Unique design issues in clinical trials of patients with bipolar affective disorder.
Two National Institute of Mental Health-sponsored meetings of experts on bipolar illness (in 1989 and 1994) noted a paucity of clinical psychopharmacological trials in this illness which has now extended over the past two decades. One of the reasons elucidated for this neglect was a lack of agreement in the field as to what constituted an optimal clinical trial design, consequently resulting in low-priority scores for funding of studies in bipolar illness. In this paper, we note some of the characteristics of bipolar illness that make it particularly difficult to study and find such agreed upon trial designs. Some of the assets and liabilities of the well-accepted traditional parallel group, placebo-controlled, randomized clinical trial (RCT) are reviewed, and a series of other potential design options, such as crossover, enrichment, off-on-off-on (B-A-B-A), and N-of-1 trials, are discussed that may help to better address some of the unique clinical characteristics of bipolar illness. Finally, a variety of statistical approaches to analyzing data in off-on-off-on trial designs, and in helping to predetermine necessary durations of clinical trials in individual patients with bipolar disorders, are suggested. Acceptance of a wider variety of clinical trial designs may help facilitate the funding and accelerate the acquisition of new data on treatment of bipolar illness.
Post
Robert M
RM
Biological Psychiatry Branch, National Institute of Mental Health, National Institutes of Health, Bldg. 10, Rm. 3S239, 10 Center Drive, MSC-1272, Bethesda, MD 20892-1272, USA. robert.post@nih.gov
Luckenbaugh
David A
DA
D001714:Bipolar Disorder / Q000628:therapy*; D002986:Clinical Trials as Topic / Q000145:classification / Q000379:methods / Q000706:statistics & numerical data / Q000639:trends; D018592:Cross-Over Studies; D004311:Double-Blind Method; D005240:Feasibility Studies; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000145:classification / Q000706:statistics & numerical data; D012107:Research Design; D013223:Statistics as Topic