Six-Month Real-World Study to Assess the Effectiveness of Ixekizumab After Switching from IL-23 Inhibitors and Other Biologic Therapies: The CorEvitas Psoriasis Registry.
Mark Lebwohl, Bruce Strober, Amy Schrader, Alvin H Li, Thomas Eckmann, Baojin Zhu, William N Malatestinic, Julie Birt, Meghan Feely, Andrew Blauvelt
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引用次数: 0
Abstract
Background: Prior work showed that patients from the CorEvitas Psoriasis Registry who had previously failed a prior biologic and then initiated ixekizumab demonstrated improvements in disease severity and patient-reported outcomes after 6 months. However, newer therapies such as interleukin-23 inhibitors (IL-23i) were not considered. Here, with more recent data including IL-23i, 6-month effectiveness of ixekizumab following a switch from any biologic was assessed as well as whether 6-month effectiveness of ixekizumab was impacted by prior biologic class.
Methods: We included CorEvitas Psoriasis Registry patients who initiated ixekizumab after discontinuing another biologic therapy and had a corresponding 6-month follow-up visit following ixekizumab initiation (N = 743, 2016-2023). Immediate prior biologic class was categorized as tumor necrosis factor inhibitor (TNFi) or interleukin-12/23 inhibitors (IL-12/23i, n = 405), non-ixekizumab interleukin-17i (IL-17i, n = 237), or IL-23i (n = 101). Adjusted mean changes in body surface area (BSA), Dermatology Life Quality Index (DLQI), itch, and skin pain were calculated for prior biologic class groups using analysis of covariance (ANCOVA). Proportions achieving ≥ 75%, ≥ 90%, and ≥ 100% improvement in Psoriasis Area and Severity Index (PASI75, PASI90, and PASI100, respectively), Investigator's Global Assessment (IGA) 0/1, and DLQI 0/1 were calculated for all patients and compared among prior biologic classes via relative risks (RRs) and 95% confidence intervals (CIs) using multivariable modified Poisson regression.
Results: Mean improvements in BSA, DLQI, itch, and skin pain, were 7.6, 3.6, 23.3, and 16.7, respectively, for ixekizumab patients who switched from TNFi or IL-12/23i (all p < 0.05); 6.8, 3.3, 19.6, and 14.1, respectively, for those who switched from non-ixekizumab IL-17i (all p < 0.05); and 7.8, 3.4, 22.2, and 12.8, respectively, for those who switched from IL-23i (all p < 0.05). Overall, 54%, 41%, and 31% of ixekizumab initiators achieved PASI75, PASI90, and PASI100, respectively, 50% maintained or achieved IGA 0/1, and 48% maintained or achieved DLQI 0/1. The prior TNFi or IL-12/23i group was 31% more likely to achieve PASI100 (RR = 1.31, 95% CI 1.01, 1.69) and 32% more likely to maintain or achieve IGA 0/1 (RR = 1.32, 95% CI 1.11, 1.57), but not significantly more likely to achieve PASI90. The prior IL-23i group was 45% more likely to achieve PASI90 (RR = 1.45, 95% CI 1.10, 1.91), 55% more likely to achieve PASI100 (RR = 1.55, 95% CI 1.12, 2.13), and 39% more likely to maintain or achieve IGA 0/1 (RR = 1.39, 95% CI 1.12, 1.73) compared to the prior non-ixekizumab IL-17i group. Achievement of PASI75 and DLQI 0/1 was consistent across the prior TNFi or IL-12/23i, IL-23i, and non-ixekizumab IL-17i groups.
Conclusions: These updated findings with IL-23i data reaffirm that patients with psoriasis who switch to ixekizumab after discontinuing another biologic demonstrate improvement in disease severity and patient-reported outcomes at 6 months in real-world settings. Compared to patients who switched from another IL-17i, patients who switched class from a TNFi or IL-12/23i were more likely to achieve PASI100 and IGA 0/1, and patients who switched class from an IL-23i were more likely to achieve PASI90 in addition to PASI100 and IGA 0/1.
期刊介绍:
Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.