Evidence map›Paper›PMID 31917873›Full record

SynthesisThe Cochrane database of systematic reviews2020

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.

Emilie Sbidian, Anna Chaimani, Sivem Afach, Liz Doney, Corinna Dressler, Camille Hua, Canelle Mazaud, Céline Phan, Carolyn Hughes, Dru Riddle and 3 more

Open access · greenAbstract readNetwork Meta-AnalysisSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 6 pooled it
11.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 6 syntheses or guidelines pooled it, 170 citations in OpenAlex.

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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 7 institutions in 5 countries.

Emilie SbidianHôpital Henri Mondor, Department of Dermatology, 51 Avenue du Maréchal de Lattre de Tassigny, Créteil, France, 94000.
Anna ChaimaniUniversité de Paris, Research Center in Epidemiology and Statistics Sorbonne Paris Cité (CRESS-UMR1153), Inserm, Inra, F-75004, Paris, France.
Sivem AfachUniversité Paris Est Créteil (UPEC), Epidemiology in dermatology and evaluation of therapeutics (EpiDermE) - EA 7379, Créteil, France.
Liz DoneyCochrane Skin Group, The University of Nottingham, Centre of Evidence Based Dermatology, A103, King's Meadow Campus, Lenton Lane, Nottingham, UK, NG7 2NR.
Corinna DresslerCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Division of Evidence Based Medicine, Department of Dermatology, Venerology and Allergology, Charitéplatz 1, Berlin, Germany, 10117.
Camille HuaHôpital Henri Mondor, Department of Dermatology, 51 Avenue du Maréchal de Lattre de Tassigny, Créteil, France, 94000.
Canelle MazaudHôpital Henri Mondor, Department of Dermatology, 51 Avenue du Maréchal de Lattre de Tassigny, Créteil, France, 94000.
Céline PhanCentre Hospitalier Victor Dupouy, Department of Dermatology, Argenteuil, France.
Carolyn HughesThe University of Nottingham, c/o Cochrane Skin Group, A103, King's Meadow Campus, Lenton Lane, Nottingham, UK, NG7 2NR.
Dru RiddleTexas Christian University (TCU), School of Nurse Anesthesia, Fort Worth, Texas, USA.
Luigi NaldiPadiglione Mazzoleni - Presidio Ospedaliero Matteo Rota, Centro Studi GISED (Italian Group for Epidemiologic Research in Dermatology) - FROM (Research Foundation of Ospedale Maggiore Bergamo), Via Garibaldi 13/15, Bergamo, Italy, 24122.
Ignacio Garcia-DovalComplexo Hospitalario Universitario de Vigo, Department of Dermatology, Meixoeiro sn, Vigo, Spain, 36214.
Laurence Le CleachHôpital Henri Mondor, Department of Dermatology, 51 Avenue du Maréchal de Lattre de Tassigny, Créteil, France, 94000.
Université Paris-Est Créteil · FRCharité - Universitätsmedizin Berlin · DECochrane · GBPresidio Ospedaliero · ITUniversité Paris Cité · FRUniversity Hospital Complex Of Vigo · ESUniversity of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPsoriasis is an immune-mediated disease for which some people have a genetic predisposition. The condition manifests in inflammatory effects on either the skin or joints, or both, and it has a major impact on quality of life. Although there is currently no cure for psoriasis, various treatment strategies allow sustained control of disease signs and symptoms. Several randomised controlled trials (RCTs) have compared the efficacy of the different systemic treatments in psoriasis against placebo. However, the relative benefit of these treatments remains unclear due to the limited number of trials comparing them directly head-to-head, which is why we chose to conduct a network meta-analysis. This is the baseline update of a Cochrane Review first published in 2017, in preparation for this Cochrane Review becoming a living systematic review.

objectivesTo compare the efficacy and safety of conventional systemic agents, small molecules, and biologics for people with moderate-to-severe psoriasis, and to provide a ranking of these treatments according to their efficacy and safety. SEARCH

methodsWe updated our research using the following databases to January 2019: the Cochrane Skin Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, LILACS and the conference proceedings of a number of dermatology meetings. We also searched five trials registers and the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) reports (until June 2019). We checked the reference lists of included and excluded studies for further references to relevant RCTs. SELECTION CRITERIA: Randomised controlled trials (RCTs) of systemic treatments in adults (over 18 years of age) with moderate-to-severe plaque psoriasis or psoriatic arthritis whose skin had been clinically diagnosed with moderate-to-severe psoriasis, at any stage of treatment, in comparison to placebo or another active agent. The primary outcomes of this review were: the proportion of participants who achieved clear or almost clear skin, that is, at least Psoriasis Area and Severity Index (PASI) 90 at induction phase (from 8 to 24 weeks after the randomisation), and the proportion of participants with serious adverse effects (SAEs) at induction phase. We did not evaluate differences in specific adverse effects. DATA COLLECTION AND ANALYSIS: Several groups of two review authors independently undertook study selection, data extraction, 'Risk of bias' assessment, and analyses. We synthesised the data using pair-wise and network meta-analysis (NMA) to compare the treatments of interest and rank them according to their effectiveness (as measured by the PASI 90 score) and acceptability (the inverse of serious adverse effects). We assessed the certainty of the body of evidence from the NMA for the two primary outcomes, according to GRADE, as either very low, low, moderate, or high. We contacted study authors when data were unclear or missing. MAIN

resultsWe included 140 studies (31 new studies for the update) in our review (51,749 randomised participants, 68% men, mainly recruited from hospitals). The overall average age was 45 years; the overall mean PASI score at baseline was 20 (range: 9.5 to 39). Most of these studies were placebo-controlled (59%), 30% were head-to-head studies, and 11% were multi-armed studies with both an active comparator and a placebo. We have assessed a total of 19 treatments. In all, 117 trials were multicentric (two to 231 centres). All but two of the outcomes included in this review were limited to the induction phase (assessment from 8 to 24 weeks after randomisation). We assessed many studies (57/140) as being at high risk of bias; 42 were at an unclear risk, and 41 at low risk. Most studies (107/140) declared funding by a pharmaceutical company, and 22 studies did not report the source of funding. Network meta-analysis at class level showed that all of the interventions (conventional systemic agents, small molecules, and biological treatments) were significantly more effective than placebo in terms of reaching PASI 90. At class level, in terms of reaching PASI 90, the biologic treatments anti-IL17, anti-IL12/23, anti-IL23, and anti-TNF alpha were significantly more effective than the small molecules and the conventional systemic agents. At drug level, in terms of reaching PASI 90, infliximab, all of the anti-IL17 drugs (ixekizumab, secukinumab, bimekizumab and brodalumab) and the anti-IL23 drugs (risankizumab and guselkumab, but not tildrakizumab) were significantly more effective in reaching PASI 90 than ustekinumab and 3 anti-TNF alpha agents: adalimumab, certolizumab and etanercept. Adalimumab and ustekinumab were significantly more effective in reaching PASI 90 than certolizumab and etanercept. There was no significant difference between tofacitinib or apremilast and between two conventional drugs: ciclosporin and methotrexate. Network meta-analysis also showed that infliximab, ixekizumab, risankizumab, bimekizumab, guselkumab, secukinumab and brodalumab outperformed other drugs when compared to placebo in reaching PASI 90. The clinical effectiveness for these seven drugs was similar: infliximab (versus placebo): risk ratio (RR) 29.52, 95% confidence interval (CI) 19.94 to 43.70, Surface Under the Cumulative Ranking (SUCRA) = 88.5; moderate-certainty evidence; ixekizumab (versus placebo): RR 28.12, 95% CI 23.17 to 34.12, SUCRA = 88.3, moderate-certainty evidence; risankizumab (versus placebo): RR 27.67, 95% CI 22.86 to 33.49, SUCRA = 87.5, high-certainty evidence; bimekizumab (versus placebo): RR 58.64, 95% CI 3.72 to 923.86, SUCRA = 83.5, low-certainty evidence; guselkumab (versus placebo): RR 25.84, 95% CI 20.90 to 31.95; SUCRA = 81; moderate-certainty evidence; secukinumab (versus placebo): RR 23.97, 95% CI 20.03 to 28.70, SUCRA = 75.4; high-certainty evidence; and brodalumab (versus placebo): RR 21.96, 95% CI 18.17 to 26.53, SUCRA = 68.7; moderate-certainty evidence. Conservative interpretation is warranted for the results for bimekizumab (as well as tyrosine kinase 2 inhibitor, acitretin, ciclosporin, fumaric acid esters, and methotrexate), as these drugs, in the NMA, have been evaluated in few trials. We found no significant difference between any of the interventions and the placebo for the risk of SAEs. Nevertheless, the SAE analyses were based on a very low number of events with low to very low certainty for just under half of the treatment estimates in total, and moderate for the others. Thus, the results have to be viewed with caution and we cannot be sure of the ranking. For other efficacy outcomes (PASI 75 and Physician Global Assessment (PGA) 0/1) the results were very similar to the results for PASI 90. Information on quality of life was often poorly reported and was absent for several of the interventions. AUTHORS'

conclusionsOur review shows that compared to placebo, the biologics infliximab, ixekizumab, risankizumab, bimekizumab, guselkumab, secukinumab and brodalumab were the best choices for achieving PASI 90 in people with moderate-to-severe psoriasis on the basis of moderate- to high-certainty evidence (low-certainty evidence for bimekizumab). This NMA evidence is limited to induction therapy (outcomes were measured from 8 to 24 weeks after randomisation) and is not sufficient for evaluation of longer-term outcomes in this chronic disease. Moreover, we found low numbers of studies for some of the interventions, and the young age (mean age of 45 years) and high level of disease severity (PASI 20 at baseline) may not be typical of patients seen in daily clinical practice. Another major concern is that short-term trials provide scanty and sometimes poorly-reported safety data and thus do not provide useful evidence to create a reliable risk profile of treatments. Indeed, we found no significant difference in the assessed interventions and placebo in terms of SAEs, but the evidence for all the interventions was of very low to moderate quality. In order to provide long-term information on the safety of the treatments included in this review, it will also be necessary to evaluate non-randomised studies and postmarketing reports released from regulatory agencies. In terms of future research, randomised trials comparing directly active agents are necessary once high-quality evidence of benefit against placebo is established, including head-to-head trials amongst and between conventional systemic and small molecules, and between biological agents (anti-IL17 versus anti-IL23, anti-IL23 versus anti-IL12/23, anti-TNF alpha versus anti-IL12/23). Future trials should also undertake systematic subgroup analyses (e.g. assessing biological-naïve participants, baseline psoriasis severity, presence of psoriatic arthritis, etc.). Finally, outcome measure harmonisation is needed in psoriasis trials, and researchers should look at the medium- and long-term benefit and safety of the interventions and the comparative safety of different agents. Editorial note: This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Indexed as

Antibodies, MonoclonalImmunosuppressive AgentsPsoriasisAntibodies, Monoclonal, HumanizedChronic DiseaseCytokinesHumansMolecular Targeted TherapyRandomized Controlled Trials as TopicRemission InductionSeverity of Illness IndexTreatment OutcomeTumor Necrosis Factor-alphaAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedCytokinesImmunosuppressive AgentsTumor Necrosis Factor-alpha

Identifiers

PMID31917873
PMCPMC6956468
OpenAlexW4237432556

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.