Biostatistics plays a crucial role in human health studies. This mathematical science of data transforms raw data into meaningful information, facilitating informed decision-making and the implementation of evidence-based strategies.
Use of biostatistics in clinical research
Biostatistics are ubiquitous in clinical research. They are used to design study protocols, analyse data, interpret results and evaluate the effectiveness and safety of medical interventions. For clinical trials, observational studies or epidemiological research, biostatistics provide the tools needed to manage uncertainty and draw reliable conclusions.
Applications of biostatistics
Biostatistics has many applications in clinical research:
- Study design: Biostatistics helps to determine the size of the population, to determine randomisation methods and to develop robust study protocols.
- Data analysis: the data collected is analysed according to a statistical analysis plan, which enables the methods and tests used to process the data to be planned.
- Interpretation of results: using biostatistics, researchers can interpret the results of analyses objectively, assessing the significance and clinical relevance of the results observed.
- Risk/benefit assessment: the benefit/risk ratio of a drug, medical device or other health product is derived from statistical evaluations carried out on the data collected.
Concepts to master
A number of fundamental concepts need to be mastered in order to provide the critical feedback required in biostatistics:
- Descriptive statistics: understanding the concepts of mean, median, variance and standard deviation to summarise data.
- Probability and distributions: knowledge of normal, binomial and Poisson distributions, as well as concepts of probability.
- Hypothesis testing: use of t-tests, chi-squares, ANOVA and other statistical tests to compare groups and determine significant differences.
- Regressions and models: application of linear and logistic regressions to analyse relationships between variables.
- Survival analysis: methods for analysing the time until an event occurs, such as Kaplan-Meier curves and Cox models.
Major themes to be developed
The basis of training in biostatistics applied to clinical research is based on major themes such as:
- Introduction to biostatistics: basics and key concepts.
- Design of clinical studies: methodologies and sample size calculation.
- Analysis of clinical data: analysis techniques and interpretation of results.
- Statistical software: use of software such as R, SAS or SPSS for data analysis.
- Ethics and regulation: understanding ethical and regulatory considerations in clinical research.
Biostatistics is a fundamental pillar of clinical research, and mastering it is essential for all those involved in the field. Adequate training not only enables them to understand and apply these concepts, but also to develop a critical eye for studies and their results, thus ensuring that practice is based on solid, reliable evidence.