Comparative Effectiveness of Ixekizumab Versus Ustekinumab in Patients With Psoriasis: A Randomized Controlled Trial Replication Using Data From an Observational Study (Shanghai Psoriasis Effectiveness Evaluation Cohort)

Abstract

Objectives

Randomized controlled trials provide high internal validity but often have limited generalizability. Benchmarking real-world data against randomized controlled trial findings helps evaluate external validity. The objectives were to assess whether the results of the IXORA-S trial comparing ixekizumab and ustekinumab could be replicated using real-world data from the Shanghai Psoriasis Effectiveness Evaluation Cohort (SPEECH) and to explore potential reasons for differences between trial and observational findings.

Methods

We conducted a prospective cohort study of adults with moderate-to-severe plaque psoriasis enrolled in SPEECH (2021-2023) and treated with ixekizumab or ustekinumab. Propensity-score methods and multiple imputation were applied to address confounding and missing data. Outcomes were benchmarked against IXORA-S using agreement metrics and sensitivity analyses, including population trimming. The primary endpoint was the proportion of patients achieving a ≥90% reduction in the Psoriasis Area and Severity Index (PASI 90) at week 12.

Results

Among 367 patients (ixekizumab n = 203; ustekinumab n = 164), ixekizumab achieved higher PASI 90 response rates at week 12 compared with ustekinumab. Effect estimates were consistent with IXORA-S in direction, magnitude, and statistical significance. Differences in baseline eligibility criteria and disease severity explained part of the efficacy-effectiveness gap.

Conclusions

The results of IXORA-S were successfully replicated using real-world data from SPEECH. This demonstrates that registry-based observational data can yield reliable estimates of treatment effects and may be used to investigate effectiveness questions not feasible to study in randomized trials, such as long-term outcomes and effects in underrepresented populations.

Authors

Ning Yu Lian Cui Yuye Wang Yu Wang Xinyi Song Qin Yang Yuling Shi

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