Defining trajectories of response in patients with psoriasis treated with biologic therapies.


Journal

The British journal of dermatology
ISSN: 1365-2133
Titre abrégé: Br J Dermatol
Pays: England
ID NLM: 0004041

Informations de publication

Date de publication:
10 2021
Historique:
accepted: 03 04 2021
pubmed: 9 4 2021
medline: 26 10 2021
entrez: 8 4 2021
Statut: ppublish

Résumé

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. To identify subgroups of patients with psoriasis treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management. We applied 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 patients pooled across four clinical trials. We discovered four discrete classes of global response trajectories, each characterized 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. The results were verified in a second cohort of clinical trial participants, where similar trajectories following the initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA-C*06:02 between our registry-identified trajectories. 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 characterizing the subgroups with additional molecular and pharmacological data.

Sections du résumé

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
To identify subgroups of patients with psoriasis treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management.
METHODS
We applied 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 patients pooled across four clinical trials.
RESULTS
We discovered four discrete classes of global response trajectories, each characterized 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. The results were verified in a second cohort of clinical trial participants, where similar trajectories following the initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA-C*06:02 between our registry-identified trajectories.
CONCLUSIONS
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 characterizing the subgroups with additional molecular and pharmacological data.

Identifiants

pubmed: 33829489
doi: 10.1111/bjd.20140
doi:

Substances chimiques

Biological Factors 0
Biological Products 0
Immunologic Factors 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

825-835

Subventions

Organisme : Medical Research Council
ID : MR/S003126/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/K006665/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/N00583X/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/L011808/1
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2021 The Authors. British Journal of Dermatology published by John Wiley & Sons Ltd on behalf of British Association of Dermatologists.

Références

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Auteurs

N Geifman (N)

The Manchester Molecular Pathology Innovation Centre, University of Manchester, Manchester, UK.
Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

N Azadbakht (N)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

J Zeng (J)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

T Wilkinson (T)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

N Dand (N)

School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Health Data Research UK, London, UK.

I Buchan (I)

Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK.

D Stocken (D)

Clinical Trials Research Unit, University of Leeds, UK.

P Di Meglio (P)

St. John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust, London, UK.

R B Warren (RB)

Dermatology Centre, Salford Royal NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester, UK.

J N Barker (JN)

St. John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust, London, UK.

N J Reynolds (NJ)

Institute of Translational and Clinical Medicine, Medical School, Newcastle University, Newcastle upon Tyne, UK.
Department of Dermatology, Royal Victoria Infirmary, and NIHR Newcastle Biomedical Research Centre, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.

M R Barnes (MR)

Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

C H Smith (CH)

St. John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust, London, UK.

C E M Griffiths (CEM)

Dermatology Centre, Salford Royal NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester, UK.

N Peek (N)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester, UK.

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