Statistical principles for prospective study protocols:: design, analysis, and reporting

In the design of scientific studies it is essential to decide on which scientific questions one aims to answer, just as it is important to decide on the correct statistical methods to use to answer these questions. The correct use of statistical methods is crucial in all aspects of research to quantify relationships in data. Despite an increased focus on statistical content and complexity of biomedical research these topics remain difficult for most researchers. Statistical methods enable researchers to condense large spreadsheets with data into means, proportions, and difference between means, risk differences, and other quantities that convey information. One of the goals in biomedical research is to develop parsimonious models - meaning as simple as possible. This approach is valid if the subsequent research report (the article) is written independent of whether the results are "statistically significant" or not. In the present paper we outline the considerations and suggestions on how to build a trial protocol, with an emphasis on having a rigorous protocol stage, always leading to a full article manuscript, independent of statistical findings. We conclude that authors, who find (rigorous) protocol writing too troublesome, will realize that they have already written the first half of the final paper if they follow these recommendations; authors simply need to change the protocols future tense into past tense. Thus, the aim of this clinical commentary is to describe and explain the statistical principles for trial protocols in terms of design, analysis, and reporting of findings.