When a clinical trial is conducted at more than one centre it is likely that the true treatment effect will not be identical at each centre. In other words there will be some degree of treatment-by-centre interaction. A number of alternative approaches for dealing with this have been suggested in the literature. These include frequentist approaches with a fixed or random effects model for the observed data and Bayesian approaches. In the fixed effects model, there are two common competing estimators of the treatment difference, based on weighted or unweighted estimates from individual centres. Which one of these should be used is the subject of some controversy and we do not intend to take a particular methodological position in this paper. Our intention is to provide some insight into the relative merits of the indicated range of possible estimators of the treatment effect. For the fixed effects model, we also look at the merits of using a preliminary test for interaction assuming a 10 per cent significance level for the test. In order to make comparisons we have simulated a 'typical' trial which compares an active drug with a placebo in the treatment of hypertension, using systolic blood pressure as the primary variable. As well as allowing the treatment effect to vary between centres, we have concentrated on the particular case where one centre is out of line with the others in terms of its true treatment difference. The various estimators that result from the different approaches are compared in terms of mean squared error and power to reject the null hypothesis of no treatment difference. Overall, the approach that uses the fixed effects weighted estimator of overall treatment difference is recommended as one that has much to offer.

Analysis of Variance↗

PubMedDate not supplied

Dynamic radiographic imaging following total laryngectomy.

Cinepharyngoesophograms of the pharynx were obtained in 51 patients after total laryngectomy for squamous cell carcinoma. The radiological findings were correlated with operative reports and follow-up findings in 47 patients. Postoperative anatomic changes were well-demonstrated radiographically. A spectrum of radiographic findings were observed and included narrowing at the superior surgical closure site in 52% and pseudodiverticula in 47% of all patients. Cricopharyngeal prominence was observed in 15%, fistulae in 10%, and pharyngeal pouches in 6% of all cases. Increased retropharyngeal soft tissue thickness was not found to be indicative of tumor recurrence. We conclude that cineradiography is a useful method for demonstrating both functional and structural changes following laryngectomy for carcinoma.

Adult↗

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Planning for an adaptive design: a case study in COPD.

We discuss the practical and clinical considerations encountered when planning a Phase IIa trial in chronic obstructive pulmonary disease (COPD). Various adaptive strategies for reducing the cost of the trial and the statistical implications of these are explored. Use of the EAST software to evaluate the properties of the study designs with one or more interim analyses for futility, efficacy or either is described. We emphasize the rationale for choosing between alternative designs and the relationship between the clinical and statistical considerations.

Clinical Trials, Phase II as Topic↗

PubMedDate not supplied

Modelling binary data from a three-period cross-over trial.

A new method of analysing binary data from a three-treatment, three-period cross-over trial is described. This method is based on a log-linear model and mirrors the analysis of continuous data. It is an extension of the method we introduced recently for the analysis of binary data from a two-treatment, two-period cross-over trial. We illustrate our method using data from a trial which compared two analgesics and a placebo for the relief of primary dysmenorrhea.

Analgesics↗

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The case for cross-over trials in phase III.

There is a common belief that cross-over trials should not be used in phase III of drug development. This was reinforced by a statement in the draft CPMP Note for Guidance on biostatistical methodology in clinical trials which was circulated for review in March 1993: 'Hence crossover trials in patients should be avoided as far as possible'. We do not share this belief. Historically, many successful drug developments in indications such as hypertension and asthma have depended heavily on cross-over trials in their phase III programmes, leading to regulatory approval for a number of well established medicines. The evidence on which these developments were based appeared sound at the time, and has not been questioned by later experiences with these medicines. Furthermore, the general level of understanding of these medical indications is now even more well developed, and hence the circumstances under which cross-over trials may be used to advantage for new drugs in phase III are even more likely to be correctly identified. There are some well-known disadvantages of cross-over trials relative to parallel group trials. These are reviewed and the ways in which early indications of such problems might be detected in phases I and II or elsewhere will be discussed. However, there are also two key advantages, the well-known one of study size and a less well-known one arising in the context of treatment-by-patient interaction. In phases I and II these advantages lead routinely to the use of the cross-over design. Some methods of analysing cross-over trials have been criticized in a number of recent articles. We compare the properties of a number of alternative analysis strategies by means of simulation and conclude that these concerns about methods of analysis do not imply that cross-over trials should be avoided, especially if baseline measurements can be included in the design. Any small risks attached to their use should not normally concern the regulator as they will tend to diminish estimates of treatment effects rather than enhance them. In summary, cross-over trials remain a potentially valuable research tool in the development of new medicines at all stages including phase III. It is unnecessary and counterproductive to exclude them from use.

Bias↗

PubMedDate not supplied

Some statistical issues in modelling pharmacokinetic data.

A fundamental assumption underlying pharmacokinetic compartment modelling is that each subject has a different individual curve. To some extent this runs counter to the statistical principle that similar individuals will have similar curves, thus making inferences to a wider population possible. In population pharmacokinetics, the compromise is to use random effects. We recommend that such models also be used in data rich situations instead of independently fitting individual curves. However, the additional information available in such studies shows that random effects are often not sufficient; generally, an autoregressive process is also required. This has the added advantage that it provides a means of tracking each individual, yielding predictions for the next observation. The compartment model curve being fitted may also be distorted in other ways. A widely held assumption is that most, if not all, pharmacokinetic concentration data follow a log-normal distribution. By examples, we show that this is not generally true, with the gamma distribution often being more suitable. When extreme individuals are present, a heavy-tailed distribution, such as the log Cauchy, can often provide more robust results. Finally, other assumptions that can distort the results include a direct dependence of the variance, or other dispersion parameter, on the mean and setting non-detectable values to some arbitrarily small value instead of treating them as censored. By pointing out these problems with standard methods of statistical modelling of pharmacokinetic data, we hope that commercial software will soon make more flexible and suitable models available.

Humans↗

PubMedDate not supplied

Simultaneous modelling of flosequinan and its metabolite.

DESIGN: A randomised, double-blind, prospective, placebo-controlled four-way study of the pharmacokinetics of single oral doses of flosequinan. We do not report the placebo data in this paper. Flosequinan was given at doses of 50, 100 and 150 mg, with a 2-week wash-out between periods. Blood samples were taken at a series of times up to 96 h after dosing. SETTING: Clinical pharmacology unit in a pharmaceutical company. PARTICIPANTS: Eighteen healthy volunteers of both genders, aged from 18 years to 55 years. MAIN OUTCOME MEASURES: Plasma concentrations of flosequinan and of its metabolite, flosequinoxan. RESULTS: We demonstrate that it is possible to model parent and metabolite concentration time profiles simultaneously and, in doing so, to estimate the first-pass effect using data from an oral administration. In our modelling approach, we propose a reasonably wide class of statistical models, allowing for left censoring. CONCLUSIONS: A parent-metabolite model that ignores the first-pass results in misleading predictions in a case where significant first-pass metabolism occurs. Thus, in phase-I studies, the new approach described in this paper can provide additional knowledge that may be useful in future formal studies.

Administration, Oral↗