Net efficacy adjusted for risk: further developments

Abstract

Background: ‘Net efficacy adjusted for risk’ (NEAR) is a simple quantitative indicator integrating risk and benefit in one measure. NEAR considers that, in a clinical trial (CT), the drug with the best risk:benefit profile corresponds to that causing the greatest number of patients to respond favourably without suffering adverse drug reactions. This number is only exceptionally reported; thus, a NEAR estimate is obtained by calculating expected frequencies. NEAR is designed to compare two drugs and may be expressed as odds ratio or relative risk with their 95% CIs. Objective: To analyse the influence of using either intention-to-treat (ITT) or per-protocol (PP) populations in NEAR results. The use of NEAR as ‘effect size’ in performing meta-analyses is posed. Method: By analyzing several examples, differences between NEAR calculated by considering either ITT or PP populations are presented. Likewise, an example of meta-analysis by using NEAR as effect size is shown. Conclusions: NEAR results may be optimised by considering the type of population analysed, ITT or PP. Meta-analyses using NEAR as effect size provide new insights into CT results. Last, correcting certain deficits in adverse drug reactions reporting is required in CT risk assessment.

Keywords::

• benefit:risk analysis
• clinical trials
• intention-to-treat analysis
• meta-analysis
• NEAR
• per-protocol analysis

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