Understanding results: P-values, confidence intervals, and number need to treat

OBJECTIVES: With the increasing emphasis on evidence-based medicine, the urology literature has seen a rapid growth in the number of high-quality randomized controlled trials along with increased statistical rigor in the reporting of study results. P-values, CI, and number needed to treat (NNT) are becoming increasingly common in the literature. This paper seeks to familiarize the reader with statistical measures commonly used in the evidence-based literature. MATERIALS AND METHODS: The meaning and appropriate interpretation of these statistical measures is reviewed through the use of a clinical scenario. RESULTS: The reader will be better able to understand such statistical measures and apply them to the critical appraisal of the literature. CONCLUSIONS: P-values, CI, and NNT each provide a slightly different estimate of statistical truth. Together, they provide a more complete picture of the true effect observed in a study. An understanding of these measures is essential to the critical appraisal of study results in evidence-based medicine.