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Understanding results: P-values, confidence intervals, and number need to treat
Lawrence Flechner1, Timothy Y Tseng
1Department of Urology, University of California, San Francisco, CA, USA.
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.
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