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Identifying Subgroups of Response to Biologics in Psoriasis using Large-scale Patient-level Data
Proposal
1693
Title of Proposed Research
Identifying Subgroups of Response to Biologics in Psoriasis using Large-scale Patient-level Data
Lead Researcher
Nophar Geifman
Affiliation
University of Manchester
Funding Source
None
Potential Conflicts of Interest
None
Data Sharing Agreement Date
19 February 2018
Lay Summary
Biologic therapies, a class of drugs modifying specific parts of the immune system's functioning, have led to remarkable improvements in outcomes for many patients suffering from Immune Mediated Inflammatory Diseases (IMID) such as psoriasis. However, these drugs are expensive, may result in serious adverse events and the response to treatment is variable. A precision medicine approach to psoriasis therefore needs to identify phenotypically distinctive subgroups of patients who may be more or less likely to respond to biologic therapies. We aim to target these therapies by using large-scale patient-level data to identify subgroups of patients for whom treatment with biologics will be most beneficial.
Using sophisticated computational methods, we aim to identify and characterise subgroups of patients demonstrating different patterns of response to treatment. To achieve this, we will apply our analytical methods to large-scale integrated patient-level data which will effectively provide sufficiently large enough cohorts to allow identification of clinically meaningful subgroups. These cohorts can be generated by employing a pooled meta-analysis approach where patients treated with the same medication or with similar disease characteristics are pooled together from a number of clinical trials and analyzed for patterns of response to treatment. By focusing on the distinguishing characteristics of these subgroups at baseline, the prediction of response to treatment might usefully be stratified. The results of our analyses will help gain a better understating of the mechanisms underlying response to biologics therapies in psoriasis and identify a responder subset which will benefit most from treatment. Analysis results will be disseminated in appropriate meetings, conferences and publications.
Study Data Provided
[{ "PostingID": 4444, "Title": "NOVARTIS-CAIN457A2302", "Description": "A Randomized, Double-blind, Placebo Controlled, Multicenter Study of Subcutaneous Secukinumab to Demonstrate Efficacy After Twelve Weeks of Treatment, and to Assess the Safety, Tolerability and Long-term Efficacy up to One Year in Subjects With Moderate to Severe Chronic Plaque-type Psoriasis
Medicine: secukinumab, Condition: Psoriasis, Phase: 3, Clinical Study ID: CAIN457A2302 , Sponsor: Novartis." },{ "PostingID": 4445, "Title": "NOVARTIS-CAIN457A2303", "Description": "A Randomized, Double-blind, Double-dummy, Placebo Controlled, Multicenter Study of Subcutaneous Secukinumab to Demonstrate Efficacy After Twelve Weeks of Treatment, Compared to Placebo and Etanercept, and to Assess the Safety, Tolerability and Long-term Efficacy up to One Year in Subjects With Moderate to Severe Chronic Plaque-type Psoriasis
Medicine: secukinumab , Condition: Psoriasis, Phase: 3, Clinical Study ID: CAIN457A2303 , Sponsor: Novartis." },{ "PostingID": 4453, "Title": "LILLY-I1F-MC-RHBA", "Description": "A Multicenter, Randomized, Double-Blind, Placebo-Controlled Study Comparing the Efficacy and Safety of LY2439821 to Etanercept and Placebo in Patients With Moderate-to-Severe Plaque Psoriasis. UNCOVER-2" },{ "PostingID": 4454, "Title": "LILLY-I1F-MC-RHBC", "Description": "A 12-Week Multicenter, Randomized, Double-Blind, Placebo-Controlled Study Comparing the Efficacy and Safety of LY2439821 to Etanercept and Placebo in Patients With Moderate to Severe Plaque Psoriasis With a Long-Term Extension Period UNCOVER-3" }]
Statistical Analysis Plan
The statistical analysis plan will be added after the research is published.
Publication Citation
The publication citation will be added after the research is published.
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