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Number Needed to Treat in Multiple Sclerosis Clinical Trials.

ABSTRACT: Clinicians are expected to select a therapy based on their appraisal of evidence on benefit-to-risk profiles of therapies. In the management of relapsing-remitting multiple sclerosis (RRMS), evidence is typically expressed in terms of risk (proportion) of event, risk reduction, relative and hazard rate reduction, or relative reduction in the mean number of magnetic resonance imaging lesions. Interpreting treatment effect using these measures from a RRMS clinical trial is fairly reliable; however, this might not be the case when treatment effect is expressed in terms of the number needed to treat (NNT). The objective of this review is to discuss the utility of NNT in RRMS trials. This article presents an overview of the methodological definition and characteristics of NNT as well as the relative merit of NNT use in RRMS controlled clinical trials, where endpoints are typically time-to-event and frequency of recurrent events. The authors caution against using NNT in multiple sclerosis, a clinically heterogeneous disease that can change course and severity unpredictably. The authors also caution against the use of NNT to interpret results in comparative trials where the absolute risk difference is not statistically significant, computing NNT using the time-to-event endpoint at intermediate time points, computing NNT using the annualized relapse rate, and comparing NNT across trials.

SUBMITTER: Okwuokenye M

PROVIDER: S-EPMC5447556 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective:Schizophrenia clinical trials commonly measure observed changes in Positive and Negative Syndrome Scale (PANSS) total score. However, it is more intuitive to think of response vs nonresponse, a binary outcome. Assessing binary outcomes enables calculation of number needed to treat (NNT) for therapeutic outcomes, number needed to harm (NNH) for adverse outcomes, and likelihood to be helped or harmed (LHH) to demonstrate benefit/risk tradeoffs. Here, NNT, NNH, and LHH were used to evaluate the clinical usefulness of aripiprazole lauroxil in patients with an acute schizophrenia exacerbation. Methods:Categorical efficacy and tolerability data were taken from the pivotal Phase 3 trial evaluating aripiprazole lauroxil for treatment of an acute exacerbation of schizophrenia. NNT and NNH values, with 95% CIs, were calculated in this post hoc analysis. Results:Using the intent-to-treat population for the pooled doses of aripiprazole lauroxil (441 mg [n=196] and 882 mg [n=204] q4w), responder rates (?30% improvement from baseline PANSS total score) were 35.3% for aripiprazole lauroxil arms vs 18.4% for placebo (n=196), yielding a NNT of 6 (95% CI: 5-11). Discontinuation rates due to adverse events (AEs) were higher among patients randomized to placebo than to either aripiprazole lauroxil dose. Akathisia was the only AE with an incidence ?5% in each aripiprazole lauroxil group and at least twice that of placebo (11.6%, 11.5%, and 4.3% of the patients receiving aripiprazole lauroxil 441 mg, 882 mg, and placebo, respectively), producing a NNH of 14 (95% CI: 9-33) for pooled aripiprazole lauroxil doses vs placebo. Calculating LHH for therapeutic response vs akathisia, aripiprazole lauroxil was 2.3 times more likely to result in a therapeutic response than an incident of akathisia. Conclusion:Using metrics of NNT, NNH, and LHH, aripiprazole lauroxil was an efficacious and well-tolerated intervention in a pivotal study in patients with an acute schizophrenia exacerbation.

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Number Needed to Treat in Multiple Sclerosis Clinical Trials.

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