PubMed · 14689599
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Carl Elliott. 2003. Making us better.. https://pubmed.ncbi.nlm.nih.gov/14689599/
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This paper reviews Bayesian strategies for monitoring clinical trial data. It focuses on a Bayesian stochastic curtailment method based on the predictive probability of observing a clinically significant outcome at the scheduled end of the study given the observed data. The proposed method is applied to derive efficacy and futility stopping rules in clinical trials with continuous, normally distributed and binary endpoints. The sensitivity of the resulting stopping rules to the choice of prior distributions is examined and guidelines for choosing a prior distribution of the treatment effect are discussed. The Bayesian predictive approach is compared to the frequentist (conditional power) and mixed Bayesian-frequentist (predictive power) approaches. The interim monitoring strategies discussed in the paper are illustrated using examples from a small proof-of-concept study and a large mortality trial.
BACKGROUND: In Norway there has in later years been much discussion of misuse of flunitrazepam. From 1 January 2003 the drug was moved up one level in the schedule of controlled substances. On 1 August 2004 the manufacturer of the Rohypnol brand withdrew it from the Norwegian market. How did these two events influence the sales and use of drugs containing flunitrazepam? MATERIALS AND METHODS: Sales figures for drugs containing flunitrazepam from the statistics database at the Norwegian Institute of Public Health were studied. The Norwegian prescription database was used to describe new (incident) users of flunitrazepam and the two brands of this drug sold in Norway in 2004. RESULTS AND DISCUSSION: Restrictions on the prescription status of flunitrazepam lead to a decrease in sales from 7.2 defined daily doses (DDD) per 1000 inhabitants per day in 2002 to 3.0 DDD per 1000 inhabitants per day in 2003. This decrease was only partly compensated for by an increase in the sales of nitrazepam (from 5.0 to 6.0 DDD per 1000 inhabitants per day). During the years 1999 to 2004 there was a steady increase in the sales of benzodiazepine-related hypnotics (zopiclone and zolpidem). This shift could mean a change from flunitrazepam to zopiclone. The withdrawal of Rohypnol in August 2004 had only minor effects on the total sales of flunitrazepam. The decline in sales of Rohypnol was almost compensated for by the increase in the overall sales of Flunipam. This was reflected in the fact that in the later months of 2004 there were many new (incident) users of Flunipam, but few new users of flunitrazepam-containing drugs in total. It could be concluded that the restrictions on prescription status of flunitrazepam had a much higher impact than the withdrawal of the Rohypnol brand.
A sweeping technique, in conjunction with micellar electrokinetic chromatography, for the simultaneous determination of flunitrazepam and its major metabolites, 7-aminoflunitrazepam and N-desmethylflunitrazepam, is described. The optimized conditions for the sweeping and separation were a pH 9.5 buffer, 25mM borate, 50mM cetyltrimethylammonium bromide, 30% MeOH (v/v), and a 151-mm injection length. The calibration functions were all linear with the coefficient of determination (r(2)) exceeding 0.996 for the three target compounds. Using the sweeping procedure, the limits of detection were determined to be 13.4, 5.6, and 12.0ng/mL for flunitrazepam, 7-aminoflunitrazepam, and N-desmethylflunitrazepam, respectively, and the sensitivity enhancement for each compound was within the range of 110-200 fold. The RSDs for the retention time and the peak area were less than 4.10%. The optimized sweeping method was also used to examine a spiked urine sample. We conclude that sweeping with micellar electrokinetic chromatography has considerable potential use in clinical and forensic analyses of flunitrazepam and its metabolites.