The overwhelming emphasis on improving the effectiveness and safety of patient care in the 20th century has given insurmountable importance to evidence-based medicine. Evidence-based medicine is fundamentally dependent on clinical trials and to be specific, it is dependent more on Randomised Clinical Trials.
The history of first successful Randomised Clinical Trials can be traced back to 1944 when the iconic streptomycin was administered to a human being for the treatment of tuberculosis. Extensive studies were conducted on the first subject to evaluate the effects of streptomycin and the subject was discharged in 1947 with a diagnosis of apparently arrested pulmonary tuberculosis. Clinical trials have since rapidly evolved setting new statistical underpinnings and eventually paving ways to more patient-centric trials.
Though the results of randomised clinical trials that are published in international journals are trusted to be the highest level of evidence in medicine, they don’t always prove to be correct. These studies reported in the journals can most of the times be misleading, owing to
- Poor design of RCT’s
- Misinterpretation of RCT’s
Poor design of RCTs is also impacting the pharmaceutical companies by reducing their productivity as measured by R&D and revenues. If we can’t get it right in the design phase, there will be a cascading of untoward effects throughout the development and commercialization of a new drug or vaccine. Owing to which, there has been a lot of research happening on finding ways to improve the design and evaluation of clinical trials.
In this article, we will have a look at the major challenges involved in improving designing and evaluation in clinical trials.
Challenges of improving the design of clinical trials
The most commonly cited challenges are insufficient knowledge of clinical research and methodologies, barriers to ethical and regulatory systems, and lack of funding. In this section, we will have a look at some of the major challenges of improving the design of clinical trials.
Collaborative nature of design
In today’s world, the clinical trial involves a universe of diverse perspectives of various stakeholders who are involved in the study. For instance, research sponsors (industry, NGO, governmental agencies, etc), clinical investigators, patients and regulators. Each of these stakeholders involved in the study would put forth various suggestions and tools that are vital for the research. Owing to the large number of participants involved in the decision-making process, most companies often fail to consider the participant schedules and conflicting priorities.
The major challenge involved here is the assimilation of large and diverse data sets. Significant time, monetary, and other resources have to be dispensed to bring these disparate resources together. Many studies show that the efficiency of the clinical trial design can be significantly improved by streamlining the clinical trial infrastructure.
Lack of clarity and understanding of the clinical research question
Every clinical research begins with a clinical research question that is often vague at the beginning. The researchers must spend adequate time to discuss among the various stakeholders and among themselves to get clarity on the question that they are trying to answer. It is also quite common to see researchers shifting their primary research question from understanding a vague concept to testing a hypothesis or to the analysis of a certain hypothesis based on data from specific data collection instruments.
Either way, it is important that the researchers have clarity on the primary clinical research question and they do not deviate from it. The clinical trial design should solely be based on the primary research question irrespective of the number of secondary research questions that may or may not be present.
Substantial variation among the test subjects
The rule of thumb when it comes to identifying treatment effects in a clinical trial is to keep the variation among the test subjects to a minimum. The larger the variation, the more difficult would it be to properly identify the effects of treatment. If steps are not taken in the design phase of a clinical trial to minimize variation, it can have a negative impact throughout the entire development cycle.
It is important to define consistent and uniform endpoints that could be measured objectively. In clinical trials that involve endpoints that can only be measured subjectively, for instance, Alzheimer’s or dementia, variations among test subjects have to be minimized by clear definitions and consistent evaluations.
Another example would be the case of clinical trials that involve imaging. To minimize the variations, it is important to set certain standardized imaging protocols to manage how images are collected. This can be beneficial in reducing variations that are caused by inconsistent patient positioning.
The other prominent challenges of improving the design on clinical trials include
- Difficulty in reaching a consensus alignment and agreement
- Regulator constraints
- Delays in internal approval
- Pressure on sponsors and investors for faster results
- Lack of flexibility to accommodate changes in the landscape during trials
- Delay in embracing technological advancements such as big data and data analytics.
Challenges of improving the evaluation of clinical trials
- Lack of consideration of external validity criteria in the analysis of clinical trials
Clinical studies can often generate discordant results and results of most clinical trials are accepted without giving sufficient importance to the external validation of results. Many studies have identified the limitations of internal validation in generalizing the diagnostic prediction models. Therefore, to improve the evaluation of clinical trials, there should be a stronger consideration of external validity criteria.
Assessing the external validity of clinical trials can be daunting owing to the lack of a clear description of the target population and target setting, for which the clinical trial claims to be valid.
The tools and methodologies for analyzing the external validity of a clinical trial are already in place and most of them are part of the academic syllabus and found in the general guidelines of clinical trials. Yet, there seems to be a lack of awareness among some researchers in the significance and application of external validation and its tools.
Another prominent challenge is the lack of solid understanding of statistical concepts by some clinicians such as poor p-value interpretation, need for confidence intervals, and the misunderstanding of the Intend-to-treat principle that can negatively impact the evaluation of a clinical trial.