ABSTRACT
BACKGROUND: Many aspects of study conduct impact the observed effect size of treatment. Data were utilized from a recently published meta-analysis of randomized, double-blind, placebo-controlled, clinical trials performed for the United States Food and Drug Administration (FDA) approval of full mu-agonist opioids for the treatment of chronic pain. METHODS: The number of study sites in each clinical trial and standardized effect size (SES) were extracted and computed. Standardized effect size was plotted against number of sites, and a two-piece linear model was fit to the plot. Ten studies were included. RESULTS: The SES decreased linearly by 0.13 units for every 10 sites (p=0.037), from 0.75 to 0.36, until an inflection point of 60 sites, after which SES did not decline further. The total number of subjects required for 90% power to discriminate drug from placebo increased from 78 to 336 subjects going from 30 to 60 sites. CONCLUSION: Results showed that the number of sites was a source of loss of assay sensitivity in clinical trials, which may contribute to the well-known problem of failure to successfully transition from Phase 2 to Phase 3 clinical development. Potential solutions include minimizing the number of sites, more rigorous and validated training, central statistical monitoring with rapid correction of performance issues, and more rigorous subject and site selection.
ABSTRACT
Inner-city children have high rates of asthma. Exposures to particles, including allergens, may cause or exacerbate asthma symptoms. As part of an epidemiologic study of inner-city children with asthma, continuous (10-min average) measurements of particle concentrations were made for 2-week periods in 294 homes drawn from seven cities. Measurements were made using an optical scattering device that is most sensitive to fine particles. The concentrations recorded by these devices were corrected to agree with colocated outdoor gravimetric PM2.5 monitors. Indoor concentrations in the homes averaged 27.7 (standard deviation = 35.9) micro g/m3, compared with concurrent outdoor concentrations of 13.6 (7.5) micro g/m3. A multivariate model indicated that outdoor particles penetrated indoors with an efficiency of 0.48 and were therefore responsible for only 25% of the mean indoor concentration. The major indoor source was smoking, which elevated indoor concentrations by 37 micro g/m3 in the 101 homes with smokers. Other significant sources included frying, smoky cooking events, use of incense, and apartment housing, although the increases due to these events ranged only from 3 to 6 micro g/m3. The 10-min averaging time allowed calculation of an average diurnal variation, showing large increases in the evening due to smoking and smaller increases at meal times due to cooking. Most of the observed variance in indoor concentrations was day to day, with roughly similar contributions to the variance from visit to visit and home to home within a city and only a small contribution made by variance among cities. The small variation among cities and the similarity across cities of the observed indoor air particle distributions suggest that sources of indoor concentrations do not vary considerably from one city to the next, and thus that simple models can predict indoor air concentrations in cities having only outdoor measurements.