Clinical study design Wikipedia

Table Of Content

• Outcomes of interest:
• Challenges and Opportunities for Designing Clinical Trials for Antibody Mediated Rejection
• Bias Control: Randomization and Masking
• Statistical analyses of clinical trials in haematopoietic cell transplantation
• Code, Data and Media Associated with this Article
• Avoiding designing negative (but valid) clinical trials

Researchers need to design, conduct, and report on clinical trials to create impactful technologies that can better our understanding of health and medicine. From learning frameworks and reporting methods to determining how to accurately collect, manage, and measure data, you’ll gain the knowledge necessary to understand the components that go into running a successful clinical trial. When constructing entry criteria, the safety of the study participant is paramount. Researcher should consider the appropriateness of recruiting participants with various conditions into the trial. The ability to accrue study participants can also affect the selection of entry criteria.

Outcomes of interest:

The interventions evaluated can be drugs, devices (e.g., hearing aid), surgeries, behavioral interventions (e.g., smoking cessation program), community health programs (e.g. cancer screening programs) or health delivery systems (e.g., special care units for hospital admissions). We consider clinical trials experiments because the investigators rather than the patients or their doctors select the treatment the patients receive. Results from randomized clinical trials are usually considered the highest level of evidence for determining whether a treatment is effective because trials incorporates features to ensure that evaluation of the benefits and risks of treatments are objective and unbiased. The FDA requires that drugs or biologics (e.g., vaccines) are shown to be effective in clinical trials before they can be sold in the US.

Challenges and Opportunities for Designing Clinical Trials for Antibody Mediated Rejection

Regression models provide estimates of effect sizes (e.g., odds ratios or hazard ratios), which are important when interpreting the results of trials. In addition, regression analyses allow for adjustments for co-variates not used in randomization stratification. Although randomization is likely to balance most factors across arms it does not guarantee balance without stratification. Regression analyses can allow for more precise estimation of effect sizes when there is an imbalance in a prognostic co-variate across arms. Subjects of psoriasis vulgaris are initiated on a biological and a group of patients attain PASI 75 response at 16 weeks.

Bias Control: Randomization and Masking

Though there are various designs available, one must consider various ethical aspects of the study. Hence, each study will require thorough review of the protocol by the institutional review board before approval and implementation. However, these differences will need to be accounted during analysis of results.

NIH launches long COVID clinical trials through RECOVER Initiative, opening enrollment - National Institutes of Health (NIH) (.gov)

NIH launches long COVID clinical trials through RECOVER Initiative, opening enrollment.

Posted: Mon, 31 Jul 2023 07:00:00 GMT [source]

Although strict entry criteria may be scientifically desirable in some cases, studies with strict entry criteria may be difficult to accrue particularly when the disease is rare or alternative interventions or trials are available. Entry criteria may need to be relaxed so that enrollment can be completed within a reasonable time frame. The design of every clinical trial starts with a primary clinical research question. Secondary research questions may also be of interest but the trial design usually is constructed to address the primary research question. Information bias is when a systematic error is committed while obtaining data from the study subjects.

This can be performed in multiple ways, and one of which being as simple as a ‘flip of a coin’ to using random tables or numbers.17 The advantage of using this methodology is that it eliminates selection bias. However, the disadvantage with this methodology is that an imbalance in the number allocated to each group as well as the prognostic factors between groups. Hence, the subjects are monitored over a period of time for occurrence of a particular disease process.

The basic concept of experimental study design is to study the effect of an intervention. In this study design, the risk factor/exposure of interest/treatment is controlled by the investigator. Therefore, these are hypothesis testing studies and can provide the most convincing demonstration of evidence for causality. As a result, the design of the study requires meticulous planning and resources to provide an accurate result. From an epidemiological standpoint, there are two major types of clinical study designs, observational and experimental.3 Observational studies are hypothesis‐generating studies, and they can be further divided into descriptive and analytic. Descriptive observational studies provide a description of the exposure and/or the outcome, and analytic observational studies provide a measurement of the association between the exposure and the outcome.

However, certain treatments cannot be blinded such as surgeries or if the treatment group requires an assessment of the effect of intervention such as quitting smoking. The trial combines phases I/II/III with a dose escalation phase, followed by a pivotal phase at the selected dose. The trial has been approved by French and UK health authorities and includes ambulant boys aged 6 to 10 suffering from Duchenne Muscular Dystrophy.

The CHARISMA (Bhatt et al 2006), MATCH (Diener et al 2004), and CAPRIE (Committee 1996) studies of clopidogrel for the prevention of vascular ischemic events use combinations of MI, stroke, death, and re-hospitalization as components of composite endpoints. The advantages of composite endpoints are that they may result in a more completed characterization of intervention effects as there may be interest in a variety of outcomes. Composite endpoints may also result in higher power and resulting smaller sample sizes in event-driven trials since more events will be observed (assuming that the effect size is unchanged).

Composite endpoints may also reduce the bias due to competing risks and informative censoring. This is because one event can censor other events and if data were only analyzed on a single component then informative censoring can occur. Composite endpoints may also help avoid the multiplicity issue of evaluating many endpoints individually. Historically controlled studies can be considered as a subtype of non‐randomized clinical trial.

However, occasionally the choice of trial phase (e.g. Phase II vs. Phase III) may be driven by feasibility to launch a large trial. Ultimately the design must be feasible and appropriate to answer the research question(s) of interest. A trial is only ethical if the proportion of benefit clearly outweighs the risk, especially when there are more than minimal risks. However, trials with higher potential benefits are often highly risky to patients, but may be the only existing options to help populations with devastating diseases. For instance, cancer patients undergoing investigational chemotherapy may suffer from toxic side effects, but their therapeutic options are so limited that running the study is justified.

It is much harder to design a clinical trial effectively if one doesn’t understand the interactions of genetic, environmental and/or pathophysiologic factors leading to a disease, especially one that is heterogeneous or complex (44). Success in a well-executed trial relates to good trial design, which relates to a good research question and a strong specific hypothesis, which in turn depends on a deep understanding of the subject matter and clinical research methods. For ethical reasons, any research question requires clinical equipoise (i.e. it is unclear if the intervention is better than the control) (42). No trial is thus guaranteed success, but a strong design can mitigate potential risks and augment its benefits and feasibility. One such trial applied transcutaneous electrical nerve stimulation as analgesic for PLP in 5 adult amputees (23).

Another concern with composite endpoints is that the interpretation can be challenging particularly when the relative importance of the components differs and the intervention effects on the components also differ. For example, how do we interpret a study in which the overall event rate in one arm is lower but the types of events occurring in that arm are more serious? Higher event rates and larger effects for less important components could lead to a misinterpretation of intervention impact. It is also possible that intervention effects for different components can go in different directions. Power can be reduced if there is little effect on some of the components (i.e., the intervention effect is diluted with the inclusion of these components).