Network meta-analysis of biologic treatments for psoriasis using absolute Psoriasis Area and Severity Index values...

In practice, the goal of treatment for patients with psoriasis is to achieve almost clear or clear skin and maintain disease control, regardless of baseline disease severity. However, identifying absolute Psoriasis Area and Severity Index (PASI) values for new treatment goals is challenging, as most clinical trials report relative PASI 50, 75, 90 or 100 improvements but rarely absolute PASI values achieved.

Our objective was to illustrate a statistical conversion method that was developed to derive absolute PASI values from available clinical trial data on relative PASI improvements. The results of network meta-analyses (NMAs) based on these derived data were then compared with those of NMAs based on the corresponding relative PASI improvement data for selected biologics for moderate-to-severe psoriasis.

The PASI statistical conversion method was applied to relative PASI improvement data for 11 biologic treatment regimens and placebo at 12 weeks using data from 50 published studies. The respective proportions of patients reaching absolute PASI values ≤1, 2, 3 or 5 were then calculated. Frequentist NMAs (Rücker method) were subsequently used to compare efficacy results across relative and absolute PASI data.

The ranking of included treatment regimens for patients achieving absolute PASI 0 to 8 was aligned with results for relative PASI scores (from 100 to 60) at end of induction therapy. Across the range of PASI scores considered, the most effective treatment regimens based on both absolute and relative PASI NMAs were brodalumab 210 mg every 2 weeks and ixekizumab 80 mg every 2 weeks, followed by guselkumab 100 mg every 8 weeks and risankizumab 150 mg every 12 weeks.

Data generated using this mathematical model will be useful to inform ongoing scientific discussions on treatment goals in the absence of primary absolute PASI data for all available treatments for moderate-to-severe plaque psoriasis.