Comparing the efficacy and tolerability of biologic therapies in psoriasis: an updated network meta-analysis

The rapid expansion of psoriasis biologics has led to an urgent need to understand their relative efficacy and tolerability to inform treatment decisions better and, specifically, to inform guideline development.

To update a 2017 meta-analysis on the comparative efficacy and tolerability of biologic treatments for psoriasis.

We searched the MEDLINE, PubMed, Embase and Cochrane databases for randomized controlled trials (RCTs), published up to 7 September 2018, of 11 licensed, NICE-approved biologics targeting tumour necrosis factor (adalimumab, etanercept, infliximab, certolizumab pegol), interleukin (IL)-12/IL-23p40 (ustekinumab), IL-17A (secukinumab, ixekizumab), IL-17RA (brodalumab) and IL-23p19 (guselkumab, tildrakizumab, risankizumab). A frequentist network meta-analysis ascertained direct or indirect evidence comparing biologics with one another, methotrexate or placebo. This was combined with hierarchical cluster analyses to consider efficacy (≥ 90% improvement in Psoriasis Area and Severity Index (PASI 90) or Physician's Global Assessment 0 or 1; PASI 75; Dermatology Life Quality Index improvement) and tolerability (drug withdrawal due to adverse events) outcomes at 10-16 weeks, followed by assessments of study quality, heterogeneity and inconsistency.

We identified 62 RCTs presenting data on direct comparisons (31 899 participants). All biologics were efficacious compared with placebo or methotrexate at 10-16 weeks. Hierarchical cluster analyses revealed that adalimumab, brodalumab, certolizumab pegol, guselkumab, risankizumab, secukinumab, tildrakizumab and ustekinumab were comparable with respect to high short-term efficacy and tolerability. Infliximab and ixekizumab clustered together, with high short-term efficacy but relatively lower tolerability than the other agents, although the number of drug withdrawal events across the network was low, so these findings should be treated with caution.

Using our methodology we found that most biologics cluster together with respect to short-term efficacy and tolerability, and we did not identify any single agent as 'best'. These data need to be interpreted in the context of longer-term efficacy, effectiveness data, safety, posology and drug acquisition costs when making treatment decisions.