Journal of biopharmaceutical statistics
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The traditional and accelerated titration (AT) designs are two frequently utilized Phase I clinical trial designs. Although each design has theoretical advantages and disadvantages, a summary of the practical application of these theories has not been reported. We report our center's experience in evaluating novel agents using both types of Phase I trial designs over a 13-year period. ⋯ The mean number of dose levels in patients treated using the traditional Phase I trial design was 8.8 (range 7-11) compared to a mean of 10.6 (range 7-15) dose levels using the AT design. The mean length of study time (25-26 months) was similar in both trial designs. The theoretical advantages and disadvantages of both Phase I trial designs did not readily emerge in their actual application in clinical trials conducted at our institution.
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Comparative Study
MMRM vs. LOCF: a comprehensive comparison based on simulation study and 25 NDA datasets.
In recent years, the use of the last observation carried forward (LOCF) approach in imputing missing data in clinical trials has been greatly criticized, and several likelihood-based modeling approaches are proposed to analyze such incomplete data. One of the proposed likelihood-based methods is the Mixed-Effect Model Repeated Measure (MMRM) model. ⋯ In a sensitivity analysis of 48 clinical trial datasets obtained from 25 New Drug Applications (NDA) submissions of neurological and psychiatric drug products, MMRM analysis appears to be a superior approach in controlling Type I error rates and minimizing biases, as compared to LOCF ANCOVA analysis. In the exploratory analyses of the datasets, no clear evidence of the presence of MNAR missingness is found.
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In this article we provide additional support for the use of a model-based design in pediatric Phase I trials and present our modifications to the continual reassessment method (CRM), which were largely motivated by specific challenges we encountered in the context of the Pediatric Brain Tumor Consortium trials. We also summarize the results of our extensive simulations studying the operating characteristics of our modified approach and contrasting it to the empirically based traditional method (TM). Compared to the TM, our simulations indicate that the modified version of CRM is more accurate, exposes fewer patients to potentially toxic doses, and tends to require fewer patients. Further, the CRM-based MTD has a consistent definition across trials, which is important, especially in a consortium setting where multiple agents are being tested in studies that are often running simultaneously and accruing from the same patient population.
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A new two-stage design is proposed that is suitable for early detection of the anticancer activity of experimental therapies in Phase II oncology trials. The endpoints of interest are response rate and early progression rate. The anticancer activity is defined by a positive signal in one endpoint and a non-negative signal in the other endpoint. ⋯ The design is optimal in that it minimizes the patient exposure when the experimental therapies are inactive. The design parameters are found by a grid searching algorithm under type I and type II error rate constraints. Examples of the design are also presented in this paper.
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Combination therapy of two antitumor agents may provide treatment additivity or synergy. Phase I trials for combination therapy search for the maximum tolerated dose (MTD) for combined agents. The conventional approach is to preselect an escalation path, usually increasing the dose of one agent and then another, and to use the standard 3 + 3 design. ⋯ A two-dimensional isotonic estimation method for toxicity rate is provided. We use simulation methods to compare 2 + 1 + 3 vs. 3 + 3 cohort sizes. We conclude that the comprehensive search proposed in our study can be more practical and efficient in identifying the MTD in combination-therapy of two agents.