BACKGROUND: The effectiveness and cost-effectiveness of biologic therapies for psoriasis are significantly compromised by variable treatment responses. Thus, more precise management of psoriasis is needed.
OBJECTIVES: We aim to identify subgroups of psoriasis patients treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management.
METHODS: Here we apply latent class mixed modelling, to identify trajectory-based patient subgroups from longitudinal, routine clinical data on disease severity, as measured by the Psoriasis Area and Severity Index (PASI), from 3546 patients in the British Association of Dermatologists Biologics and Immunomodulators Register, as well as in an independent cohort of 2889 subjects pooled across four clinical trials.
RESULTS: We discovered four, discrete classes of global response trajectories, each characterised in terms of time to response, size of effect and relapse. Each class was associated with differing clinical characteristics, e.g. Body Mass Index, baseline PASI, and prevalence of different manifestations. Our results were verified in a second cohort of clinical trials subjects, where similar trajectories following initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA-C*06:02 between our registry-identified trajectories.
CONCLUSION: These subgroups, defined by change in disease over time, may be indicative of distinct endotypes driven by different biological mechanisms and may help inform the management of patients with psoriasis. Future work will aim to further delineate these mechanisms by extensively characterising the subgroups with additional molecular and pharmacological data.
Original languageEnglish
JournalBritish Journal of Dermatology
Publication statusAccepted/In press - 31 Mar 2021


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