Research and Evaluation Support Core Unit (RESCU Core)

方法论核心 摘要 CCCR的方法论核心将汇集来自不同科学背景的研究人员， 研究兴趣是在特定的疾病的重点为这个CCCR，骨关节炎和痛风，沿着利益 脊椎关节炎、硬皮病、骨质疏松症和肌肉骨骼疼痛。通过风湿病学，康复 流行病学和生物统计学研究人员每周聚会一次， 跨学科的对话，并提供给临床研究人员的方法学专业知识， 否则就不属于他们的赠款或科学项目。与先前的MCRC一样， 方法学：骨关节炎和痛风的流行病学研究的核心。在 此外，在过去的五年里，我们已经开发了解决流行病学问题的专业知识， 电子健康记录数据库，特别是健康改善网络（THIN）。波士顿大学 CCCR集团以培训年轻的调查人员而闻名，其中许多人现在占了调查人员的很大一部分。 国内外风湿病临床研究者。核心方法将继续 重点培养博士、博士后和流变学研究员。 该方法核心的总体目标是为临床研究提供最先进的方法学输入 我们研究的OA，痛风和其他疾病的问题，并介绍新的有效的临床研究方法 进入这些疾病的研究。除了为研究方案、设计和统计提供支持外， 分析，现代流行病学的方法，包括因果推理和孟德尔随机化。 此外，因为它们代表了CCCR疾病临床研究未来的主要组成部分，我们将 包括机器学习和移动的医疗技术方面的新专业知识。

METHODOLOGY CORE ABSTRACT The Methodology Core of the CCCR will bring together investigators from diverse scientific backgrounds whose research interests are in the specific diseases of focus for this CCCR, osteoarthritis and gout, along with interests in spondyloarthritis, scleroderma, osteoporosis and musculoskeletal pain. By having rheumatology, rehabilitation and epidemiology and biostatistics investigators meet once a week together, the Methodology Core creates interdisciplinary conversations and makes available to clinician researchers methodologic expertise that would otherwise not be part of their grants or scientific projects. As in the prior MCRC, there is a focus in the Methodology Core on epidemiologic studies of established and new cohorts in osteoarthritis and gout. In addition, in the past five years we have developed expertise in addressing epidemiologic questions using large electronic health record databases, especially the Health Improvement Network (THIN). The Boston University CCCR group is well known for training young investigators, many of whom now make up a large segment of the clinical researchers in rheumatology domestically and around the world. The Methodology Core will continue to emphasize training doctoral and postdoctoral students and rheumatology fellows. The overall goals of this methodology core are to provide state of the art methodologic input into clinical research questions in OA, gout and other diseases we study and also to introduce new impactful clinical research methods into the study of these diseases. In addition to providing support for study protocols, design and statistical analysis, modern epidemiologic methods involving causal inference and Mendelian randomization will be used. Further, because they represent major components of the future of clinical research in CCCR diseases, we will include new expertise in machine learning and mobile health technologies.