Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA.
J Thorac Oncol. 2009 Dec;4(12):1447-9. doi: 10.1097/JTO.0b013e3181c0a329.
Biostatistics plays a key role in all phases of clinical research starting from the design to the monitoring, data collection, data analysis, and interpretation of the results. A clear understanding of the statistical framework as it relates to the study hypothesis, reported results, and interpretation is vital for the scientific integrity of the study and its acceptance in the general medical community. In this brief report, we will put in perspective the general analytical framework for exploring and validating prognostic factors using data from large databases.
生物统计学在临床研究的所有阶段都起着关键作用，从设计到监测、数据收集、数据分析和结果解释。清晰理解统计框架与研究假设、报告结果和解释之间的关系，对于研究的科学性及其在普通医学领域的接受至关重要。在本简要报告中，我们将从使用大型数据库的数据探索和验证预后因素的一般分析框架的角度来探讨这个问题。
