Abstract
As health professionals, pharmacists are inundated with new information from the thousands of articles published every year, creating an ever-expanding knowledge bank. Before we can effectively communicate research evidence to our patients, we must first be familiar with the ways that study results are presented. The number needed to treat (NNT) is a simple representation that compares the efficacy of different therapeutic interventions.
The effects of new drugs described in randomised controlled trials (RCTs) and systematic reviews are usually based on dichotomous outcomes such as survival vs death, or cure vs no cure. The probabilities generated from these studies can be used to calculate a number of statistical values (i.e. NNT, relative risks, odds ratios, hazard ratios and absolute risk reductions) that can assist pharmacists to make informed decisions when evaluating treatment benefits or harms. But how exactly do we interpret the NNT? And what do we mean by risks and odds?
The effects of new drugs described in randomised controlled trials (RCTs) and systematic reviews are usually based on dichotomous outcomes such as survival vs death, or cure vs no cure. The probabilities generated from these studies can be used to calculate a number of statistical values (i.e. NNT, relative risks, odds ratios, hazard ratios and absolute risk reductions) that can assist pharmacists to make informed decisions when evaluating treatment benefits or harms. But how exactly do we interpret the NNT? And what do we mean by risks and odds?
| Original language | English |
|---|---|
| Pages (from-to) | 24-32 |
| Number of pages | 8 |
| Journal | Australian Pharmacist |
| Volume | 41 |
| Issue number | 3 |
| Publication status | Published - 1 May 2022 |