Users’ guide to the surgical literature: how to assess a noninferiority trial

Abstract

DISCUSSIONS IN SURGERY • DISCUSSIONS EN CHIRURGIEUsers' guide to the surgical literature: how to assess a noninferiority trial A well-planned randomized controlled trial (RCT) is the most optimal study design to determine if a novel surgical intervention is any different than a prevailing one. Traditionally, when we want to show that a new surgical intervention is superior to a standard one, we analyze data from an RCT to see if the null hypothesis of "no difference" can be rejected (i.e., the 2 surgical interventions have the same effect).1,2 Let's consider a hypothetical RCT that compares laparoscopic to open appendectomy and the outcome meas ured is a pain score based on a Likert scale from 0 to 10. Suppose it was found that the mean pain score following laparoscopic appendectomy was 7 points and that following open appendectomy was 8 points, and that this 1-point difference was statistically significant. Such a result would be uncommon because it would require a large sample size, but let's accept this for now. Although statistically the result is significant, we do not consider this 1-point difference to have clinical relevance. This type of thinking addresses the concept of minimum clinically important difference (MCID), which describes a threshold that might persuade us to change our surgical practice. The meaningful MCID is usually based on the available best evidence derived from previous systematic reviews, pilot/feasibility studies or clinical judgment based on discussion with experts in the field.In another hypothetical RCT, the length of stay (LOS) after laparoscopic appendectomy was observed to be 24 hours versus 30 hours after open appendectomy, with a p < 0.05. It would be meaningless to conclude that the observed difference of 6 hours is the truth without reporting a confidence interval (CI), as a p value alone does not provide information on the degree of uncertainty (variation) applied in measuring the difference in hospital stay. Briefly, a CI provides information regarding the degree of uncertainty associated with the observed difference of 6 hours in hospital stay. It is within the CI that the true difference will likely lie. Let's say that in our hypothetical example the 95% CI for hospitalization time difference of 6 hours was 1-11 hours in favour of the laparoscopic approach. This means we are 95% confident that the true difference lies somewhere between 1 and 11 hours, A well-planned randomized controlled trial (RCT) is the most optimal study design to determine if a novel surgical intervention is any different than a prevailing one. Traditionally, when we want to show that a new surgical intervention is superior to a standard one, we analyze data from an RCT to see if the null hypothesis of "no difference" can be rejected (i.e., the 2 surgical interventions have the same effect). A noninferiority RCT design seeks to determine whether a new intervention is not worse than a prevailing (standard) one within an acceptable margin of risk or benefit, referred to as the "noninferiority margin...

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