Explanatory and pragmatic trials

Optimizing the design of pragmatic trials: key issues remain

Clinical trials have largely focused on whether an intervention can work. To ensure valid and powerful testing of this hypothesis, trials attempt to maximize the effect of the intervention of interest, controlling other factors that can confound comparisons. The benefits observed in these studies are often not sustained once the treatment is used in routine care, leaving regulators, practitioners and patients with a paucity of reliable evidence to assist decision-making. Attempts to address this need have led to 'pragmatic trials' that prioritize applicability of findings to real-world practice by minimizing design features that produce less pertinent information. Minimizing biases in this pragmatic context remains a very difficult task, however. This paper reviews some of these challenges and highlights specific aspects of design that must be approached with a pragmatic attitude.

Dichotomizing rating scale scores in psychiatry: a bad idea?

In psychiatry, the use of rating scales as measures of outcome in clinical trials allows us to generate continuous outcome data, where each individual's outcome is measured in numbers. Continuous outcomes can be divided into two categories, such as improved and not improved, or may be kept continuous. This article briefly presents the main advantages and disadvantages of these two approaches, which are commonly employed in the analyses of rating scale scores in clinical trials and systematic reviews.

Why internal and external validity of experimental studies are relevant for clinical practice?

In randomised controlled trials (RCTs) there are two types of validity: internal validity and external validity. Internal validity refers to the extent to which the observed difference between groups can be correctly attributed to the intervention under investigation. In other words, it is the extent to which the design and conduct of the trial eliminate error. Internal validity might be threatened by two types of errors: systematic error (also called bias) and chance error (also called random error or statistical error) (Keirse & Hanssens, 2000. Systematic error, or bias, may be the consequence of erroneous ways of collecting, analysing and interpreting data. This may produce differences between treatments that are not real, with an overestimation or an underestimation of the true beneficial or harmful effect of an intervention (Juni et al., 2001). In RCTs there are four types of bias: selection bias (when the groups differ in baseline characteristics because of the way participants are selected), performance bias (when the care provided to the trial participants differs systematically between the experimental and control group), detection bias (when there are systematic differences in outcome assessment), and attrition bias (when the loss of participants from the study systematically differs between the experimental and control group). By contrast, chance error, or statistical error, is due to outcome variability that may arise by chance alone. Studies with small sample sizes are more likely to incur in this type of error than studies with large sample sizes. Thus, the risk of random error may be minimised by recruiting sufficiently large samples of patients.

Outcome reporting bias in clinical trials

Randomised controlled trials (RCTs) are designed and powered to measure one single outcome, calledprimary outcome(Sibbald & Roland, 1998; Barbuiet al., 2007). The primary outcome is the pre-specified outcome of greatest clinical importance and is usually the one used in the sample size calculation (Accordini, 2007). In addition to the primary outcome, RCTs may have several other outcomes, calledsecondary outcomes. In contrast with the analysis of the primary outcome, the analysis of secondary outcomes and its interpretation may be complicated by at least two factors:1)

Rationale and design of an independent randomised controlled trial evaluating the effectiveness of aripiprazole or haloperidol in combination with clozapine for treatment-resistant schizophrenia

BACKGROUND

One third to two thirds of people with schizophrenia have persistent psychotic symptoms despite clozapine treatment. Under real-world circumstances, the need to provide effective therapeutic interventions to patients who do not have an optimal response to clozapine has been cited as the most common reason for simultaneously prescribing a second antipsychotic drug in combination treatment strategies. In a clinical area where the pressing need of providing therapeutic answers has progressively increased the occurrence of antipsychotic polypharmacy, despite the lack of robust evidence of its efficacy, we sought to implement a pre-planned protocol where two alternative therapeutic answers are systematically provided and evaluated within the context of a pragmatic, multicentre, independent randomised study.

METHODS/DESIGN

The principal clinical question to be answered by the present project is the relative efficacy and tolerability of combination treatment with clozapine plus aripiprazole compared with combination treatment with clozapine plus haloperidol in patients with an incomplete response to treatment with clozapine over an appropriate period of time. This project is a prospective, multicentre, randomized, parallel-group, superiority trial that follow patients over a period of 12 months. Withdrawal from allocated treatment within 3 months is the primary outcome.

DISCUSSION

The implementation of the protocol presented here shows that it is possible to create a network of community psychiatric services that accept the idea of using their everyday clinical practice to produce randomised knowledge. The employed pragmatic attitude allowed to randomly allocate more than 100 individuals, which means that this study is the largest antipsychotic combination trial conducted so far in Western countries. We expect that the current project, by generating evidence on whether it is clinically useful to combine clozapine with aripiprazole rather than with haloperidol, provides physicians with a solid evidence base to be directly applied in the routine care of patients with schizophrenia.

Understanding antipsychotic non-classical prescriptions: a quantitative and qualitative approach

AIMS

To date only a few studies investigated the clinical reasons supporting and explaining non-classical antipsychotic prescriptions. The present study was carried out to develop concepts which help understand this phenomenon in a natural setting, giving emphasis to views of clinicians according to quali - quantitative research methodologies.

SUBJECTS

From the South-Verona Psychiatric Case Register all antipsychotic prescriptions issued during 2005 were extracted. Concurrent prescribing of two or more antipsychotics, prescribing antipsychotic drugs outside the licensed indications, and outside the licensed ranges of doses reported in the Italian National Formulary, were considered non-classical prescriptions. Reasons for non-classical prescriptions were collected by means of brainstorming sessions with clinicians. Non-classical prescriptions and the corresponding reasons were grouped according to whether they were "clinically sound" or "clinically not sound".

RESULTS

During 2005 a total of 259 patients received 376 non-classical prescriptions. The most frequently reported reasons for non-classical prescribing were that prescriptions were inherited from another clinician with or without benefit, and that prescriptions were motivated by the need of reducing psychotic symptoms. More than 60% of these non-classical prescriptions were categorised as "clinically sound". Clinically not sound prescriptions were related with negative clinicians' views and opinions about the patient/clinician relationship.

CONCLUSION

Clinically not sound prescriptions appeared just a reflection of a problematic doctor/patient relationship, where no individual treatment plan existed and psychiatric visits had the only goal of monitoring ongoing prescriptions.

A simple approach to manage dosages in drug-epidemiology research

In the study of the beneficial and adverse effects of psychotropic drugs, in addition to experimental studies (Barbui et al., 2007), epidemiological studies may provide interesting insights. A key methodological aspect in drug utilization studies is how drug consumption should be measured. Specifically, the need is to end up with a single variable that may be reliably used to indicate the overall consumption, for each patient included in a certain survey, of one specific drug (for example one antipsychotic, say haloperidol) or a specific drug class (for example second-generation antipsychotics) or a group of drugs (for example psychotropic drugs, including antipsychotics plus antidepressants plus benzodiazepines). Not only such a variable has to accommodate the problem that actual doses cannot be directly compared, but also that many patients often receive more than one drug, belonging to different or to the same pharmacological class. A methodology is therefore needed to convert each medication dosage into a standardised measure that allows to calculate, for each patient, a cumulative index of drug consumption. Standardised measures of drug consumption are also beneficial for national and international comparisons, for the evaluation of time trends in drug use, and for assessing the public health impact of specific events (for example a change in reimbursement status).