Statistical Principles for Clinical Trials

TLDR

A thorough grasp of basic statistical principles is essential for well‑designed trials and valid conclusions. The study examines the intent‑to‑treat principle in comparative trials. The authors describe key methodological elements: sample‑size calculation, randomization to balance groups, proper p‑value calculation, and confidence‑interval interpretation. Inaccurate initial calculations render trial results unreliable.

Abstract

If a trial is to be well designed, and the conclusions drawn from it valid, a thorough understanding of the benefits and pitfalls of basic statistical principles is required. When setting up a trial, appropriate sample-size calculation is vital. If initial calculations are inaccurate, trial results will be unreliable. The principle of intent-to-treat in comparative trials is examined. Randomization as a method of selecting patients to treatment is essential to ensure that the treatment groups are equalized in terms of avoiding biased allocation in the mix of patients within groups. Once trial results are available the correct calculation and interpretation of the P-value is important. Its limitations are examined, and the use of the confidence interval to help draw valid conclusions regarding the clinical value of treatments is explored.