ReviewThe culture of designing hepato-biliary randomised trials
Introduction
The Scottish naval surgeon James Lind started his controlled trial of 12 scurvy-ridden sailors on 20th May 1747 [1]. Lind divided them: two got oranges and lemons, two cider, two vinegar, two elixir vitriol, two a concoction of spices, garlic, and mustard seeds, and two sea water. Within 6 days, the two sailors given oranges and lemons became well. The others did not. Lind was intelligent. His trial marks a major breakthrough. The 20th May is now the International Clinical Trials' Day [2]. Lind was lucky. We seldom see such dramatic intervention effects. We are usually looking for smaller, but still important effects. Such effects, however, may be blurred by random and systematic errors. Scientists have, therefore, developed larger trials using central randomisation, blinding, and intention-to-treat analyses, aiming at reducing random errors and systematic errors to a minimum [1], [3], [4], [5], [6].
Although randomised trials provide the fairest way to test the effects of interventions [1], [3], [4], [5], [6], over 200 years went before the first hepato-biliary randomised trial was published [7]. Thomas C Chalmers and co-workers conducted their two factorial-designed trials on diet, rest, and physical reconditioning in 460 patients with acute infectious hepatitis in 1955 [7]. Other trials in liver diseases followed [8] and hepato-biliary randomised trials appeared regularly from the 1970s (Fig. 1) [9]. Currently over 500 publications on hepato-biliary randomised trials are published each year (Fig. 1) [9]. Here, I describe some of the issues one has to consider when assessing or designing a randomised clinical trial. Further, I contrast the cultures of hepato-biliary randomised trials to randomised trials from any other medical field.
Section snippets
Why is it important to randomise?
The hierarchy of evidence is well-established [10], [11], [12], [13]. It is based on the risks of bias in the different study designs. Randomised trials are internationally considered the gold standard for intervention comparisons [1], [3], [4], [5], [6], [10], [11], [12], [13]. The results from randomised trials form the basis for determining which diagnostics, drugs, drills, or devices are effective. Randomisation forms the basis for making fair comparisons [6].
Historically controlled
What kind of participants to include and which data to collect?
The participants going to be included in a trial should be clearly defined. You should be able to list few entry criteria and few exclusion criteria. The reason for stressing few is that we often see trials with so many in- and exclusion criteria that it becomes difficult to identify such patients in clinical practice. Such trials may have adequate internal validity, but are less valuable due to lack of external validity.
When designing a new trial you want to include patients having a known
Which experimental intervention?
Apart from questions about which diagnostic method, drug dosage, endoscopic technique, or surgical technique to test, it is essential to decide if you want to conduct an explanatory trial or a pragmatic trial.
Explanatory trials test whether an intervention is efficacious. That is, whether the intervention has a beneficial effect in an ideal situation. The explanatory trial seeks to maximise the internal validity by assuring rigorous control of all variables. Explanatory trials often have a
Which comparator: placebo or active?
If there is no evidence-based intervention offered in clinical practice for the potential trial participants, then placebo or ‘sham’ procedure is the right comparator choice. Claims that the Food and Drug Administration and the European Medicines Agency require placebo-controlled trials are wrong.
If a systematic review of low-bias trials or other convincing evidence show that the potential participants should be offered an intervention, the intervention must be offered. There are three
Parallel-group or cross-over randomised trial?
Whether you read a report on a trial or you are going to design a trial, one of the questions you have to answer is: should this trial be a parallel-group or a cross-over trial? Both parallel-group and cross-over trials offer the opportunity to randomise to experimental intervention and comparator. It is, however, a delicate decision when to use one design in stead of the other [42], [43], [44], [45].
In parallel-group trials one randomises consecutive participants fulfilling entry criteria and
Multiple promising interventions: the factorial design
Randomised trials may create plenty of problems if you have one experimental intervention and a comparator. What should you do if you have two experimental interventions that both look promising? You can of course conduct a three-armed randomised trial (experimental A versus experimental B versus control C). If the interventions do not interact, you are far better off conducting a 2 × 2 factorial trial. You obtain the same information with fewer patients plus at the same time you assess any
Cluster randomised trials
Asking a clinician to offer an intervention to half of the patients, you run the risk of contamination in the other half. In such situations you may want to apply your intervention at a higher level than the individual participant, e.g. the individual clinician, group of clinicians, hospital wards, cities, regions, or countries. You hereby randomise trial participants in clusters [48]. Because the responses of participants within clusters can be expected to be more similar than responses of
What is the goal of the trial?
To find the goal of a trial you have to answer the three questions: do you want to show your experimental intervention is superior, equivalent, or non-inferior to your comparator?
The superiority trials are the usual trials (Fig. 2). You want to establish if your experimental intervention is superior to your control. If you do not have a convincing evidence-based intervention that works, the choice of a superiority trial is straightforward. Thirty years ago there were variable approaches to
Sample size estimation in randomised trials
Your sample size estimation depends on the goal of the trial (superiority, equivalence, or non-inferiority) and the type of the primary outcome measure (dichotomous or continuos).
In a superiority trial with a dichotomous primary outcome, the sample size is determined from four pieces of information based on the primary outcome measure [4]:
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The expected proportion of patients with the primary outcome during the trial in the control arm. Very often this variable is grossly overestimated. The
Sample size of randomised trials
Most hepato-biliary randomised trials are too small [9], [34], [37], [40], [51], [52], [54], [55], [56] (Table 2, Table 3). The number of patients included in hepato-biliary randomised trials only varied a little depending on the journal in which they were published [34], [37], [51], [52] (Table 3). The median number of participants per intervention arm was 23 (10th–90th percentiles from 7 to 102) in hepato-biliary trials published in 12 journals during 1985–1996 [54] (Table 2). In
Methodological quality: the risk of bias
Conducting randomised trials with high methodological quality (i.e. avoiding selection, performance, assessment, attrition, and other biases) decreases the risks of bias [28], [29], [30], [31], [32], [33]. We have examined the methodological quality of hepato-biliary randomised trials (Table 2, Table 3, Table 4). Most trials have one or more methodological deficiencies [9], [34], [37], [51], [52], [54], [55], [56].
The low methodological quality raises the question if biased estimates of
Conflicting interests
The impact of conflicts of interests may have profound effects on the results of trials as well as how results are interpreted [63], [64], [65], [66]. It is clear to many that the influence of the drug and device industry has become too large [67].
Discussion
During the last 50 years we have witnessed a very positive increase in the number of randomised trials being conducted (Fig. 1). Compared to randomised trials in general, hepato-biliary trials are less often cross-over trials and more often conducted with adequate generation of allocation sequence and adequate allocation concealment. These are very positive observations. On the other hand, the size, the bias risks, the analysis of and the interpretation of hepato-biliary trials still leave a
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