Introduction to collection of papers about Fundamentals of Research Methodology in Medicine

This paper opens a series of publications about fundamentals of research methodology in medicine. Fast development of evidence-based medicine includes placing the practice of medicine on a solid scientific basis, the development of more sophisticated hierarchies of evidence, analysis of high-dimensional and longitudinal data, and the development of the algorithms for generating reliable recommendations for clinical decision making. Explosion-like growth of available digital data accompanying each patient increased the role of biomedicine statistics, but the fundamentals of research methodology in medicine include many other topics.

In the present series of papers, we will try to review basics of these approaches as a guideline for every PhD student or practicing clinician who plans to include research related topics in the everyday practice. These topics extend from standard approaches to scientometric information and general principles of functioning of international medical journals to basic principles of evidence-based medicine and the possibility of applying clinical epidemiology and the results of clinical trials in practice.

Covering different topics from fundamentals of trial design and sample size estimations to such sophisticated methodology as principal component analysis, we plan to publish self-consistent collection of instructions to simplify the life of a medical worker.

Our aim is to present a structured collection of methodology descriptions correlated with the courses taught in the Sechenov University. To be more detailed, we plan to cover such topics as basics of statistics and the Venn diagrams, fundamentals of trial design, sample size and power calculation, preprocessing of data, basics in descriptive and inferential statistics, usage of testing, classification, predictive modelling and many others. The topics we cover will not be limited to the technical recommendations on how to execute a research in clinical practice, as we will draw a significant amount of attention to how to prepare a correct statistical analysis plan or perform a meta-analysis.

Team of authors