniques

The use of a randomization list allows the researcher to assign therapies to patients based on a random list of numbers, without always knowing which therapy corresponds to which number. There are computer programs that generate these kind of lists that meet this condition.

Stratified randomization is a strategy that allows researchers to compare variables across study groups. The main objective is to try to avoid large differences in patient characteristics across treatment groups. In this kind of randomization, you must carefully choose which patient attributes to stratify. This method should not be used in studies with a high number of patients or where interim data review is impossible or irrelevant.

When the necessary instruments to fully monitor the randomization are not available, there is a risk of error.
when it is unknown which patient characteristics will influence how they react to treatment.

Unequal randomization: This unusual technique includes randomly assigning more patients to the experimental treatment group than to the control group in a 2: 1 or 3: 2 ratio. The distinction is that we are interested in gaining experience and learning more about the unique treatment. This randomization is permissible in clinical research as long as the discrepancy does not impair the statistical efficacy of the treatment comparison. It is sometimes used in research comparing more than two treatments.

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