Tuesday, October 23, 2018

TYPES OF CLINICAL TRIALS - pharmacovigilance-material


TYPES OF CLINICAL TRIALS
Clinical trials can be classified based on different types:
The first way of classifying clinical trials is in the way the researchers behave.
In an observational study, the investigators observe the subjects and measure their outcomes. The researchers do not actively manage the experiment. This is also called a natural experiment. An example is the Nurses' Health Study.
                     In an interventional study, the investigators give the research subjects a particular medicine or other intervention. (Usually they compare the treated subjects to subjects who receive no treatment or standard treatment.) Then the researchers measure how the subjects' health changes.
                     Second way of classifying trials is by their purpose. The U.S. National Institutes of Health (NIH) organizes trials into five (5) different types:
                     Prevention trials: look for better ways to prevent disease in people who have never had the disease or to prevent a disease from returning. These approaches may include medicines, vitamins, vaccines, minerals, or lifestyle changes.
                     Screening trials: test the best way to detect certain diseases or health conditions.
                     Diagnostic trials: conducted to find better tests or procedures for diagnosing a particular disease or condition.
                     Treatment trials: test experimental treatments, new combinations of drugs, or new approaches to surgery or radiation therapy.
                     Quality of Life trials: explore ways to improve comfort and the quality of life for individuals with a chronic illness (e.g. Supportive Care trials).
                     Genetic trials :-Determine how one’s genetic makeup can influence detection, diagnosis, prognosis, and treatment
§  Broaden understanding of causes of cancer
§  Develop targeted treatments based on the genetics of a tumor
                     Academic clinical trials: They share a valuable component of the health care system; they benefit patients and help to determine the safety and efficacy of new drugs and devices.
Typical areas of academic clinical trials are the advancement and optimization of already existing therapies. Thus academic clinical trials may for instance test how a combination of registered drugs may improve treatment outcomes or they may apply registered treatments in additional, less frequent indications. Such research questions are not a primary focus of for-profit companies and thus these trials are typically initiated by individual investigators or academic research organizations.
There are many different organizations which have an interest in academic clinical trials and facilitate or take part in their conduct. These organizations include:
                     Hospitals, universities, researchers and institutions that view trials as a source of income and prestige and receive private, charitable and governmental funding.
                     Pharmaceutical or biotech companies who view the development and commercialization of treatments as their business.
                     Regulators who wish to ensure treatments are safe and work effectively.
                     Patients and patients' organizations and associations who want faster access to advanced treatments.
Academic clinical trials are run at academic sites, such as medical schools, academic hospitals and universities and non-academic sites which may be managed by so-called Site Management Organizations (SMOs). Site management organizations are for-profit organizations which enlist and manage the physician practice sites that actually recruit and follow patients enrolled in clinical trials. In some cases, academic members participate in clinical trials act as members of SMOs.
A crossover trial also referred to as a crossover study is a clinical trial in which patients are given all of the medications to be studied or one medication and a placebo in random order. These studies are generally done on patients with chronic diseases to control their symptoms. The data are analyzed according to the original intention to treat.
A crossover study has the advantage over a simple double-blind study that the variability between patients is minimized because each patient crossing over in effect serves as their own control. One disadvantage is that long term effects cannot be tracked with this approach. Another disadvantage is that curative therapies cannot be tested after one another or before a placebo.
There are some important issues with respect to the design of cross-over studies. Two in particular may often crop up.
First is the issue of order effects, because it is possible that the order in which treatments are administered may affect the outcome. An example might be a drug with many adverse effects given first, making patients taking a second, less harmful medicine, more sensitive to any adverse effect.
Second is the issue of carry-over between treatments. In practice carry-over can be and is often dealt with by the use of a wash-out period between treatments or by making observations sufficiently later after the start of a treatment period that any carry-over effect is minimized.
A randomized controlled trial (RCT):
Randomization is a process for allocating subjects between the different trial interventions. Each subject has the same chance of being allocated to any group, which ensures similarity in characteristics between the arms. This minimizes the effect of both known and unknown confounders, and thus has a distinct advantage over observational studies in which statistical adjustments can only be made for known confounders. Although randomization is designed to produce groups with similar characteristics, there will always be small differences because of chance variation. Randomization cannot produce identical groups.
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). According to Lachin (1998), 'RCTs are considered the most reliable form of scientific evidence in healthcare because they eliminate spurious causality and bias'. 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. This ensures that known and unknown confounding factors are evenly distributed between treatment groups.
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.
Trials are used to establish average efficacy of a treatment as well as learn about its most frequently occurring side-effects. 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. 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 act of administering the treatment itself may have direct, sometimes very powerful, psychological effects on the patient, which is known as the placebo effect.
Randomized trials are employed to test efficacy while avoiding these factors. Trials may be open, blind or double-blind.
Blind trials
The randomization process minimizes the potential for bias but the benefit could be greater if the trial intervention given to each subject is concealed. Subjects or researchers may have expectations associated with a particular treatment and knowing which was given can create bias. This can affect how people respond to treatment or how the researcher manages or assesses the subject. In subjects, this bias is specifically referred to as the placebo effect. Humans have a remarkable psychological ability to affect their own health status. The effect of any of these biases could result in subjects receiving the new intervention appearing to do better than those on the control treatment, but the difference is not really due to the action of the new treatment.
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 him 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
An experiment designed to test the effect of a treatment or substance by using groups of experimental and control subjects in which neither the subjects nor the investigators know which treatment or substance is being administered to which group. In a double-blind test of a new drug, the substance may be identified to the investigators by only a code. The purpose of a double-blind study is to eliminate the risk of prejudgment by the participants, which could distort the results. A double-blind study may be augmented by a cross-over experiment, in which experimental subjects unknowingly become control subjects, and vice versa, at some point in the study.
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. Alternately, it may mean that the patient, researcher and statistician are blinded. 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 license 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. 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. The branch of statistics that deals specifically with biomedical research is biostatistics. 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. 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.
                     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.
                     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. 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. The potential magnitude of that bias, if any, will depend on the randomization procedure.
Complete randomization
This is commonly used in which, each patient is effectively and randomly assigned to any one of the groups. It is simple and optimal in the sense of robustness against both selection and accidental biases. 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 Designs:
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 Minimization can be used to minimize the imbalance within each of the factors.
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. This introduces selection bias and confounders and distorts the results of the study. Breaking allocation concealment in randomized controlled trials is 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.
 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'). 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.

No comments:

Post a Comment

INTRODUCTION TO CLINICAL RESEARCH - pharmacovigilance-material

INTRODUCTION TO CLINICAL RESEARCH Clinical trials have revolutionised the way disease is prevented, detected or treated and early deat...