Pragmatic Free Trial Meta
Pragmatic Free Trail Meta is an open data platform that facilitates research into pragmatic trials. It is a platform that collects and shares clean trial data and ratings using PRECIS-2, which allows for multiple and varied meta-epidemiological studies to examine the effects of treatment across trials with different levels of pragmatism, as well as other design features.
Background
Pragmatic studies are increasingly acknowledged as providing evidence from the real world for clinical decision-making. The term "pragmatic", however, is used inconsistently and its definition and assessment require further clarification. The purpose of pragmatic trials is to guide the practice of clinical medicine and policy decisions rather than prove a physiological or clinical hypothesis. A pragmatic trial should try to be as close as it is to real-world clinical practices that include recruiting participants, setting, designing, implementation and delivery of interventions, determination and analysis results, as well as primary analysis. This is a significant distinction from explanation trials (as described by Schwartz and Lellouch1) which are designed to provide more thorough proof of the hypothesis.
The trials that are truly practical should not attempt to blind participants or the clinicians, as this may result in bias in estimates of the effects of treatment. Practical trials should also aim to recruit patients from a wide range of health care settings, to ensure that their findings are generalizable to the real world.
Furthermore, trials that are pragmatic must be focused on outcomes that matter to patients, such as the quality of life and functional recovery. This is especially important for trials involving invasive procedures or those with potential for serious adverse events. The CRASH trial29, for instance, focused on functional outcomes to compare a 2-page case-report with an electronic system for the monitoring of hospitalized patients with chronic heart failure, and the catheter trial28 used urinary tract infections caused by catheters as the primary outcome.
In addition to these aspects pragmatic trials should reduce the procedures for conducting trials and requirements for data collection to cut costs and time commitments. Additionally, pragmatic trials should aim to make their results as relevant to actual clinical practices as they can. This can be achieved by ensuring that their analysis is based on the intention-to treat approach (as described in CONSORT extensions).
Many RCTs that don't meet the criteria for pragmatism, but contain features contrary to pragmatism have been published in journals of varying types and incorrectly labeled pragmatic. This can lead to false claims of pragmatism and the use of the term should be standardized. The creation of the PRECIS-2 tool, which provides a standard objective assessment of pragmatic features is a good initial step.
Methods
In a pragmatic research study, the goal is to inform clinical or policy decisions by demonstrating how an intervention could be integrated into routine care in real-world situations. This is different from explanatory trials that test hypotheses regarding the cause-effect relationship in idealised conditions. In this way, pragmatic trials may have a lower internal validity than explanatory studies and be more susceptible to biases in their design analysis, conduct, and design. Despite their limitations, pragmatic studies can be a valuable source of data for making decisions within the context of healthcare.
The PRECIS-2 tool measures the degree of pragmatism in an RCT by assessing it on 9 domains that range from 1 (very explanatory) to 5 (very pragmatic). In this study, the recruit-ment organization, flexibility in delivery, flexible adherence and follow-up domains received high scores, however the primary outcome and the method of missing data were not at the pragmatic limit. This suggests that a trial could be designed with good pragmatic features, without damaging the quality.
It is hard to determine the level of pragmatism within a specific study because pragmatism is not a have a binary attribute. Certain aspects of a study can be more pragmatic than other. The pragmatism of a trial can be affected by changes to the protocol or logistics during the trial. Additionally, 36% of the 89 pragmatic trials discovered by Koppenaal et al were placebo-controlled or conducted prior to licensing, and the majority were single-center. This means that they are not as common and are only pragmatic if their sponsors are tolerant of the lack of blinding in these trials.
A typical feature of pragmatic research is that researchers attempt to make their findings more meaningful by studying subgroups within the trial. However, this often leads to unbalanced results and lower statistical power, increasing the likelihood of missing or misinterpreting the results of the primary outcome. In the instance of the pragmatic trials that were included in this meta-analysis this was a significant problem because the secondary outcomes were not adjusted for the differences in baseline covariates.
Furthermore practical trials can have challenges with respect to the gathering and interpretation of safety data. This is because adverse events are generally reported by the participants themselves and are susceptible to reporting delays, inaccuracies or coding errors. It is important to improve the quality and accuracy of the results in these trials.
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While the definition of pragmatism may not mean that trials must be 100 percent pragmatic, there are benefits of including pragmatic elements in clinical trials. These include:
Increasing sensitivity to real-world issues, reducing study size and cost, and enabling the trial results to be faster translated into actual clinical practice (by including patients from routine care). But pragmatic trials can have their disadvantages. For example, the right kind of heterogeneity can allow a trial to generalise its results to different patients and settings; however the wrong kind of heterogeneity could reduce assay sensitivity, and thus decrease the ability of a study to detect small treatment effects.
A variety of studies have attempted to categorize pragmatic trials with various definitions and scoring systems. Schwartz and Lellouch1 created a framework to discern between explanation-based studies that support a physiological hypothesis or clinical hypothesis, and pragmatic studies that inform the choice for appropriate therapies in clinical practice. The framework was comprised of nine domains evaluated on a scale of 1-5 with 1 being more explanatory while 5 was more practical. The domains included recruitment of intervention, setting up, delivery of intervention, flex adherence and primary analysis.
The original PRECIS tool3 was built on the same scale and domains. Koppenaal et al10 created an adaptation of this assessment, dubbed the Pragmascope that was simpler to use in systematic reviews. They found that pragmatic systematic reviews had a higher average scores in the majority of domains but lower scores in the primary analysis domain.
This difference in the primary analysis domain could be explained by the fact that most pragmatic trials analyze their data in an intention to treat manner however some explanation trials do not. The overall score was lower for systematic reviews that were pragmatic when the domains on organisation, flexible delivery, and follow-up were merged.
It is important to remember that the term "pragmatic trial" does not necessarily mean a low quality trial, and in fact there is a growing number of clinical trials (as defined by MEDLINE search, however it is neither specific or sensitive) which use the word "pragmatic" in their abstracts or titles. These terms may indicate that there is a greater awareness of pragmatism within abstracts and titles, however it's unclear whether this is reflected in the content.
Conclusions
As the value of evidence from the real world becomes more popular, pragmatic trials have gained popularity in research. They are randomized trials that compare real world treatment options with experimental treatments in development. They involve patient populations closer to those treated in regular medical care. This method is able to overcome the limitations of observational research like the biases that come with the use of volunteers and the limited availability and coding variations in national registries.
Pragmatic trials have other advantages, such as the ability to use existing data sources and a greater chance of detecting significant distinctions from traditional trials. However, they may have some limitations that limit their reliability and generalizability. The participation rates in certain trials may be lower than expected because of the healthy-volunteering effect, financial incentives, or competition from other research studies. The requirement to recruit participants in a timely manner also reduces the size of the sample and the impact of many pragmatic trials. In addition, some pragmatic trials do not have controls to ensure that the observed differences are not due to biases in the conduct of trials.
The authors of the Pragmatic Free Trial Meta identified 48 RCTs that self-described themselves as pragmatic and were published up to 2022. The PRECIS-2 tool was used to assess the pragmatism of these trials. It includes areas such as eligibility criteria and flexibility in recruitment and adherence to intervention and follow-up. They found 14 trials scored highly pragmatic or pragmatic (i.e. scoring 5 or more) in at least one of these domains.
Trials that have a high pragmatism score tend to have more expansive eligibility criteria than traditional RCTs that have specific criteria that are not likely to be used in the clinical setting, and contain patients from a broad range of hospitals. The authors argue that these characteristics can help make the pragmatic trials more relevant and applicable to daily practice, but they don't necessarily mean that a trial using a pragmatic approach is completely free of bias. The pragmatism characteristic is not a definite characteristic and a test that does not have all the characteristics of an explicative study could still yield reliable and beneficial results.