Pregabalin demonstrated modest efficacy in pain, global assessment, and function in FM at 450 mg/day, and improved sleep across all dose levels, but it did not provide consistent evidence of benefit at 300 and 600 mg/day in this study. Pregabalin was generally well tolerated for the treatment of FM. (Clinical trial registry NCT00333866).

A large number of analgesics have failed to prove superiority over placebo in randomized controlled trials (RCTs), and as this has been related to increasing placebo responses, there is currently an interest in specifying predictors of the placebo response. The literature on placebo mechanisms suggests that factors related to patients' expectations of treatment efficacy are pivotal for the placebo response. Also, general characteristics of RCTs have been suggested to influence the placebo response. Yet, only few meta-analyses have directly tested these hypotheses. Placebo data from 9 industrially sponsored, randomized, double-blind, placebo-controlled, multicenter phase III trials in 2017 adult patients suffering from chronic painful osteoarthritis (hip or knee) or low back pain were included. The primary outcome was pain intensity. Based on previous studies, we chose 3 expectancy-related primary predictors: type of active medication, randomization ratio, and number of planned face-to-face visits. In addition, explorative analyses tested whether RCT and patients' characteristics predicted the placebo response. Opioid trials, a high number of planned face-to-face visits, and randomization ratio predicted the magnitude of the placebo response, thereby supporting the expectancy hypothesis. Exploratory models with baseline pain intensity, age, washout length, and discontinuation because of adverse events accounted for approximately 10% of the variability in the placebo response. Based on these results and previous mechanisms studies, we think that patients' perception of treatment allocation and expectations toward treatment efficacy could potently predict outcomes of RCTs.

The minimum clinically important difference (MCID) between treatments is recognized as a key concept in the design and interpretation of results from a clinical trial. Yet even assuming such a difference can be derived, it is not necessarily clear how it should be used. In this paper, we consider three possible roles for the MCID. They are: (1) using the MCID to determine the required sample size so that the trial has a pre-specified statistical power to conclude a significant treatment effect when the treatment effect is equal to the MCID; (2) requiring with high probability, the observed treatment effect in a trial, in addition to being statistically significant, to be at least as large as the MCID; (3) demonstrating via hypothesis testing that the effect of the new treatment is at least as large as the MCID. We will examine the implications of the three different possible roles of the MCID on sample size, expectations of a new treatment, and the chance for a successful trial. We also give our opinion on how the MCID should generally be used in the design and interpretation of results from a clinical trial.

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Women with interstitial cystitis/bladder pain syndrome and patients with symptoms suggesting the concomitant presence of nonurological associated somatic syndromes were more likely to experience significant pain reduction with tanezumab than with placebo therapy. In contrast, no difference was reported in response between tanezumab and placebo therapy for men with chronic prostatitis/chronic pelvic pain syndrome symptoms only.