A randomized controlled trial (RCT) is a type of scientific experiment most commonly used in testing healthcare services (such as medicine or nursing) or health technologies (such as pharmaceuticals, medical devices or surgery). In scientific inquiry an experiment ( Latin: Ex- periri, "to try out" is a method of investigating particular types of research questions or Health care is the prevention treatment and management of illness and the preservation of mental health through the services offered by the medical, Nursing A service is the non-material equivalent of a good. A service provision is an economic activity that does not result in Ownership, and this is what differentiates Medicine is the art and science of healing It encompasses a range of Health care practices evolved to maintain and restore Human Health by the Nursing is a Profession focused on assisting individuals families, and communities in attaining maintaining and recovering optimal Health Health is a state of complete physical mental and social well-being and not merely the absence of disease or infirmity Technology is a broad concept that deals with a Species ' usage and knowledge of Tools and Crafts and how it affects a species' ability to control and adapt A drug, broadly speaking is any chemical substance that when absorbed into the body A medical device is an object which is useful for diagnostic or therapeutic purposes Surgery (from the χειρουργική cheirourgikē, via chirurgiae meaning "hand work" is a medical specialty that uses operative manual and instrumental According to Lachin (1998), 'RCTs are considered the most reliable form of scientific evidence in healthcare because they eliminate spurious causality and bias'. Scientific method refers to bodies of Techniques for investigating phenomena RCTs are mainly used in clinical studies, but are also employed in other sectors such as judicial, educational, and social research. As their name suggests, RCTs involve the random allocation of different interventions (or treatments) to subjects. Randomness is a lack of order Purpose, cause, or predictability In Biostatistics or Psychological statistics, a research subject is any object or phenomenon that is observed for purposes of research This ensures that known and unknown confounding factors are evenly distributed between treatment groups. In statistics a confounding variable (also confounding factor, lurking variable, a confound, or confounder) is an Extraneous variable

Sellers of medicines throughout the ages have had to convince their consumers that the medicine works. As science has progressed, public expectations have risen, and government health budgets have become ever tighter, pressure has grown for a reliable system to do this. Moreover, the public's concern for the dangers of medical interventions has spurred both legislators and administrators to provide an evidential basis for licensing or paying for new procedures and medications. In most modern health-care systems all new medicines and surgical procedures therefore have to undergo trials before being approved. Medication, also referred to as medicine, can be loosely defined as any substance intended for use in the diagnosis cure mitigation treatment or prevention of disease Surgery (from the χειρουργική cheirourgikē, via chirurgiae meaning "hand work" is a medical specialty that uses operative manual and instrumental

Trials are used to establish average efficacy of a treatment as well as learn about its most frequently occurring side-effects. In Medicine, an adverse effect is a harmful and undesired effect resulting from a medication or other intervention such as Chemotherapy or Surgery. This is meant to address the following concerns. First, effects of a treatment may be small and therefore undetectable except when studied systematically on a large population. Second, biological organisms (including humans) are complex, and do not react to the same stimulus in the same way, which makes inference from single clinical reports very unreliable and generally unacceptable as scientific evidence. Human beings, humans or man (Origin 1590–1600 L homō man OL hemō the earthly one (see Humus Third, some conditions will spontaneously go into remission, with many extant reports of miraculous cures for no discernible reason. Finally, it is well-known and has been proven that the simple process of administering the treatment may have direct, sometimes very powerful, psychological effects on the patient, which is known as the placebo effect. Placebo is a substance or procedure a patient accepts as medicine or therapy but which has no specific therapeutic activity

Contents 1 Types of trials 1.1 Open trial 1.2 Blind trials 1.2.1 Single-blind trial 1.2.2 Double-blind trial 1.2.3 Triple-blind trial 2 Aspects of control in clinical trials 2.1 Types of control groups 3 Randomization in clinical trials 3.1 Randomization procedures 3.1.1 Complete randomization 3.1.2 Permuted block randomization 3.1.3 Urn randomization 3.1.4 Covariate-adaptive randomization 3.1.5 Outcome-adaptive randomization 3.2 Allocation concealment 4 Difficulties 5 See also 6 References 7 External links

Types of trials

Randomized trials are employed to test efficacy while avoiding these factors. Trials may be open, blind or double-blind.

Open trial

In an open trial, the researcher knows the full details of the treatment, and so does the patient. These trials are open to challenge for bias, and they do nothing to reduce the placebo effect. Placebo is a substance or procedure a patient accepts as medicine or therapy but which has no specific therapeutic activity However, sometimes they are unavoidable, particularly in relation to surgical techniques, where it may not be possible or ethical to hide from the patient which treatment he or she received. Usually this kind of study design is used in bioequivalence studies. Bioequivalence is a term in Pharmacokinetics used to assess the expected in vivo biological equivalence of two proprietary preparations of a drug

Blind trials

Single-blind trial

In a single-blind trial, the researcher knows the details of the treatment but the patient does not. Because the patient does not know which treatment is being administered (the new treatment or another treatment) there might be no placebo effect. In practice, since the researcher knows, it is possible for them to treat the patient differently or to subconsciously hint to the patient important treatment-related details, thus influencing the outcome of the study.

Double-blind trial

In a double-blind trial, one researcher allocates a series of numbers to 'new treatment' or 'old treatment'. The blind method is a part of the Scientific method, used to prevent research outcomes from being influenced by either the Placebo effect or the Observer The second researcher is told the numbers, but not what they have been allocated to. Since the second researcher does not know, they cannot possibly tell the patient, directly or otherwise, and cannot give in to patient pressure to give them the new treatment. In this system, there is also often a more realistic distribution of sexes and ages of patients. Therefore double-blind (or randomized) trials are preferred, as they tend to give the most accurate results.

Triple-blind trial

Some randomized controlled trials are considered triple-blinded, although the meaning of this may vary according to the exact study design. The most common meaning is that the subject, researcher and person administering the treatment (often a pharmacist) are blinded to what is being given. Pharmacists are Health professionals who practice the art and science of Pharmacy. Alternately, it may mean that the patient, researcher and statistician are blinded. Statisticians work with theoretical and applied Statistics in both the private and public sectors These additional precautions are often in place with the more commonly accepted term "double blind trials", and thus the term "triple-blinded" is infrequently used. However, it connotes an additional layer of security to prevent undue influence of study results by anyone directly involved with the study.

Aspects of control in clinical trials

Traditionally the control in randomized controlled trials refers to studying a group of treated patients not in isolation but in comparison to other groups of patients, the control groups, who by not receiving the treatment under study give investigators important clues to the effectiveness of the treatment, its side effects, and the parameters that modify these effects.

Other aspects of control include having other members of the research team, who will typically review the test to try to remove any factors which might skew the results. For example, it is important to have a test group which is reasonably balanced for ages and sexes of the subjects (unless this is a treatment which will never be used on a particular sex or age group). Additionally, peer review and/or review by government regulators can be seen as another source of control. These bodies examine the trial results when they are presented for publication or when the drug manufacturer applies for a licence for the drug.

The importance of having a control group cannot be overstated. Merely being told that one is receiving a miraculous cure can be enough to cure a patient—even if the pill contains nothing more than sugar. Additionally, the procedure itself can produce ill effects. For example, in one study on rabbits where these subjects were receiving daily injections of a drug, it was found that they were developing cancer. Rabbits are small Mammals in the family Leporidae of the order Lagomorpha, found in several parts of the world Cancer (medical term Malignant Neoplasm) is a class of Diseases in which a group of cells display uncontrolled If this was a result of the treatment, it would obviously be unsuitable for testing in humans. Because this result was reflected equally between the control and test groups, the source of the problem was investigated and it was shown in this case that the administration of daily injections was the cancer risk—not the drug itself.

The analysis of the trial results requires knowledge of medicine, epidemiology, and in particular statistics. Medicine is the art and science of healing It encompasses a range of Health care practices evolved to maintain and restore Human Health by the Epidemiology is the study of factors affecting the Health and Illness of populations and serves as the foundation and Logic of interventions made in the Statistics is a mathematical science pertaining to the collection analysis interpretation or explanation and presentation of Data. The branch of statistics that deals specifically with biomedical research is biostatistics. Biostatistics (a Portmanteau word made from biology and statistics sometimes referred to as biometry or biometrics) is the application of Statistics Pharmaceutical firms employ groups of biostatisticians to try to make sense of the data. Likewise, regulators pay keen attention to the appropriateness of statistical methods used to analyze trial results.

Types of control groups

• Placebo concurrent control group
• Dose-response concurrent control group
• Active concurrent control group
• No treatment concurrent control group
• Historical control

Randomization in clinical trials

There are two processes involved in randomizing patients to different interventions. First is choosing a randomization procedure to generate a random and unpredictable sequence of allocations. Randomization is the process of making something Random; this means Generating a Random permutation of a sequence (such as when shuffling cards This may be a simple random assignment of patients to any of the groups at equal probabilities, or may be complex and adaptive. A second and more practical issue is allocation concealment, which refers to the stringent precautions taken to ensure that the group assignment of patients are not revealed to the study investigators prior to definitively allocating them to their respective groups.

Randomization procedures

There are a couple of statistical issues to consider in generating the randomization sequences^[1]. :

• Balance: since most statistical tests are most powerful when the groups being compared have equal sizes, it is desirable for the randomization procedure to generate similarly-sized groups. The power of a statistical test is the probability that the test will reject a false Null hypothesis (that it will not make a Type II error)
• Selection bias: depending on the amount of structure in the randomization procedure, investigators may be able to infer the next group assignment by guessing which of the groups has been assigned the least up to that point. Selection bias is a distortion of evidence or data that arises from the way that the data are collected This breaks allocation concealment (see below) and can lead to bias in the selection of patients for enrollement in the study.
• Accidental bias: if important covariates that are related to the outcome are ignored in the statistical analysis, estimates arising from that analysis may be biased. In statistics a covariate is a variable that is possibly predictive of the outcome under study In Statistics, the difference between an Estimator 's Expected value and the true value of the parameter being estimated is called the bias. The potential magnitude of that bias, if any, will depend on the randomization procedure.

Complete randomization

In this commonly used and intuitive procedure, each patient is effectively randomly assigned to any one of the groups. It is simple and optimal in the sense of robustness against both selection and accidental biases. Robustness is the quality of being able to withstand stresses pressures or changes in procedure or circumstance However, its main drawback is the possibility of imbalances between the groups. In practice, imbalance is only a concern for small sample sizes (n < 200).

Permuted block randomization

In this form of restricted randomization, blocks of k patients are created such that balance is enforced within each block. For instance, let E stand for experimental group and C for control group, then a block of k = 4 patients may be assigned to one of EECC, ECEC, ECCE, CEEC, CECE, and CCEE, with equal probabilities of 1/6 each. Note that there are equal numbers of patients assigned to the experiment and the control group in each block.

Permuted block randomization has several advantages. In addition to promoting group balance at the end of the trial, it also promotes periodic balance in the sense that sequential patients are distributed equally between groups. This is particularly important because clinical trials enroll patients sequentially, such that there may be systematic differences between patients entering at different times during the study.

Unfortunately, by enforcing within-block balance, permuted block randomization is particularly susceptible to selection bias. That is, since toward the end of each block the investigators know the group with the least assignment up to that point must be assigned proportionally more of the remainder, predicting future group assignment becomes progressively easier. The remedy for this bias is to blind investigator from group assignments and from the randomization procedure itself.

Strictly speaking, permuted block randomization should be followed by statistical analysis that takes the blocking into account. However, for small block sizes this may become infeasible. In practice it is recommended that intra-block correlation be examined as a part of the statistical analysis.

A special case of permuted block randomization is random allocation, in which the entire sample is treated as one block.

Urn randomization

Covariate-adaptive randomization

When there are a number of variables that may influence the outcome of a trial (for example, patient age, gender or previous treatments) it is desirable to ensure a balance across each of these variables. This can be done with a separate list of randomization blocks for each combination of values - although this is only feasible when the number of lists is small compared to the total number of patients. When the number of variables or possible values are large a statistical method known as Minimisation can be used to minimise the imbalance within each of the factors. 'Minimisation' is a method of adaptive stratified randomization as used in Clinical trials, as described by Pocock and Simon (Pocock SJ Simon R

Outcome-adaptive randomization

For a randomized trial in human subjects to be ethical, the investigator must believe before the trial begins that all treatments under consideration are equally desirable. At the end of the trial, one treatment may be selected as superior if a statistically significant difference was discovered. Between the beginning and end of the trial is an ethical grey zone. As patients are treated, evidence may accumulate that one treatment is superior, and yet patients are still randomized equally between all treatments until the trial ends.

Outcome-adaptive randomization is a variation on traditional randomization designed to address the ethical issue raised above. Randomization probabilities are adjusted continuously throughout the trial in response to the data. The probability of a treatment being assigned increases as the probability of that treatment being superior increases. The statistical advantages of randomization are retained, while on average more patients are assigned to superior treatments.

Allocation concealment

In practice, in taking care of individual patients, clinical investigators often find it difficult to maintain impartiality. Stories abound of investigators holding up sealed envelopes to lights or ransacking offices to determine group assignments in order to dictate the assignment of their next patient^[2]. This introduces selection bias and confounders and distorts the results of the study. Selection bias is a distortion of evidence or data that arises from the way that the data are collected In statistics a confounding variable (also confounding factor, lurking variable, a confound, or confounder) is an Extraneous variable Breaking allocation concealment in randomized controlled trials is that much more problematic because in principle the randomization should have minimized such biases.

Some standard methods of ensuring allocation concealment include:

• Sequentially-Numbered, Opaque, Sealed Envelopes (SNOSE)
• Sequentially-numbered containers
• Pharmacy controlled
• Central randomization

Great care for allocation concealment must go into the clinical trial protocol and reported in detail in the publication. Recent studies have found that not only do most publications not report their concealment procedure, most of the publications that do not report also have unclear concealment procedures in the protocols^[3][4].

Difficulties

A major difficulty in dealing with trial results comes from commercial, political and/or academic pressure. Most trials are expensive to run, and will be the result of significant previous research, which is itself not cheap. There may be a political issue at stake (compare MMR vaccine) or vested interests (compare homeopathy). The MMR vaccine is a mixture of three live Attenuated viruses administered via injection for Immunization against Measles, Mumps and Rubella This article has been the subject of edit wars and has been placed on probation In such cases there is great pressure to interpret results in a way which suits the viewer, and great care must be taken by researchers to maintain emphasis on clinical facts.

Most studies start with a 'null hypothesis' which is being tested (usually along the lines of 'Our new treatment x cures as many patients as existing treatment y') and an alternative hypothesis ('x cures more patients than y'). See also Statistical hypothesis testing In Statistics, a null hypothesis ( H 0 is a plausible hypothesis (scenario which may explain See also Statistical hypothesis testing The alternative hypothesis (or maintained hypothesis or research hypothesis) and the Null hypothesis The analysis at the end will give a statistical likelihood, based on the facts, of whether the null hypothesis can be safely rejected (saying that the new treatment does, in fact, result in more cures). Nevertheless this is only a statistical likelihood, so false negatives and false positives are possible. These are generally set an acceptable level (e. g. , 1% chance that it was a false result). However, this risk is cumulative, so if 200 trials are done (often the case for contentious matters) about 2 will show contrary results. There is a tendency for these two to be seized on by those who need that proof for their point of view.

See also

• Clinical baseline, the pre-treatment state that some trials use as a basis for comparison
• Drug development
• Evidence-based medicine
• Hypothesis testing
• Intention to treat analysis
• Meta-analysis
• Statistical inference
• Systematic review

References

External links

• A humorous look at problems with requiring randomized studies in medicine
• Directory of randomization software and services
• Power and bias in adaptively randomized clinical trials
• Design and analysis of randomized controlled trials using simulations
• Adaptive randomization software
• Lessons Learned from a Randomized Study of Multisystemic Therapy in Canada
• Statistics & Research Design

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