Intended for healthcare professionals

Clinical Review

Understanding controlled trials: What are pragmatic trials?

BMJ 1998; 316 doi: (Published 24 January 1998) Cite this as: BMJ 1998;316:285
  1. Martin Roland, director of research and developmenta,
  2. David J Torgerson, research fellowb
  1. National Primary Care Research and Development Centre, University of Manchester, Manchester M13 9PL
  2. National Primary Care Research and Development Centre, Centre for Health Economics, University of York, York YO1 5DD
  1. Correspondence to: Professor Roland

    Trials of healthcare interventions are often described as either explanatory or pragmatic. Explanatory trials generally measure efficacy-the benefit a treatment produces under ideal conditions, often using carefully defined subjects in a research clinic. Pragmatic trials measure effectiveness-the benefit the treatment produces in routine clinical practice.

    An explanatory approach recruits as homogeneous a population as possible and aims primarily to further scientific knowledge. By contrast, the design of a pragmatic trial reflects variations between patients that occur in real clinical practice and aims to inform choices between treatments. To ensure generalisability pragmatic trials should, so far as possible, represent the patients to whom the treatment will be applied. The need for purchasers and providers of health care to use evidence from trials in policy decisions has increased the focus on pragmatic trials.

    While the intervention should be described precisely for both types of trial, in pragmatic trials this does not mean that the same treatment is offered to each patient. If, for example, two physiotherapy approaches are being evaluated for back pain the protocol may allow for the physiotherapist to apply different treatments to different patients: it is then the management protocol which is the subject of the investigation, not the individual treatments.

    Randomisation deals with the main source of bias in clinical research-selection bias. However, several other sources of bias may affect the results. Biased assessment of outcome may occur when the researcher is aware of which treatment has been given: this is dealt with in both explanatory and pragmatic trials by having an independent assessor who is blind to treatment allocation. However, bias can also occur when patient or clinician is aware of the treatment being given; in explanatory trials this is dealt with by blinding both patient and clinician to the treatment.

    While pragmatic trials may also be blinded, this is not always possible. Placebos are not generally used in pragmatic trials, as they aim to help clinicians decide between a new treatment and the best current treatment. Clinician and patient biases are not necessarily viewed as detrimental in a pragmatic trial but accepted as part of physicians' and patients' responses to treatment and included in the overall assessment. In pragmatic approaches, therefore, the treatment response is the total difference between two treatments, including both treatment and associated placebo effects, as this will best reflect the likely clinical response in practice.

    Outcome measures differ between explanatory and pragmatic approaches. In explanatory trials intermediate outcomes are often used, which may relate to understanding the biological basis of the response to the treatment-for example, a reduction in blood pressure. In pragmatic trials they should represent the full range of health gains-for example, a reduction in stroke and improvement in quality of life.

    In a pragmatic trial it is neither necessary nor always desirable for all subjects to complete the trial in the group to which they were allocated. However, patients are always analysed in the group to which they were initially randomised (intention to treat analysis), even if they drop out of the study or change groups.

    The two approaches to trial design will sometimes arrive at different conclusions about the benefit of a treatment, either because a treatment which works in an ideal setting does not work in real life or because improvement in a biomedical endpoint does not produce the expected health gain-for example, sodium fluoride increases non-vertebral bone density in osteoporosis but increases fracture rates.2 Clinicians need to understand these two approaches when reading trial reports, to judge the relevance of the findings to their own clinical practice.


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