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Patient safety was monitored by phone call on day 7 and at a clinic visit on day 30 after administration of the last dose of study medication. The sample size and numbers of patients assigned to each dose was determined by adaptive randomization27 rather than pair-wise comparisons. The primary endpoint, which was the change from baseline in postprandial fullness/early satiety GCSI score subscale, was used for dose�Cresponse model and patients were randomized to different doses using an adaptive allocation scheme. For the first 12 patients enrolled in the study, equal numbers of patients were randomly assigned across study dose groups. After that, the randomization probabilities were adjusted to reflect the accumulated data on the primary http://www.selleckchem.com/products/azd9291.html endpoint (for http://www.selleckchem.com/products/carfilzomib-pr-171.html example, if the effect appeared to be larger in one study dose group, more patients were assigned to that group as enrollment continued). An Interactive Web Response System (IWRS) was used to dynamically randomize patients based on statistical output performed on a weekly basis. The relationship between change in the subscale score and dose was modeled using a normal dynamic linear model (NDLM) as described by West and Harrison.28 The NDLM did not assume a monotonic relationship and flexibly modeled the dose�Cresponse curve. The objective was finding the best dose for the subscale score improvement while validating its superiority over placebo. The prospectively defined adaptive randomization rules were based on two goals: finding the ED90 (the lowest dose achieving 90% of the efficacy seen with the maximum effective dose) and determining the probability for the ED90 to be superior to placebo in a phase 3 study. The trial was to stop when the sample size cap of 100 subjects was reached, or when sufficient information was available to show that a TZP-101 dose was sufficiently effective, had a high probability of being the ED90 (probability of at least 0.60 or 0.70) and was likely to be superior to placebo in a phase 3 study, or when continuation of the trial was deemed futile. Bayesian analysis27 of the primary endpoint was the primary statistical analysis for the study. In addition, the primary and all secondary endpoints were analyzed using frequentist inferential analyses27 to test for differences between each TZP-101 http://en.wikipedia.org/wiki/YES1 dose and placebo. The linear mixed-effects model included subject baseline as a covariate and factors for dose, day and dose by day. These analyses were performed using sas version 9.1 or higher (SAS Institute Inc., Cary, NC, USA). A mixed-effects model was applied for the analysis of TZP-101 dose?��?day interaction terms for each of the nine individual GCSI symptom scores, for the three GCSI subscales and overall GCSI score. All efficacy analyses were based on two-sided tests with significance levels of P?