Contemporary clinical trials
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Contemp Clin Trials · Jul 2007
Randomized Controlled TrialA unicenter, randomized, double-blind, parallel-group, placebo-controlled study of Melatonin as an Adjunct in patients with acute myocaRdial Infarction undergoing primary Angioplasty The Melatonin Adjunct in the acute myocaRdial Infarction treated with Angioplasty (MARIA) trial: study design and rationale.
Experimental studies have documented the beneficial effects of the endogenously produced antioxidant, melatonin, in reducing tissue damage and limiting cardiac pathophysiology in models of experimental ischemia-reperfusion. Melatonin confers cardioprotection against ischemia-reperfusion injury most likely through its direct free radical scavenging activities and its indirect actions in stimulating antioxidant enzymes. These actions of melatonin permit it to reduce molecular damage and limit infarct size in experimental models of transient ischemia and subsequent reperfusion. ⋯ The MARIA trial tests a novel pharmacologic agent, melatonin, in patients with acute myocardial infarction and the hypothesis that it will confer cardioprotection against ischemia-reperfusion injury. If successful, the finding would support the use of melatonin in therapy of ischemic-reperfusion injury of the heart.
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Contemp Clin Trials · Jul 2007
Sample size calculation for multicenter randomized trial: taking the center effect into account.
In multicenter trials, data from the same center are more similar than those from different centers. These similarities induce a correlation between data, known as the center effect, which is assessed by the intraclass correlation coefficient (ICC). ⋯ Our analytical developments lead to an elementary formula different from the classical one by a (1-rho) factor, where rho is the ICC. This work allows for adjusting and reducing the sample size according to the magnitude of the center effect and leads to a better consistency in the conduct of multicenter randomized trials.
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Contemp Clin Trials · Jul 2007
Methods of joint evaluation of efficacy and toxicity in phase II clinical trials.
Phase II clinical trials in oncology are usually conducted to evaluate the anti-tumor effect. Because phase I trials are small studies, the maximum tolerated dose of a new drug may not be precisely established and the recommended dose used may lead to excessive toxicity. We investigate the methods proposed by Conaway-Petroni and Bryant-Day allowing early termination of phase II clinical trials and based on joint evaluation of treatment efficacy and safety. ⋯ Choosing Phi has a minimal impact on expected accrual. Finally, one type I error risk (alpha00) defined by Conaway-Petroni dramatically increases in the case of deviation from the assumption made on Phi. Due to its robustness in relation to a deviation from the independence assumption, we recommend the use of the Bryant-Day method in clinical practice.
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Contemp Clin Trials · Jul 2007
Alternative designs of phase II trials considering response and toxicity.
Phase II clinical trials in oncology are used to initially evaluate the therapeutic efficacy of a new treatment regimen. Simon's two-stage design is commonly used for such trials. However, he only focused on the "response rate", the proportion of patients experiencing tumor regression. ⋯ We provide guides on searching the stopping and rejecting regions and determination of sample size. The proposed method has advantage over other designs, including those of Conaway and Petroni's and Bryant and Day's, that it can definitely control one type I error of the interests such as treatment antitumor activity or safety and is robust against the real association parameter. Furthermore, it is conceptive intuitive, very simple to implement, and also feasible for the requirement of small sample size in a phase II trial.
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Contemp Clin Trials · May 2007
The effect of omitted covariates on confidence interval and study power in binary outcome analysis: a simulation study.
The consequence of omitted but balanced covariates on odds ratio point estimation is well-known in the literature. When exposure or intervention has a non-null effect on disease outcome, omitted covariates lead to underestimation of the effect of exposure or intervention. However, the effect of omitted covariates on confidence interval and study power is unknown. ⋯ Omitting an important balanced covariate lowers both coverage probability and study power. This implies the need for thoughtful consideration of important covariates at the design as well as the analysis stages of a study.