Improving interpretation of clinical studies by use of confidence levels, clinical significance curves, and risk-benefit contours

The process of interpreting the results of clinical studies and translating them into clinical practice is being debated, Here we examine the role of p values and confidence intervals in clinical decision-making, and draw att ention to confusion in their interpretation. To improve result reporting, w e propose the use of confidence levels and plotting of clinical significanc e curves and risk-benefit contours. These curves and contours provide degre es of probability of both the potential benefit of treatment and the detrim ent due to toxicity, Additionally, they provide clinicians with a mechanism of translating the results of studies into treatment for individual patien ts, thus improving the clinical decision-making process. We illustrate the application of these curves and contours by reference to published studies. Confidence levels, clinical significance curves, and risk-benefit contours can be easily calculated with a hand calculator or standard statistical pa ckages. We advocate their incorporation into the published results of clini cal studies.