Randomised Clinical Trials. David Machin. Читать онлайн. Newlib. NEWLIB.NET

Автор: David Machin
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Медицина
Год издания: 0
isbn: 9781119524670
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A Fisher (1890–1962) in laying the foundations of good experimental design, although in an agricultural and biological context, advocated the use of randomisation in allocating experimental treatments. Thus, for example, in agricultural trials various plots in a field are randomly assigned to the different experimental interventions. The argument for randomisation is that it will prevent systematic differences between the allocated plots receiving the different interventions, whether or not these can be identified by the investigator concerned, before the experimental treatment is applied. Then, once the experimental treatments are applied and the outcome observed, the randomisation enables any differences between treatments to be estimated objectively and without bias. In these and many other contexts, randomisation has long been a keystone to good experimental design.

      The need for random allocation extends to all experimental situations including those concerned with patients as opposed to agricultural plots of land. The difficulty arises because clinical trials (more emotive than experiments) do indeed concern human beings who cannot be regarded as experimental units and so should not be allocated the interventions without their consent. The consent process clearly complicates the allocation process and, at least in the past, has been used as a reason to resist the idea of randomisation of patients to treatment. Unfortunately, the other options, perhaps a comparison of patients receiving a ‘new’ treatment with those from the past receiving the ‘old’, are flawed in the sense that any observed differences (or lack thereof) may not reflect the true situation. Thus, in the context of controlled clinical trials, Pocock (1983) concluded, many years ago and some 30 years after the first randomised trials were conducted, that:

      The proper use of randomization guarantees that there is no bias in the selection of patients for the different treatments and so helps considerably to reduce the risk of differences in experimental environment. Randomized allocation is not difficult to implement and enables trial conclusions to be more believable than other forms of treatment allocation.

      As a consequence, we are focussing on randomised controlled trials and not giving much attention to less scientifically rigorous options.

      1.3.3 Design hierarchy

       1.3.3.1 Randomisation

       1.3.3.2 Blinding or masking

      For the simple situation in which the attending clinician is also the assessor of the outcome, the trial should ideally be double‐blind (or double‐masked). This means that neither the patient nor the attending clinician will know the actual treatment allocated. Having no knowledge of which treatment has been taken, neither the patient nor the clinician can be influenced at the assessment stage by such knowledge. In this way, an unprejudiced evaluation of the patient response is obtained. Thus Meggitt, Gray and Reynolds (2006) used double‐blind formulations of Azathioprine or Placebo so that neither the patients with moderate‐to‐severe eczema, nor their attending clinical team, were aware of who received which treatment. Although they did not give details, the blinding is best broken only at the analysis stage once all the data had been collated.

      Finally, and this is possibly the majority situation, there will circumstances in which neither the patient nor the assessor can be blind to the treatments actually received. Such designs are referred to as ‘open’ or ‘open‐label’ trials.

       1.3.3.3 Non‐randomised designs

      In certain circumstances, when a new treatment has been proposed for evaluation, all patients are recruited prospectively but allocation to treatment is not made at random. In such cases, the comparisons may well be biased and hence are unreliable. The bias arises because the clinical team choose which patients receive which intervention and in so doing may favour (even subconsciously) giving one treatment to certain patient types and not to others. In addition, the requirement that all patients should be suitable for all options may not be fulfilled – in that if it is known that a certain option is to be given to a particular subject then one may not so rigorously check if the other options are equally appropriate. Similar problems arise if investigators have recruited patients into a single‐arm study, and the results from these patients are then compared with information on similar patients having (usually in the past) received a relevant standard therapy for the condition in question. However, such historical comparisons are likely to be biased also and to an unknown extent so again it will not be reasonable to ascribe the difference (if any) observed entirely to the treatments themselves. Of course, in either case, there will be situations when one of these designs is the only option available. In such cases, a detailed justification for not using the ‘gold standard’ of the randomised controlled trial is required.

      Understandably, in this era of EBM, information from non‐randomised comparative studies is categorised as providing weaker evidence than that from randomised trials.

      The before‐and‐after design is one in which, for example, patients are treated with the Standard option for a specified period and then, at some fixed point