Factors Predicting Persistence of Biologic Drugs in Psoriasis

A Systematic Review and Meta-analysis

A. Mourad; S. Straube; S. Armijo-Olivo; R. Gniadecki

Disclosures

The British Journal of Dermatology. 2019;181(3):450-458. 

In This Article

Abstract and Introduction

Abstract

Background: Long-term therapy for psoriasis is impaired by gradual loss of effectiveness and treatment discontinuation. Identifying factors that affect biologic drug survival may help in treatment optimization.

Objectives: To identify factors that predicted biologic drug persistence or discontinuation in a real-life setting.

Methods: We identified studies of biologic persistence in psoriasis through a comprehensive, systematic literature search using predefined search criteria. Studies were screened by title and abstract then further by full-text review. Hazard ratio (HR) data were extracted for all available predictive factors (HRs > 1 denoted biologic discontinuation, and HRs < 1 denoted biologic persistence). A meta-analysis of HRs (random-effects model) was used to assess any predictive factor included in at least two studies.

Results: Sixteen cohort studies were included in the review, with a total of 32 194 patients. A meta-analysis was performed on 13 studies (n = 29 802): nine for female sex (n = 28 090), six for obesity (n = 9311) and six for psoriatic arthritis (n = 24 444). Obesity and female sex predicted treatment discontinuation, with HRs of 1.21 [95% confidence interval (CI) 1.10–1.32, I 2 = 0%] and 1.22 (95% CI 1.07–1.38, I 2 = 84%), respectively. Concomitant psoriatic arthritis predicted biologic persistence (HR 0.83, 95% CI 0.80–0.86, I 2 = 0%). Female sex predicted biologic discontinuation due to side-effects, with a pooled HR of 2.16 (95% CI 1.39–3.35, I 2 = 67%). Other reported predictive factors (smoking, metabolic syndrome, biologic naivety, age, Dermatology Life Quality Index, dyslipidaemia, high socioeconomic status and concomitant methotrexate) were insufficiently reported for meta-analysis.

Conclusions: Our meta-analysis demonstrates that female sex and obesity predict biologic discontinuation, and concomitant psoriatic arthritis predicts biologic survival.

Introduction

Psoriasis is an immune-mediated inflammatory disorder that has a significant impact on patient quality of life.[1] It is known that patients with psoriasis have numerous comorbid conditions and risk factors, which can impact the management and outcome of their disease.[2–4] Biologic therapy is an effective option in the management of otherwise treatment-resistant psoriasis.[5,6] Current biologics used to treat psoriasis include anti-tumour necrosis factor-α agents (adalimumab, etanercept and infliximab), an anti-interleukin (IL)-12/23 biologic (ustekinumab), anti-IL-17 biologics (secukinumab and ixekizumab) and, more recently, an IL-23 inhibitor (guselkumab).[7–11] These biologics are able to produce long-term remission of psoriasis;[12–14] however, the disease usually recurs once the treatment is discontinued.[15–17]

Drug survival is the time until drug discontinuation and is considered to be an important real-world measurement of biologic treatment success.[17–19] Biologics that have prolonged drug survival rates are associated with superior efficacy and safety profiles.[20–22] In addition, prolonged treatment adherence is noted as a surrogate measure for treatment success.[23] The predictive factors for survival of biologics remain unclear, as no pooled analysis of these data has, to our knowledge, been performed yet. We therefore conducted a systematic review and meta-analysis of eligible studies that assessed drug survival of biologics to identify the predictive factors for biologic discontinuation and persistence in psoriasis. We hypothesize that this study will yield distinct predictive factors that predict either lower or higher biologic persistence rates. Knowing which factors predict biologic treatment persistence or discontinuation is important in understanding the interplay between biologics and certain patient cohorts with psoriasis.[23,24] In turn, this knowledge may help guide biologic treatment decisions and improve treatment outcome in patients with psoriasis.

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