This is the second installment of a new series in which clinically relevant research is briefly discussed and, perhaps more important, a few tips on how to read and interpret research studies are presented. Your feedback, suggestions, and questions are eagerly solicited at email@example.com
More efficacious treatments are sorely needed for the treatment of the major depressive episodes of bipolar I and bipolar II disorders (“bipolar depression”). For example, lamotrigine(Drug information on lamotrigine) has been found to be more effective than placebo for delaying occur-rence of both depressive and, to a lesser extent, manic episodes during 18 months in patients with bipolar I disorder (who were recently or currently in a manic, mixed, or depressive episode and whose condition was first stabilized with the use of lamotrigine).1 Its efficacy in the acute phase of bipolar depression is, however, much less clear.
The published literature on the treatment of acute bipolar depression with lamotrigine was somewhat misleading until recently. One clinical trial found lamotrigine to be more efficacious than placebo on at least some of the outcome measures.2
The American Psychiatric Association’s practice guideline for bipolar disorder advocates using lamotrigine as one of the first-line options for bipolar depression.3 However, 4 other randomized, placebo-controlled clinical trials (similar in size to the published one) were not published (although the results of 1 of these 4 were mentioned as part of a review article). These 4 trials did not find lamotrigine to be more efficacious than placebo on most of the outcome measures. This was a prominent example of publication bias in which studies that fail to find a treatment to be effective are much less likely to be published, thus significantly biasing the published literature in favor of the proposed treatment.4
TIP: In assessing whether a particular treatment is efficacious for a particular disorder, or reading a review or meta-analysis that attempts to do this, it is essential that all randomized, controlled clini-cal trials on the topic be taken into consideration. Unfortunately, this is commonly not done, so readers must be vigilant for this.
Finally, in 2008 the results of all 5 randomized, placebo-controlled studies of the efficacy of lamotrigine monotherapy for acute bipolar depression were published in a single article.5
These studies randomized about 200 patients each and lasted for 7 to 10 weeks. Three of the studies included only patients with bipolar I disorder, 1 included only those with bipolar II disorder, and 1 included patients with both. The final dosage of lamotrigine was 200 mg/d in 3 studies, 1 study compared 50 mg/d and 200 mg/d with placebo, and 1 study used a flexible dosage between 100 and 400 mg/d.
In each study, 1 of the 2 clinician-rated depression severity scales that were completed in all 5 studies (Hamilton Depression Rating Scale [HDRS] and the Montgomery-Asberg Depression Rating Scale) was identified as the “primary” outcome measure. Other outcome measures (for example, the Clinical Global Impression–Severity scale, and the Clinical Global Impression–Improvement scale) were considered “secondary” outcome measures.
TIP: Why have multiple outcome measures? In clinical trials, it is standard practice to measure the same outcome by more than 1 method and to evaluate a variety of outcomes. This is because different outcome measures may capture a different aspect of change and to a different extent. For example, rating scales for severity of depression that cover a specified list of symptoms in a specified way may reach different conclusions from the Clinical Global Impression–Improvement scale in which clinicians assess patients and simply rate the patient as being “minimally improved,” “much improved,” “very much improved,” and so on.
TIP:Why would 1 of the measures be identified as the “primary” outcome measure? Statistical testing is based on probability. The more times you flip a coin, the more chances that there will be at least 1 tail. Similarly, if multiple statistical tests are done to compare several different outcome measures, this increases the likelihood that at least 1 of the tests will be “statistically significant” just by chance. Therefore, researchers should identify in advance that 1 of the comparisons is the “primary” outcome measure.
The difference in improvement in severity of depression between patients treated with lamotrigine or placebo, on the basis of the depression rating scale that was the predefined primary outcome measure for that study, was not statistically significant in any of the 5 studies (ie, was not such that it was unlikely to have been due to chance). In 1 study, lamotrigine was statistically significantly better than placebo on improvement as assessed by important secondary outcome measures.2,5 In the other 4 studies, however, lamotrigine was not statistically significantly better than placebo even on the secondary outcome measures.5