Pragmatic clinical trial

Last updated

A pragmatic clinical trial (PCT), sometimes called a practical clinical trial (PCT), [1] is a clinical trial that focuses on correlation between treatments and outcomes in real-world health system practice rather than focusing on proving causative explanations for outcomes, which requires extensive deconfounding with inclusion and exclusion criteria so strict that they risk rendering the trial results irrelevant to much of real-world practice. [2] [3]

Contents

Examples

A typical example is that an anti-diabetic medication in the real world will often be used in people with (latent or apparent) diabetes-induced kidney problems, but if a study of its efficacy and safety excluded some subsets of people with kidney problems (to escape confounding), the study's results may not reflect well what will actually happen in broad practice. PCTs thus contrast with explanatory clinical trials, [3] which focus more on causation through deconfounding. The pragmatic versus explanatory distinction is a spectrum or continuum rather than a dichotomy (each study can fall toward one end or the other), [4] but the distinction is nonetheless important to evidence-based medicine (EBM) because physicians have found that treatment effects in explanatory clinical trials do not always translate to outcomes in typical practice. Decision-makers (including individual physicians deciding what to do next for a particular patient, developers of clinical guidelines, and health policy directors) hope to build a better evidence base to inform decisions by encouraging more PCTs to be conducted. [1]

Distinction from other forms of trials

The distinction between pragmatic and explanatory trials is not the same as the distinction between randomized and nonrandomized trials. Any trial can be either randomized or nonrandomized and have any degree of pragmatic and explanatory power, depending on its study design, with randomization being preferable if practicably available. However, most randomized controlled trials (RCTs) to date have leaned toward the explanatory side of the pragmatic-explanatory spectrum, largely because of the value traditionally placed on proving causation by deconfounding as part of proving efficacy, but sometimes also because "attempts to minimize cost and maximize efficiency have led to smaller sample sizes". [2] The movement toward supporting pragmatic randomized controlled trials (pRCTs) hopes to make sure that money spent on RCTs is well spent by providing information that actually matters to real-world outcomes, [2] regardless of conclusively tying causation to particular variables. This is the pragmatic element of such designs. Thus pRCTs are important to comparative effectiveness research, [2] and a distinction is often (although not always) made between efficacy and effectiveness, whereby efficacy implies causation provided by deconfounding other variables (we know with certainty that drug X treats disease Y by mechanism of action Z) but effectiveness implies correlation with outcomes regardless of presence of other variables (we know with certainty that people in a situation similar to X who take drug A tend to have slightly better outcomes than those who take drug B, and even if we think we may suspect why, the causation is not as important). [5]

Explanation remains important, as does traditional efficacy research, because we still value knowledge of causation to advance our understanding of molecular biology and to maintain our ability to differentiate real efficacy from placebo effects. What has become apparent in the era of advanced health technology is that we also need to know about comparative effectiveness in real-world applications so that we can ensure the best use of our limited resources as we make countless instances of clinical decisions. And it is apparent that explanatory evidence, such as in vitro evidence and even in vivo evidence from clinical trials with tight exclusion criteria, often does not help enough, by itself, with that task. [2]

Other types of pragmatic research

Pragmatism can be used as an epistemology when undertaking any type of research. [6] Examples include systematic reviews, consensus methods such as Delphi [7] and crowdsourcing [8] in fields such as urban planning. [9]

See also

Related Research Articles

<span class="mw-page-title-main">Cognitive behavioral therapy</span> Therapy to improve mental health

Cognitive behavioral therapy (CBT) is a psycho-social intervention that aims to reduce symptoms of various mental health conditions, primarily depression and anxiety disorders. Cognitive behavioral therapy is one of the most effective means of treatment for substance abuse and co-occurring mental health disorders. CBT focuses on challenging and changing cognitive distortions and their associated behaviors to improve emotional regulation and develop personal coping strategies that target solving current problems. Though it was originally designed to treat depression, its uses have been expanded to include many issues and the treatment of many mental health conditions, including anxiety, substance use disorders, marital problems, ADHD, and eating disorders. CBT includes a number of cognitive or behavioral psychotherapies that treat defined psychopathologies using evidence-based techniques and strategies.

Evidence-based medicine (EBM) is "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients." The aim of EBM is to integrate the experience of the clinician, the values of the patient, and the best available scientific information to guide decision-making about clinical management. The term was originally used to describe an approach to teaching the practice of medicine and improving decisions by individual physicians about individual patients.

<span class="mw-page-title-main">Meta-analysis</span> Statistical method that summarizes data from multiple sources

A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. It is thus a basic methodology of metascience. Meta-analytic results are considered the most trustworthy source of evidence by the evidence-based medicine literature.

<span class="mw-page-title-main">Randomized controlled trial</span> Form of scientific experiment

A randomized controlled trial is a form of scientific experiment used to control factors not under direct experimental control. Examples of RCTs are clinical trials that compare the effects of drugs, surgical techniques, medical devices, diagnostic procedures or other medical treatments.

In a blind or blinded experiment, information which may influence the participants of the experiment is withheld until after the experiment is complete. Good blinding can reduce or eliminate experimental biases that arise from a participants' expectations, observer's effect on the participants, observer bias, confirmation bias, and other sources. A blind can be imposed on any participant of an experiment, including subjects, researchers, technicians, data analysts, and evaluators. In some cases, while blinding would be useful, it is impossible or unethical. For example, it is not possible to blind a patient to their treatment in a physical therapy intervention. A good clinical protocol ensures that blinding is as effective as possible within ethical and practical constraints.

Efficacy is the ability to perform a task to a satisfactory or expected degree. The word comes from the same roots as effectiveness, and it has often been used synonymously, although in pharmacology a distinction is now often made between efficacy and effectiveness.

<span class="mw-page-title-main">Number needed to treat</span> Epidemiological measure

The number needed to treat (NNT) or number needed to treat for an additional beneficial outcome (NNTB) is an epidemiological measure used in communicating the effectiveness of a health-care intervention, typically a treatment with medication. The NNT is the average number of patients who need to be treated to prevent one additional bad outcome. It is defined as the inverse of the absolute risk reduction, and computed as , where is the incidence in the treated (exposed) group, and is the incidence in the control (unexposed) group. This calculation implicitly assumes monotonicity, that is, no individual can be harmed by treatment. The modern approach, based on counterfactual conditionals, relaxes this assumption and yields bounds on NNT.

The Dodo bird verdict is a controversial topic in psychotherapy, referring to the claim that all empirically validated psychotherapies, regardless of their specific components, produce equivalent outcomes. It is named after the Dodo character in Alice in Wonderland. The conjecture was introduced by Saul Rosenzweig in 1936, drawing on imagery from Lewis Carroll's novel Alice's Adventures in Wonderland, but only came into prominence with the emergence of new research evidence in the 1970s.

Clinical study design is the formulation of trials and experiments, as well as observational studies in medical, clinical and other types of research involving human beings. The goal of a clinical study is to assess the safety, efficacy, and / or the mechanism of action of an investigational medicinal product (IMP) or procedure, or new drug or device that is in development, but potentially not yet approved by a health authority. It can also be to investigate a drug, device or procedure that has already been approved but is still in need of further investigation, typically with respect to long-term effects or cost-effectiveness.

<span class="mw-page-title-main">Applied kinesiology</span> Alternative medicine technique

Applied kinesiology (AK) is a pseudoscience-based technique in alternative medicine claimed to be able to diagnose illness or choose treatment by testing muscles for strength and weakness.

A hierarchy of evidence, comprising levels of evidence (LOEs), that is, evidence levels (ELs), is a heuristic used to rank the relative strength of results obtained from experimental research, especially medical research. There is broad agreement on the relative strength of large-scale, epidemiological studies. More than 80 different hierarchies have been proposed for assessing medical evidence. The design of the study and the endpoints measured affect the strength of the evidence. In clinical research, the best evidence for treatment efficacy is mainly from meta-analyses of randomized controlled trials (RCTs). Systematic reviews of completed, high-quality randomized controlled trials – such as those published by the Cochrane Collaboration – rank the same as systematic review of completed high-quality observational studies in regard to the study of side effects. Evidence hierarchies are often applied in evidence-based practices and are integral to evidence-based medicine (EBM).

<span class="mw-page-title-main">Observational study</span> Study with uncontrolled variable of interest

In fields such as epidemiology, social sciences, psychology and statistics, an observational study draws inferences from a sample to a population where the independent variable is not under the control of the researcher because of ethical concerns or logistical constraints. One common observational study is about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. This is in contrast with experiments, such as randomized controlled trials, where each subject is randomly assigned to a treated group or a control group. Observational studies, for lacking an assignment mechanism, naturally present difficulties for inferential analysis.

<span class="mw-page-title-main">Vaccine efficacy</span> Reduction of disease among the vaccinated comparing to the unvaccinated

Vaccine efficacy or vaccine effectiveness is the percentage reduction of disease cases in a vaccinated group of people compared to an unvaccinated group. For example, a vaccine efficacy or effectiveness of 80% indicates an 80% decrease in the number of disease cases among a group of vaccinated people compared to a group in which nobody was vaccinated. When a study is carried out using the most favorable, ideal or perfectly controlled conditions, such as those in a clinical trial, the term vaccine efficacy is used. On the other hand, when a study is carried out to show how well a vaccine works when they are used in a bigger, typical population under less-than-perfectly controlled conditions, the term vaccine effectiveness is used.

Clinical trials are medical research studies conducted on human subjects. The human subjects are assigned to one or more interventions, and the investigators evaluate the effects of those interventions. The progress and results of clinical trials are analyzed statistically.

Implementation research is the systematic study of methods that support the application of research findings and other evidence-based knowledge into policy and practice. It aims to understand the most effective pathways from research to practical application, particularly in areas such as health, education, psychology and management. Intervention research, also known as intervention science, evaluates how various interventions or approaches are adopted and applied in “real world” settings in order to establish an understanding of their effectiveness in different contexts.

<span class="mw-page-title-main">Placebo-controlled study</span>

Placebo-controlled studies are a way of testing a medical therapy in which, in addition to a group of subjects that receives the treatment to be evaluated, a separate control group receives a sham "placebo" treatment which is specifically designed to have no real effect. Placebos are most commonly used in blinded trials, where subjects do not know whether they are receiving real or placebo treatment. Often, there is also a further "natural history" group that does not receive any treatment at all.

In epidemiology and biomedicine, biological plausibility is the proposal of a causal association—a relationship between a putative cause and an outcome—that is consistent with existing biological and medical knowledge.

<span class="mw-page-title-main">Phases of clinical research</span> Clinical trial stages using human subjects

The phases of clinical research are the stages in which scientists conduct experiments with a health intervention to obtain sufficient evidence for a process considered effective as a medical treatment. For drug development, the clinical phases start with testing for drug safety in a few human subjects, then expand to many study participants to determine if the treatment is effective. Clinical research is conducted on drug candidates, vaccine candidates, new medical devices, and new diagnostic assays.

The philosophy of medicine is a branch of philosophy that explores issues in theory, research, and practice within the field of health sciences. More specifically in topics of epistemology, metaphysics, and medical ethics, which overlaps with bioethics. Philosophy and medicine, both beginning with the ancient Greeks, have had a long history of overlapping ideas. It was not until the nineteenth century that the professionalization of the philosophy of medicine came to be. In the late twentieth century, debates among philosophers and physicians ensued of whether the philosophy of medicine should be considered a field of its own from either philosophy or medicine. A consensus has since been reached that it is in fact a distinct discipline with its set of separate problems and questions. In recent years there have been a variety of university courses, journals, books, textbooks and conferences dedicated to the philosophy of medicine.

Real world data (RWD) in medicine is data derived from a number of sources that are associated with outcomes in a heterogeneous patient population in real-world settings, including but not limited to electronic health records, health insurance claims and patient surveys. While no universal definition of real world data exists, researchers typically understand RWD as distinct from data sourced from randomized clinical trials.

References

  1. 1 2 Tunis, SR; Stryer, DB; Clancy, CM (2003), "Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy", JAMA, 290 (12): 1624–1632, doi:10.1001/jama.290.12.1624, PMID   14506122.
  2. 1 2 3 4 5 Mullins, CD; Whicher, D; Reese, ES; Tunis, S; et al. (2010), "Generating evidence for comparative effectiveness research using more pragmatic randomized controlled trials", Pharmacoeconomics, 28 (10): 969–976, doi:10.2165/11536160-000000000-00000, PMID   20831305, S2CID   33592391.
  3. 1 2 Schwartz, D; Lellouch, J; et al. (1967), "Explanatory and pragmatic attitudes in therapeutical trials", J Chronic Dis, 20 (8): 637–648, doi:10.1016/0021-9681(67)90041-0, PMID   4860352.
  4. Thorpe, KE; et al. (2009), "A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers", J Clin Epidemiol, 62 (5): 464–475, doi:10.1016/j.jclinepi.2008.12.011, PMC   2679824 , PMID   19348971.
  5. Zimmer, Carl (20 November 2020). "2 Companies Say Their Vaccines Are 95% Effective. What Does That Mean? You might assume that 95 out of every 100 people vaccinated will be protected from Covid-19. But that's not how the math works". The New York Times. Retrieved 21 November 2020.
  6. Yvonne Feilzer, Martina (2010-01-01). "Doing Mixed Methods Research Pragmatically: Implications for the Rediscovery of Pragmatism as a Research Paradigm". Journal of Mixed Methods Research. 4 (1): 6–16. doi:10.1177/1558689809349691. ISSN   1558-6898. S2CID   220267495.
  7. Amos, Trevor (2008). "Pragmatic research design. An illustration of the use of the Delphi technique". Electronic Journal of Business Research Methods. 6 (2): 95–102.
  8. Eklund, Lina; Stamm, Isabell; Liebermann, Wanda Katja (2019-10-01). "The crowd in crowdsourcing: Crowdsourcing as a pragmatic research method". First Monday. 4 (10). doi: 10.5210/fm.v24i10.9206 . ISSN   1396-0466. S2CID   204699798.
  9. te Brömmelstroet, Marco (2017-10-01). "Towards a pragmatic research agenda for the PSS domain". Transportation Research Part A: Policy and Practice. 104: 77–83. doi:10.1016/j.tra.2016.05.011. ISSN   0965-8564. S2CID   156431540.