Freda Cooner, R. Liao, Junjing Lin, Sophie Barthel, Y. Seifu, Shiling Ruan
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引用次数: 0
Abstract
Abstract Starting in early 2020, a fast-ravaging viral infection erupted and caused the COVID-19 (coronavirus disease of 2019) pandemic. The disease rapidly spread across the world and has altered people’s lifestyle since its first reporting. Many scientists and medical practitioners have strived to understand the disease and research for treatments and vaccines. As real-world data quickly accumulate, the general public reacts to new findings and government bodies enforce preventive measures accordingly. These actions subsequently alter the real-world data pattern and structure. It creates great challenges in interpreting this maze of data. This article delves into the specificity of COVID-19 real-world data; summarizes some existing COVID-19 databases and the disease modeling strategies; outlines potential trial designs incorporating real-world data to meet evidentiary requirements for treatment effect demonstration; and then presents a few case examples. It provides statistical considerations for real-world data utilization in understanding COVID-19 and finding potential treatments and preventive care.
期刊介绍:
Statistics in Biopharmaceutical Research ( SBR), publishes articles that focus on the needs of researchers and applied statisticians in biopharmaceutical industries; academic biostatisticians from schools of medicine, veterinary medicine, public health, and pharmacy; statisticians and quantitative analysts working in regulatory agencies (e.g., U.S. Food and Drug Administration and its counterpart in other countries); statisticians with an interest in adopting methodology presented in this journal to their own fields; and nonstatisticians with an interest in applying statistical methods to biopharmaceutical problems.
Statistics in Biopharmaceutical Research accepts papers that discuss appropriate statistical methodology and information regarding the use of statistics in all phases of research, development, and practice in the pharmaceutical, biopharmaceutical, device, and diagnostics industries. Articles should focus on the development of novel statistical methods, novel applications of current methods, or the innovative application of statistical principles that can be used by statistical practitioners in these disciplines. Areas of application may include statistical methods for drug discovery, including papers that address issues of multiplicity, sequential trials, adaptive designs, etc.; preclinical and clinical studies; genomics and proteomics; bioassay; biomarkers and surrogate markers; models and analyses of drug history, including pharmacoeconomics, product life cycle, detection of adverse events in clinical studies, and postmarketing risk assessment; regulatory guidelines, including issues of standardization of terminology (e.g., CDISC), tolerance and specification limits related to pharmaceutical practice, and novel methods of drug approval; and detection of adverse events in clinical and toxicological studies. Tutorial articles also are welcome. Articles should include demonstrable evidence of the usefulness of this methodology (presumably by means of an application).
The Editorial Board of SBR intends to ensure that the journal continually provides important, useful, and timely information. To accomplish this, the board strives to attract outstanding articles by seeing that each submission receives a careful, thorough, and prompt review.
Authors can choose to publish gold open access in this journal.