Journal of biopharmaceutical statistics
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Comparative Study
Good statistical practice in utilizing real-world data in a comparative study for premarket evaluation of medical devices.
Observational (non-randomized) comparative studies have been adopted in the pre-market safety/effectiveness evaluation of medical devices. There has been an increased interest in utilizing this design with the growing available real-world data. ⋯ In this paper, challenges and opportunities are discussed from the regulatory perspective. Considerations and good statistical practice to mitigate the potential bias are presented.
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Phase I designs traditionally use the dose-limiting toxicity (DLT), a binary endpoint from the first treatment cycle, to identify the maximum-tolerated dose (MTD) assuming a monotonically increasing relationship between dose and efficacy. In this article, we establish a general framework for a multi-stage adaptive design where we jointly model a continuous efficacy outcome and continuous/quasi-continuous toxicity endpoints from multiple treatment cycles. The normalized Total Toxicity Profile (nTTP) is used as an illustration for quasi-continuous toxicity endpoints, and we replace DLT with nTTP to take into account multiple grades and types of toxicities. ⋯ Simulations showed that the design had a high probability of making the correct dose selection and good overdose control across various dose-efficacy and dose-toxicity scenarios. In addition, the proposed design allows for early termination when all doses are too toxic. To our best knowledge, the proposed dual-endpoint dose-finding design is the first such study to incorporate multiple cycles of toxicities and a continuous efficacy outcome.
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In this article, we propose and evaluate three alternative randomization strategies to the adaptive randomization (AR) stage used in a seamless Phase I/II dose-finding design. The original design was proposed by Wages and Tait in 2015 for trials of molecularly targeted agents in cancer treatments, where dose-efficacy assumptions are not always monotonically increasing. Our goal is to improve the design's overall performance regarding the estimation of optimal dose as well as patient allocation to effective treatments. ⋯ Unlike the original method, our proposed adaption does not require an arbitrarily specified sample size for the adaptive randomization stage. Simulations are used to compare the proposed strategies and a final strategy is recommended. Under most scenarios, our recommended method allocates more patients to the optimal dose while improving accuracy in selecting the final optimal dose without increasing the overall risk of toxicity.
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The Biological Price Competition and Innovation Act (BPCI Act) of 2009 established a pathway for the approval of biosimilars and interchangeable biosimilars in the United States. The Food Drug Administration (FDA) has issued several guidances on the development and assessment of biosimilars which implement the BPCI Act. In particular, a recent draft guidance on the interchangeability of biological products presents an overview of scientific considerations on the demonstration of interchangeability with a reference product. The present communication provides a general summary of the draft guidance and briefly observes a few current issues on interchangeability.