Alcoholism and alcohol abuse compose a large, worldwide public health problem that is responsible for significant morbidity and mortality (Mokdad et al., 2004
). To this point, the most common form of treatment for alcohol dependence in the USA has been group counseling and referral to community support groups. Three medications – disulfiram, naltrexone, and acamprosate – have been approved for the treatment of alcohol dependence although the use of these medications is limited. Further, there is no single medication that is effective in every case or every person. Craving is an instrumental component of alcohol dependence and can involve a desire for the reward provided by alcohol, the need for relief from tension, or an obsessive loss of control over one’s thoughts about alcohol; hence, the most promising and efficacious medications are those that interfere with the neurotransmitters involved in craving mechanisms (Addolorato et al., 2005
). The development of new and more effective medications to treat alcoholism remains a high priority (Willenbring, 2007
Many clinical trials have been used to evaluate the efficacy and safety of new medications to treat alcoholism. Most of them involve two arms: a treatment arm and a control arm. It is often of particular interest to clinicians, however, to determine the optimal dose from a range of doses. In this case, two-arm studies are insufficient. For instance, in the single-site topiramate study (Johnson et al., 2003
), topiramate’s (or matching placebo’s) dose started at 25
mg for week 1, with a 25-mg increment in weeks 2–4 and a 50-mg increment in weeks 5–8 (up to a total dose of 300
mg). The topiramate dose of 300
mg was maintained between weeks 8 and 12. A similar dose-escalating scheme was employed in the multi-site topiramate study (Johnson et al., 2007
). These proof-of-concept trials established the overall topiramate treatment effect at improving drinking outcomes. However, the topiramate effect at different dose levels remains to be established so that we can identify the best dose that has the satisfactory efficacy while minimizing the rate of adverse events.
A possible solution to this problem lies in the use of an adaptive design made up of two parts. The goal of the first part would be to determine the most promising dose of topiramate and to optimize the number of patients treated at that dose level while including enough patients at neighboring doses to examine accurately the relationship. In other words, we want to locate the dose that provides the best chance for success from among a set of doses. In the second part of the design, the optimal dose found in the first stage would be compared with a placebo arm in a randomized study to establish the statistical significance of the treatment. This stage is imperative because it guards against the unlikely situation in which the optimal dose, although more efficacious than any other dose, is not more successful than placebo.
The motivation behind adaptive designs is to make use of the statistical advantages of a sequential design in combination with the ethical considerations of treating as many patients as possible at a dose believed to be the best, given prior knowledge, and accumulated data. For traditional dose-finding designs in cancer, aimed at controlling adverse events, the optimal dose is defined in correspondence to a tolerable level of toxicity, i.e., maximum tolerated dose (MTD). For designs whose aim is to identify the most successful dose (MSD), the optimal dose is the one that maximizes the overall success rate, considering both treatment benefit (efficacy) and failure. Here, failure would be defined as either unacceptable toxicity or dropout as a result of not being able to tolerate the treatment or the absence of sufficient benefit. To address the questions raised above, we can make use of the dose-finding methodology that has been used successfully in the cancer and HIV settings over the last 30
years. One such method is the continual reassessment method (CRM; O’Quigley et al., 1990
), which makes use of working statistical models that have some optimal operating characteristics.
However, the implementation of adaptive designs is often challenging and is generally not readily available to practitioners. Consequently, these designs are not commonly applied in alcohol dependence trials. In this article, we will give a review of such methods and illustrate how we can apply them in the alcohol treatment field. The paper is organized as follows. In “Recent developments in dose-finding”, we give a basic introduction to the dose-finding background, mostly the original CRM to locate the MTD and MSD. In “Studies with topiramate”, we provide an example of identifying the optimal dose from a range of doses in an alcohol dependence trial. We conclude the paper with some discussion on future work.