Randomized controlled trial
"A clinical trial is defined as a prospective scientific experiment that involves human subjects in whom treatment is initiated for the evaluation of a therapeutic intervention. In a randomized controlled clinical trial, each patient is assigned to receive a specific treatment intervention by a chance mechanism." The theory behind these trials is that the value of a treatment will be shown in an objective way, and, though usually unstated, there is an assumption that the results of the trial will be applicable to the care of patients who have the condition that was treated.
Medical research answers many questions about health, illness, and treatment options. Evaluating new medicines and other treatments may involve research using randomized controlled trials [(RCT)]. In such trials the participants who receive the treatment under study are assigned [to different treatments] at random (by chance, like the flip of a coin). This is necessary to ensure that the outcomes are determined only by the treatment under study and not by other factors that could otherwise influence treatment assignment. Other participants who, by the randomization process, serve as controls receive a standard treatment or placebo treatment (a pill or procedure that does not include active ingredients).
Trials of potential treatments, for ethical reasons, tend to involve multiple stages, starting with small safety tests of the drug or other therapy. Once there is evidence of safety, and preliminary clinical trials, the effort moves to a larger scale: large multicentre clinical trials that are randomized, controlled, and double-blind using a control group of patients (i.e., "arm" of the trial) and an experimental arm.
Trials should be large, so that serious adverse events might be detected even when they occur rarely. Multi-centre trials minimize problems that can arise when a single geographical locus has a population that is not fully representative of the global population, and they can minimize the effect of geographical variations in environment and health care delivery. Randomization (if the study population is large enough) should mean that the study groups are unbiased. A double-blind trial is one in which neither the patient nor the deliverer of the treatment is aware of the nature of the treatment offered to any particular individual, and this avoids bias caused by the expectations of either the doctor or the patient.
Major developments in randomized controlled trials
International Conference on Harmonization
In 1990, the steering committee was formed for the International Conference on Harmonization. This led to the recommendations for Good Clinical Practices in the conduct of trials. Some have considered these guidelines to be burdensome.
In the United States of America, Good Clinical Practices is overseen by the Food and Drug Administration (http://www.fda.gov/ScienceResearch/SpecialTopics/RunningClinicalTrials/).
The quality of reporting of the conduct of randomized controlled trials remains problematic.
As of 2005, among high impact journals, "CONSORT was mentioned in the instructions of 36 (22%) journals (see bmj.com), more often in general and internal medicine journals (8/15; 53%) than in specialty journals (28/152; 18%)". Changes in 2010 includes reporting of trial registration, availability of the original protocol, and funding. The quality of reporting of trials in psychiatry may be better since introduction of the CONSORT statement.
In 2004, the International Committee of Medical Journal Editors (ICMJE) announced that all trials starting enrollment after July 1, 2005 must be registered prior to consideration for publication in one of the 12 member journals of the Committee. However, trial registration may still occur late or not at all.
Disclosure of Competing Interests
In 2009, the International Committee of Medical Journal Editors (ICMJE) announced a Uniform Format for Disclosure of Competing Interests in ICMJE Journals.
"Control", according to the current Declaration of Helsinki ethical guides, may or may not involve a placebo. If there is no accepted treatment, or the disease is mild and self-limiting, placebo controls may be ethical. If there is accepted treatment, the best accepted treatment becomes the control arm. Trials that are controlled, but not by a placebo, still generate arguments about information value versus ethics.
Placebo controls are important, because the placebo effect can often be strong. The more value a subject believes an unknown drug has, the more placebo effect is has. The use of historical rather than concurrent controls may lead to exaggerated estimation of effect.
Optimization of the delivery of health care in the control groups is important. This was illustrated in a randomized control trial of extracorporeal membrane oxygenation (ECMO). The ECO showed no improvement in survival although the survival of patients treated with ECMO was similar to prior published results. In this trial, the authors had protocolized the management of the mechanical ventilation in the control group and found high adherence to the protocols and higher than expected survival in the control group. In a subsequent randomized controlled trial, the authors found that protocolized management mechanical ventilation of was better than usual care management of mechanical ventilation.
The Hawthorne effect is the improvements seen in control subjects simply from participating in research.
Blinding, where neither participants nor experimenters know what treatment the participants are receiving, is important, especially for trials that have subjective outcomes. Trials that are not blinded tend to report more favorable results.
Variations in design
In some settings, health care providers, or healthcare institutions should be randomized rather than randomizing the research subjects. This should occur when the intervention targets the provider or institutions and thus the results from each subject are not truly independent, but will cluster within the health care provider or healthcare institution. Guidelines exist for conducting cluster randomised trials. Cluster-randomized trials are not always correctly designed and executed.
Designing an adequately sized cluster-randomized trial is based on several factors. One factor is the intraclass (intracluster) correlation coefficient (ICC). The ICC between clusters is analogous to the variance between subjects in a randomized controlled trial. Just as when randomized controlled trials exhibiting high variance between subjects means a larger study is needed, less correlation between clusters indicates more clusters are needed.
Uncontrolled before-after studies and controlled before-after studies probably should not be considered variations of a randomized controlled trial, yet if carefully done offer advantages to observational studies. As in a true cluster-randomized trial, the intervention group can be randomly assigned; however, unlike a cluster-randomized trial, the before-after study does not have enough clusters or groups. An interrupted time series analysis can try to improve plausibility of causation; however, interrupted time series are commonly performed incorrectly.
Delayed start trial
In this design, one group is randomized to receive treatment before the control group. This design allows analysis for disease-modifying effects of treatments. An example of this design was a trial of rasagiline for Parkinson's disease.
Dose ranging studies
Various study designs exit to determine the optimal dose of a new drug.
- Crossover designs have been used.
- Designs that test doses in sequence, such as up and down studies and adaptive dose-ranging trials, depend upon being able to measure an outcome from the medication that occurs quickly, and the drug's dose can be titrated to achieve the effect. An example of this type of outcome is blood pressure.
- Parallel designs such as multi-level factorial studies have been used. Special sample size calculations exist for these designs.
1. There were 15 patients in each group.
A factorial design allows two interventions to be studied with ability to measure the treatment effect of each intervention in isolation and in combination. Interaction between the two treatments can be displayed with "interaction ratios or odds ratios accompanied by their confidence intervals" and can be measured with the method of Gail and Simon or the Breslow-Day test for homogeneity.
N of 1 trial
In an "N of 1" trial, also called a "single-subject randomized" trial, a single patient randomly proceeds through multiple blinded crossover comparisons. This address the concerns that traditional randomized controlled trials may not generalize to a specific patient.
Underlining the difficulty in extrapolating from large trials to individual patients, Sackett proposed the use of N of 1 randomized controlled trials. In these, the patient is both the treatment group and the placebo group, but at different times. Blinding must be done with the collaboration of the pharmacist, and treatment effects must appear and disappear quickly following introduction and cessation of the therapy. This type of trial can be performed for many chronic, stable conditions. The individualized nature of the single-subject randomized trial, and the fact that it often requires the active participation of the patient (questionnaires, diaries), appeals to the patient and promotes better insight and self-management as well as patient safety, in a cost-effective manner.
Noninferiority and equivalence randomized trials
As stated in The Declaration of Helsinki by the World Medical Association it is unethical to give any patient a placebo treatment if an existing treatment option is known to be beneficial. Many scientists and ethicists consider that the U.S. Food and Drug Administration, by demanding placebo-controlled trials, encourages the systematic violation of the Declaration of Helsinki. In addition, the use of placebo controls remains a convenient way to avoid direct comparisons with a competing drug.
The appropriate use of placebo is being revised. When guidelines suggest a placebo is an unethical control, then an "active-control noninferiority trial" may be used. To establish non-inferiority, the following three conditions should be - but frequently are not - established:
- "The treatment under consideration exhibits therapeutic noninferiority to the active control."
- "The treatment would exhibit therapeutic efficacy in a placebo-controlled trial if such a trial were to be performed."
- "The treatment offers ancillary advantages in safety, tolerability, cost, or convenience."
Noninferiority and equivalence randomized trial are difficult to execute well. Guidelines exists for noninferiority and equivalence randomized trials. In planning the trial, the investigators should choose "a noninferiority or equivalence criterion, and specifying the margin of equivalence with the rationale for its choice." In reporting the outcomes, the authors should present the confidence intervals to show the reader whether the result was within their noninferiority or equivalence criterion.
"Sometimes a new agent can be assessed by using an 'add-on' study design in which all patients are given standard therapy and are randomly assigned to also receive either new agent or placebo."
Consort has described pragmatic trials and standards for their reporting. CONSORT describes a pragmatic trial as addressing "does the intervention work when used in normal practice" as opposed to an "explanatory trial" that addresses "can the intervention work." CONSORT states that this is not a dichotomy of trial designs, but that pragmatic trials reflect an attitude in the design. CONSORT offers an example of a pragmatic trial and an explanatory trial.
The Belmont Report was released in 1979 by the National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research. The three Belmont principles are beneficence, justice and respect for persons.
The Declaration of Helsinki requires informed consent for participation in a trial. In the United States, there is an approval procedure for clinical trials in human subjects, whether for research only or for potential approval of a commercial drug. Most industrialized countries have such procedures; some permit reciprocal approvals.
In the United States, the Code of Federal Regulations (45 CFR 46.102(d) or http://www.access.gpo.gov/nara/cfr/waisidx_02/45cfr46_02.html) regulates human subjects research. Definition from the Code are:
- "Research means a systematic investigation, including research development, testing and evaluation, designed to develop or contribute to generalizable knowledge. Activities which meet this definition constitute research for purposes of this policy, whether or not they are conducted or supported under a program which is considered research for other purposes. For example, some demonstration and service programs may include research activities."
- Human subject means a living individual about whom an investigator (whether professional or student) conducting research obtains:
- Data through intervention or interaction with the individual, or
- Identifiable private information.
In the United States, the Code of Federal Regulations defines:
- Research that may be exempt from IRB approval (45 CFR 46.101(b))
- Research that may be eligible for expedited IRB approval (45 CFR 46.110)
- The informed consent process (45 CFR 46.116)
Ethics of randomizing subjects
Determining the justification for experimentation can be difficult.
The appropriate use of placebo is being revised. One tension is the balance between using placebo to increase scientific rigor versus the unnessessary deprival of active treatment to patients. This is the conundrum faced by Martin Arrowsmith in the book by the same name.
Comparing a new intervention to a placebo control may not be ethical when an accepted, effective treatment exists. In this case, the new intervention should be compared to the active control to establish whether the standard of care should change. The observation that industry sponsored research may be more likely to conduct trials that have positive results suggest that industry is not picking the most appropriate comparison group. However, it is possible that industry is better at predicting which new innovations are likely to be successful and discontinuing research for less promising interventions before the trial stage.
There are ethical concerns in comparing a surgical intervention to sham surgery; however, this has been done. Guidelines by the American Medical Association address the use of placebo surgery.
Interim analysis - stopping trials early
Trials are increasingly stopped early; however, this may induce a bias that exaggerates results. Data safety and monitoring boards that are independent of the trial are commissioned to conduct interim analyses and make decisions about stopping trials early. 
Regarding efficacy, various rules exist that adjust alpha to decide when to stop a trial early. A commonly recommended rules are the O'Brien-Fleming (the O'Brien-Fleming rule requires a varying p-value depending on the number of interim analyses) and the Haybittle-Peto (the Haybittle-Peto which requires p<0.001 to stop a trial early) rule.
Using a more conservative stopping rule reduces the chance of a statistical alpha (Type I) error; however, these rules do not alter that the effect size may be exaggerated. According to Bassler, "the more stringent the P-value threshold results must cross to justify stopping the trial, the more likely it is that a trial stopped early will overestimate the treatment effect." A review of trials stopped early found that the earlier a trial was stopped the larger was its reported treatment effect, especially if the trial had less than 500 total events. Accordingly, examples exist of trials whose interim analyses were significant, but the trial was continued and the final analysis was less significant or was insignificant.
Some trials may be unnecessary because their hypotheses have already been established. Using cumulative meta-analysis, 25 of 33 randomized controlled trials of streptokinase for the treatment of acute myocardial infarction were unnecessary.
Authors of trials may fail to cite prior trials.
Seeding trials are studies sponsored by industry whose "apparent purpose is to test a hypothesis. The true purpose is to get physicians in the habit of prescribing a new drug." Examples include the ADVANTAGE and STEPS trials.
Subjectively assessed outcomes are more susceptible to bias in trials with inadequate allocation concealment.
Several approaches to handling missing data have been reviewed. Regarding assigning an outcome to the patient, using a 'last observation carried forward' (LOCF) analysis may introduce biases.
Crossover between experimental groups
Regarding group assignment, a 'per protocol' analysis may introduce bias compared to an 'intention to treat' analysis. Intention to treat is not always adequately described. This bias may be due to the observations that research subjects who adhere to therapy, whether the therapy be an active treatment or placebo, have a reduction in mortality. Thus excluding non-compliant subjects would appear to exaggerate the effects of treatment; however the bias can go both directions. Analysis options exist.
The costs and efforts required to measure primary endpoints such as morbidity and mortality make using surrogate outcomes an option. An example is in the treatment of osteoporosis, the primary outcomes are fractures and mortality whereas the surrogate outcome is changes in bone mineral density. Other examples of surrogate outcomes are tumor shrinkage or changes in cholesterol level, blood pressure, HbA1c, CD4 cell count. Surrogate markers might be acceptable when "the surrogate must be a correlate of the true clinical outcome and fully capture the net effect of treatment on the clinical outcome". However, surrogate outcomes and their rationale may not be adequately described in trials.
Adverse effects may be discovered only after a trial is concluded, or in the larger populations to which a drug, approved for general release based on trial data, is used. Postmarketing surveillance is intended to detect hazards that the trials are not powerful enough to find.
Planning analyses prior to conducting the trial
Conflict-of-interests in data analyses
Regarding data analyses of randomized controlled trials, research sponsored by industry may incompletely report or analyze drug toxicity. Similarly, industry-sponsored trials may be more likely to omit intention-to-treat analyses. These problems with statistical analyses have led the Journal of the American Medical Association (JAMA) to require independent analysis of data. This policy has been associated with a decreased in the number of trials published by JAMA.
When multiple subgroups are present, examining subgroups with a multivariate risk score may be better than examining subgroups one-variable-at-at-time which may exaggerate the role of subgroups.
Statistical methods and criteria exist for assessing the importance of subgroups. In brief, testing the statistical significance of an interaction (e.g. statistical heterogeneity) between subgroups and a relative measure of outcome. variation in the relative measure.
- P > 0.1 indicates skepticism of a subgroup effect
- P is between 0.1 and 0.01 suggests to "consider the hypothesis"
- P less than or equal to 0.001 "take the hypothesis seriously"
Assessing the quality of a trial
Biased trials are more common, sepecially in trials with subjective outcomes, if:
- Inadequate or unclear random-sequence generation
- Inadequate or unclear allocation concealment
- Lack of or unclear double-blinding
Numerous scales and checklists for assessing quality have been proposed. A comparison of the Cochrane Collaboration Tool, the Jadad score, and the Schulz approach found that the Cochrane Collaboration Tool required more time to complete, contained some subjective items, and did not well correlate with the Jadad score or Schulz approach.
Cochrane bias scale
In using the Cochrane tool, if any of the first three items are low quality (randomization, allocation concealment before and during enrollment, blinding), the trial may be considered high or uncertain bias.
The Jadad score may be used to assess quality. The scale focuses on three attributes: randomization, blinding, and dropouts.
The Schulz approach assess the quality of allocation concealment.
Studies of characteristics of trails
Large studies may not be associated with better quality.
Problems with trials
Small study effect
Small trials report stronger effect estimates.
Publication bias refers to the tendency that trials that show a positive significant effect are more likely to be published than those that show no effect or are inconclusive.
At the same time, in September 2004, the International Committee of Medical Journal Editors (ICMJE) announced that all trials starting enrollment after July 1, 2005 must be registered prior to consideration for publication in one of the 12 member journals of the Committee. This move was to reduce the risk of publication bias as negative trials that are unpublished would be more easily discoverable.
Available trial registries include:
- World Health Organization's International Clinical Trial Registry Platform (ICTRP)
It is not clear how effective trial registration is because many registered trials are never completely published.
Judging external validity is more difficult than judging internal validity. "External validity refers to the question whether results are generalizable to persons other than the population in the original study." A framework for assessing external validity proposes:
- "The study population might not be representative for the eligibility criteria that were intended. It should be addressed whether the study population differs from the intended source population with respect to characteristics that influence outcome."
- "The target population will, by definition, differ from the study population with respect to geographical, temporal and ethnical conditions. Pondering external validity means asking the question whether these differences may influence study results."
- "It should be assessed whether the study's conclusions can be generalized to target populations that do not meet all the eligibility criteria."
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