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Original Article| Volume 99, ISSUE 1, P53-61, July 2020

Short-term effectiveness of biologics in patients with moderate-to-severe plaque psoriasis: A systematic review and network meta-analysis

Open AccessPublished:June 18, 2020DOI:https://doi.org/10.1016/j.jdermsci.2020.06.003

      Highlights

      • This network meta-analysis included 41 trials in 19,248 psoriasis patients.
      • Brodalumab and ixekizumab were more effective than others for PASI100 achievement.
      • Brodalumab, ixekizumab and risankizumab were more effective for PASI90 achievement.
      • Brodalumab, ixekizumab and risankizumab had high probability of being most effective.

      Abstract

      Background

      Complete lesion clearance is important to patients with psoriasis.

      Objective

      To conduct a network meta-analysis of randomized controlled trials of biologic agents available for psoriasis in Japan, using mixed-treatment comparisons.

      Methods

      MEDLINE and EMBASE were searched to identify randomized clinical trials (placebo-controlled or head-to-head) of infliximab, adalimumab, ustekinumab, secukinumab, ixekizumab, brodalumab, risankizumab or guselkumab in adult patients with moderate-to-severe plaque psoriasis published in English between 01 January 2000 and 31 August 2019. We assessed the proportion of patients who achieved a 100 %, 90 % and 75 % reduction in their Psoriasis Area and Severity Index (PASI) score (PASI100, PASI90 and PASI75) at 10, 12 or 16 weeks after starting biologic treatment, using contrast-based network meta-analysis methods and risk difference (RD). Probabilities of rank and surface under the cumulative ranking (SUCRA) were also estimated.

      Results

      Data were pooled from 41 trials in 19,248 patients. All biologics were significantly more effective than placebo for PASI100, PASI90 and PASI75. The RD for PASI100 for brodalumab vs ixekizumab was 0.05 (95 % Confidence intervals [CI] –0.02, 0.11), brodalumab vs risankizumab was 0.04 (95 %CI –0.03, 0.11), and risankizumab vs ixekizumab was –0.01 (95 %CI –0.08, 0.06). The SUCRA for PASI100 and PASI90 achievement was 96.8 % and 86.8 %, respectively, for brodalumab, 82.6 % and 90.3 %, respectively for risankizumab, and 78.3 %, 80.9 %, respectively, for ixekizumab.

      Conclusion

      Of the biologics assessed, brodalumab, ixekizumab and risankizumab were the greatest rates of PASI90 and PASI100 achievement, and a higher probability of being most effective in the induction phase, compared with the other biologics.

      Keywords

      1. Introduction

      Psoriasis is a chronic systemic inflammatory disorder characterized by persistent or repeating skin lesions [
      • Greb J.E.
      • Goldminz A.M.
      • Elder J.T.
      • Lebwohl M.G.
      • Gladman D.D.
      • Wu J.J.
      • Mehta N.N.
      • Finlay A.Y.
      • Gottlieb A.B.
      Psoriasis.
      ]. Estimates suggest that more than 125 million people worldwide are affected by psoriasis [
      • Greb J.E.
      • Goldminz A.M.
      • Elder J.T.
      • Lebwohl M.G.
      • Gladman D.D.
      • Wu J.J.
      • Mehta N.N.
      • Finlay A.Y.
      • Gottlieb A.B.
      Psoriasis.
      ], with the prevalence ranging from 2.7 % in the USA to 8.7 % in Norway [
      • Parisi R.
      • Symmons D.P.
      • Griffiths C.E.
      • Ashcroft D.M.
      Global epidemiology of psoriasis: a systematic review of incidence and prevalence.
      ]. The chronic activation of the innate and adaptive immune systems is involved in psoriatic disease manifestations, leading to increased release of pro-inflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin (IL)-17, IL-12, and IL-23 [
      • Greb J.E.
      • Goldminz A.M.
      • Elder J.T.
      • Lebwohl M.G.
      • Gladman D.D.
      • Wu J.J.
      • Mehta N.N.
      • Finlay A.Y.
      • Gottlieb A.B.
      Psoriasis.
      ]. This has led to the development of biologic therapies targeting these pro-inflammatory mediators for patients with psoriasis, including monoclonal antibodies targeting these cytokines, e.g., adalimumab and infliximab target TNF-α, ustekinumab targets p40 (IL-12/23), guselkumab and risankizumab targets p19 (IL-23), secukinumab and ixekizumab target IL-17A ligand, and brodalumab targets the IL-17R alpha receptor [
      • Greb J.E.
      • Goldminz A.M.
      • Elder J.T.
      • Lebwohl M.G.
      • Gladman D.D.
      • Wu J.J.
      • Mehta N.N.
      • Finlay A.Y.
      • Gottlieb A.B.
      Psoriasis.
      ].
      Psoriasis has a profound negative impact on patients’ health-related quality of life (HRQoL) [
      • Duvetorp A.
      • Ostergaard M.
      • Skov L.
      • Seifert O.
      • Tveit K.S.
      • Danielsen K.
      • Iversen L.
      Quality of life and contact with healthcare systems among patients with psoriasis and psoriatic arthritis: results from the NORdic PAtient survey of Psoriasis and Psoriatic arthritis (NORPAPP).
      ,
      • Rapp S.R.
      • Feldman S.R.
      • Exum M.L.
      • Fleischer Jr., A.B.
      • Reboussin D.M.
      Psoriasis causes as much disability as other major medical diseases.
      ]. In a comparative study, the impact of psoriasis on the mental and physical components of quality of life (as measured by the Short Form-36 questionnaire) were comparable with those of heart. disease and diabetes and so on [
      • Rapp S.R.
      • Feldman S.R.
      • Exum M.L.
      • Fleischer Jr., A.B.
      • Reboussin D.M.
      Psoriasis causes as much disability as other major medical diseases.
      ]. However, HRQoL improves markedly with effective treatment [
      • Elewski B.E.
      • Puig L.
      • Mordin M.
      • Gilloteau I.
      • Sherif B.
      • Fox T.
      • Gnanasakthy A.
      • Papavassilis C.
      • Strober B.E.
      Psoriasis patients with psoriasis Area and Severity Index (PASI) 90 response achieve greater health-related quality-of-life improvements than those with PASI 75-89 response: results from two phase 3 studies of secukinumab.
      ]; the proportion of patients with HRQoL scores indicating no effect of psoriasis on their daily life (score of 0/1 on the Dermatology Quality of Life Index) was significantly greater among patients who had a 90 % reduction in Psoriasis Area and Severity Index scores (PASI90) or a 100 % reduction (PASI100) than those with lower PASI achievements rates [
      • Elewski B.E.
      • Puig L.
      • Mordin M.
      • Gilloteau I.
      • Sherif B.
      • Fox T.
      • Gnanasakthy A.
      • Papavassilis C.
      • Strober B.E.
      Psoriasis patients with psoriasis Area and Severity Index (PASI) 90 response achieve greater health-related quality-of-life improvements than those with PASI 75-89 response: results from two phase 3 studies of secukinumab.
      ]. Therefore, important goals of therapy for patients (and therefore, by extension, for physicians) include rapid and complete clearance of skin lesions [
      • Blome C.
      • Gosau R.
      • Radtke M.A.
      • Reich K.
      • Rustenbach S.J.
      • Spehr C.
      • Thaci D.
      • Augustin M.
      Patient-relevant treatment goals in psoriasis.
      ].
      For this reason, it is important to evaluate the short-term treatment efficacy of the available drugs, using not only the proportion of patients who achieved a 75 % reduction in PASI (PASI75) but also PASI90 and PASI100, during the induction phase (short-term) of therapy. Network meta-analysis (NMA) is an evidence synthesis method that can be used to understand the comparative efficacy of different drugs. NMA offers the advantage of multiple pair-wise treatment comparisons that use the total body of available evidence involving indirect evidence, even when head-to-head studies are missing [
      • Jansen J.P.
      • Fleurence R.
      • Devine B.
      • Itzler R.
      • Barrett A.
      • Hawkins N.
      • Lee K.
      • Boersma C.
      • Annemans L.
      • Cappelleri J.C.
      Interpreting indirect treatment comparisons and network meta-analysis for health-care decision making: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 1.
      ]. Thus, the aim of this NMA was to map out the relative positioning of the eight biologics approved in Japan in adult patients with moderate-to-severe plaque psoriasis based on their effect on PASI outcomes during the induction phase of treatment, using data from randomized, controlled trials.

      2. Materials and methods

      2.1 Reporting guideline and protocol

      The study protocol was registered with the International Prospective Register of Systematic Reviews (registration number CRD42017063906; see https://www.crd.york.ac.uk/prospero/). This study is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension statement for systematic reviews incorporating NMA of health care interventions (Appendix A).

      2.2 Data source and search strategies

      We conducted a systematic review of the published literature identified using the MEDLINE and EMBASE electronic databases. The literature search strategy used medical subject headings (MeSH) and text words related to psoriasis, along with a Boolean search string of MeSH terms for the biologic agents (infliximab OR adalimumab OR ustekinumab OR secukinumab OR ixekizumab OR brodalumab OR biologic agents OR tumor necrosis factor inhibitor OR interleukin 17 antibody). The search, conducted in May 2017, was limited to English-language articles reporting randomized controlled trials in human adults, and published between 01 January 2000 and 31 March 2017. In November 2017, the search was revised, adding guselkumab and interleukin 23 antibody, and extending the publication date to 30 September 2017. In September 2019, the search was further revised, adding risankizumab, and extending the publication date to 31 August 2019. A copy of this latter search strategy is provided in AppendixB. An update search was run on 18 September 2019.

      2.3 Study selection and eligibility criteria

      Two authors (Y.T. and R.W.) independently reviewed the results of the literature search and selected randomized clinical trials (placebo-controlled or head-to-head trials) in adult patients with moderate-to-severe psoriasis, in which treatment effect by PASI75, PASI100 and/or PASI100 was assessed at 10–16 weeks after starting biologic treatment. This analysis was undertaken based on the article title and abstract. Any disagreements between Y.T. and R.W. about article inclusion were resolved by rational scientific debate until a consensus was reached. Case reports, letters, editorials, conference abstracts, and conference papers were excluded, as were retrospective studies. Full text copies of potentially relevant articles were then evaluated in order to exclude all studies with agents that were not specifically included in our initial search plan, including studies in which the biologic agent of interest was combined with another agent, and studies that included individuals aged >75 years or <18 years. Studies with results in both adults and children were included if the data for adults were reported separately. We did not exclude studies in patients with psoriatic arthritis but patients were required also to have plaque psoriasis. Only studies in which the biologics were used at dosages approved for the treatment of psoriasis in Japan were included (see Table S1 in the Appendix C – Supplementary materials).

      2.4 Data extraction

      Two authors (Y.T. and R.W.) extracted the relevant data from each study into a spreadsheet using predefined criteria including site of study (global, regional, national); number of patients included; inclusion criteria (diagnosis, severity, minimum PASI, age); baseline patient characteristics (age, gender, bodyweight, body mass index [BMI], PASI); comparators; timing of assessments; achievement of PASI100, PASI90, and PASI75 at the end of the induction phase. Additional information related to bias assessment (see below) was also extracted into the spreadsheet.

      2.5 Risk of bias assessment

      To evaluate the possible risk of bias within studies, we conducted risk assessment using the Cochrane Collaboration tools based on the following features of the included studies: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, and selective outcome reporting [
      • Higgins J.P.
      • Altman D.G.
      • Gotzsche P.C.
      • Juni P.
      • Moher D.
      • Oxman A.D.
      • Savovic J.
      • Schulz K.F.
      • Weeks L.
      • Sterne J.A.
      The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials.
      ]. The judgments were independently conducted by two reviewers (Y.T. and R.W.).

      2.6 Outcomes

      The outcomes assessed in this NMA were the number of patients who achieved PASI100, PASI90, and PASI75 at 10, 12 or 16 weeks of treatment.

      2.7 Statistical analysis

      The comparative effectiveness of the nine treatments (infliximab, adalimumab, ustekinumab, secukinumab, ixekizumab, brodalumab, guselkumab, risankizumab and placebo) was evaluated using NMA techniques [
      • Salanti G.
      Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool.
      ]. First, we summarized the geometry of the network of evidence using network plots. Then, standard pairwise meta-analyses were conducted for all the direct comparisons using the ordinary DerSimonian-Laird-type random-effects model [
      • DerSimonian R.
      • Larid N.M.
      Meta-analysis in clinical trials.
      ]. Treatment effects were measured using risk difference (RD). Thereafter, the comparative efficacy was assessed using contrast-based NMA methods [
      • Salanti G.
      • Higgins J.P.
      • Ades A.E.
      • Ioannidis J.P.
      Evaluation of networks of randomized trials.
      ]. To address the heterogeneity of treatment effects among the studies, the multivariate random effect model was used [
      • Salanti G.
      • Higgins J.P.
      • Ades A.E.
      • Ioannidis J.P.
      Evaluation of networks of randomized trials.
      ]. The multi-armed trials were modelled as multivariate outcome variables, and their within-studies correlations were adequately addressed by the multivariate meta-analysis model [
      • White I.R.
      • Barrett J.K.
      • Jackson D.
      • Higgins J.P.
      Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression.
      ]. The probabilities of ranks and surface under the cumulative ranking (SUCRA) of the treatments were also estimated, based on parametric bootstrap methods [
      • Hutton B.
      • Salanti G.
      • Caldwell D.M.
      • Chaimani A.
      • Schmid C.H.
      • Cameron C.
      • Ioannidis J.P.
      • Straus S.
      • Thorlund K.
      • Jansen J.P.
      • Mulrow C.
      • Catala-Lopez F.
      • Gotzsche P.C.
      • Dickersin K.
      • Boutron I.
      • Altman D.G.
      • Moher D.
      The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations.
      ].
      In addition, the consistency of the network was evaluated using tests of local and global inconsistency. The local inconsistency tests evaluate the loop inconsistency by (pseudo-) Wald tests of all the triangle loops on the network [
      • Bucher H.C.
      • Guyatt G.H.
      • Griffith L.E.
      • Walter S.D.
      The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials.
      ]. The global inconsistency test is a goodness-of-fit test using the Higgins’s design-by-treatment interaction model [
      • Higgins J.P.
      • Jackson D.
      • Barrett J.K.
      • Lu G.
      • Ades A.E.
      • White I.R.
      Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies.
      ]. Also, we assessed publication biases using the comparison-adjusted funnel plots. All analyses were performed using Stata version 15 (StataCorp LLC, College Station, TX). All P-values quoted are 2-sided.

      3. Results

      3.1 Study selection

      Among 2548 records identified in the database search (1863 after duplicates were removed), 37 articles reporting the results of 41 clinical studies met the inclusion criteria (Fig. 1)(see Appendix D for the list of papers). The studies included 19,248 patients with psoriasis, and were published between 2000 and 2019; eleven were head-to-head studies and all but five included a placebo comparator. Twenty-seven were international/global studies, six were conducted in Japan, three in China, two in North America, two in the USA, and one in Taiwan and Korea.
      Fig. 1
      Fig. 1PRISMA Flowchart of Search Results and Study Selection.
      The clinical trials were deemed sufficiently similar on the baseline characters of age, gender, body weight or BMI, and PASI score. Sample sizes ranged from 11 to 814 psoriasis patients, of whom between 58 % and 91 % were male. Mean age ranged from 39.2–53.9 years, mean body weight from 67 to 94.2 kg, mean BMI from 23.6–31.5 kg/m2, and mean baseline PASI score from 16.0–33.1. The assessment of treatment efficacy was made at Week 10 in 6 trials, Week 12 in 23 trials, and Week 16 in 10 trials (Table 1). In two trial, the assessment of treatment efficacy was made at Week 12 for PASI75 and, at Week 16 for PASI 90 and PASI 100. The mean rate of PASI75 achievement ranged from 0.0 % through 94.6 %, PASI90 achievement from 0.0 % through 91.9 %, and PASI100 achievement from 0.0 % through 62.0 %.
      Table 1Characteristics of the studies included in the network meta-analysis.
      Source
      See list of reference in Appendix D.
      Study designPatient baseline characteristicsOutcomes, n (%)
      Intervention TypeLocationEndpoint assessment, WeekNMean age, yMale, n (%)Mean body weight, kgMean BMI, km/m2Mean PASI scorePASI75PASI90PASI100
      Reich et al 2019 [1]adalimumabGlobal1630447212 (70)91.430.819.7218(72.0)144 (47.0)70 (23.0)
      risankizumab1630145.3210 (70)88.830.220273 (91.0)218 (72.0)120 (40.0)
      Ohtsuki et al 2019 [2]placeboJapan165850.945 (78)75.126.7245 (8.6)1 (1.7)0 (0.0)
      risankizumab165553.950 (91)74.126.426.352 (94.5)41 (74.5)18 (32.7)
      Gordon et al 2018 [3]ustekinumabGlobal12/1610046.570 (70)88.929.820.170 (70.0)42 (42.0)12 (12.0)
      placebo12/1610249.379 (77)88.829.520.510 (9.8)5 (4.9)0 (0.0)
      risankizumab12/1630448.3212 (70)87.829.920.6264 (86.8)229 (75.3)109 (35.9)
      Gordon et al 2018 [3]ustekinumabGlobal12/169948.666 (67)91.930.918.269 (69.7)47 (47.5)24 (24.2)
      placebo12/169846.367 (68)92.23118.98 (8.2)2 (2)2 (2)
      risankizumab12/1629446.2203 (69)92.231.120.5261 (88.8)220 (74.8)149 (50.7)
      Ferris et al 2020 [4]placeboGlobal161645.412 (75.0)18.40 (0.0)0 (0.0)0 (0.0)
      guselkumab166246.241 (66.1)17.955 (88.7)47 (75.8)31 (50)
      Reich et al 2019 [5]secukinumabGlobal1251445.3342 (67)3020.1471 (92)391 (76)
      guselkumab1253446.3365 (68)29.820477 (89)369 (69)
      Bagle et al 2018 [6]ustekinumabGlobal1255245.3376 (68.1)9321.3410 (74.2)264 (47.9)111 (20.1)
      secukinumab1255045.4366 (64.7)9120.8484 (88)366 (66.5)199 (38.1)
      Ohstuki et al 2018 [7]placeboJapan166448.354 (84.4)71.625.425.94 (6.3)0 (0.0)0 (0.0)
      guselkumab166347.847 (74.6)74.326.326.753 (84.1)44 (69.8)17 (27)
      Reich et al 2017 [8]ustekinumabGlobal1216644112 (67.5)89.429.719.8114 (68.7)70 (42.2)24 (14.5)
      ixekizumab1213642.790 (66.2)85.828.819.9120 (88.2)99 (72.8)49 (36)
      Lacour et al 2017 [9]PlaceboGlobal126143.738 (62.3)90.230.019.42 (3.3)0 (0.0)0 (0.0)
      Secukinumab126046.646 (76.7)91.030.018.953 (88.0)33 (55.6)16 (26.9)
      Reich et al 2017 [10]PlaceboGlobal1624843.3173 (69.8)29.621.520 (8.1)6 (2.4)2 (0.8)
      Adalimumab1624843.2170 (68.5)29.621.7170 (68.5)116 (46.8)51 (20.6)
      Guselkumab1649643.7349 (70.4)29.621.9428 (86.3)347 (70.0)169 (34.1)
      Blauvelt et al 2017 [11]PlaceboGlobal1617444.9119 (68.4)28.920.410 (5.7)5 (2.9)1 (0.6)
      Adalimumab1633442.9249 (74.6)29.822.4244 (73.1)166 (49.7)57 (17.1)
      Guselkumab1632943.9240 (72.9)29.722.1300 (91.2)241 (73.3)123 (37.4)
      Cai et al 2017 [12]PlaceboChina128743.858 (66.7)6723.625.610 (11.5)3 (3.4)1 (1.1)
      Adalimumab1233843.1254 (75.1)69.724.428.2263 (77.8)188 (55.6)45 (13.3)
      Gordon et al 2016 [13]PlaceboGlobal1243146303 (70.3)922017 (3.9)2 (0.5)0 (0.0)
      Ixekizumab1243345291 (67.2)9220386 (89.1)307 (70.9)153 (35.3)
      Nakagawa et al 2016 [14]PlaceboJapan123846.627 (71.1)72.1626.0223.973 (7.9)1 (2.6)0 (0.0)
      Brodalumab123746.429 (78.4)72.5926.3427.9835 (94.6)34 (91.9)22 (59.5)
      Papp et al 2016 [15]PlaceboGlobal1222047161 (73)90.430.319.76 (2.7)2 (0.9)1 (0.5)
      Brodalumab1222246162 (73)91.43119.4185 (83.3)156 (70.3)93 (41.9)
      Blauvelt et al 2015 [16]PlaceboGlobal125946.539 (66.1)88.421.10 (0.0)0 (0.0)0 (0.0)
      Secukinumab125945.138 (64.4)92.620.745 (75.9)36 (60.3)25 (43.1)
      Griffiths et al 2015 [17]PlaceboGlobal1216845119 (71)9231214 (2.4)1 (0.6)1 (0.6)
      Ixekizumab1235145221 (63)893019315 (89.7)248 (70.7)142 (40.5)
      Griffiths et al 2015 [17]PlaceboGlobal1219346137 (71)91302114 (7.3)6 (3.1)0 (0.0)
      Ixekizumab1238546254 (66)903021336 (87.3)262 (68.1)145 (37.7)
      Lebwohl et al 2015 [18]PlaceboGlobal1230944219 (71)9230.520.425 (8)10 (3)2 (1)
      Brodalumab1261245422 (69)9130.520.3528 (86)430 (70)272 (44)
      Ustekinumab 45 mg or 90 mg1230045204 (68)9130.620210 (70)141 (47)65 (22)
      Lebwohl et al 2015 [18]PlaceboGlobal1231544208 (66)8929.920.119 (6)5 (2)1 (0.3)
      Brodalumab1262445431 (69)9030.320.4531 (85)429 (69)229 (37)
      Ustekinumab 45 mg or 90 mg1231345213 (68)9030.420.1217 (69)149 (48)58 (19)
      Paul et al 2015 [19]PlaceboGlobal126143.738 (62.3)90.23019.42 (3.3)0 (0.0)0 (0.0)
      Secukinumab126046.646 (76.7)913018.952 (86.7)33 (55.0)16 (26.7)
      Thaci et al 2015 [20]SecukinumabGlobal1633745.2229 (68)87.429.121.7311 (93.1)264 (79.0)148 (44.3)
      Ustekinumab 45 mg or 90 mg1633944.6252 (74.3)87.22921.5283 (84.5)199 (59.5)98 (29.3)
      Langley et al 2014 [21]PlaceboGlobal1224845.4172 (69.4)89.730.321.411 (4.5)3 (1.2)2 (0.8)
      Secukinumab1224544.9269 (69.0)88.830.322.5200 (81.6)145 (59.2)70 (28.6)
      Langley et al 2014 [21]PlaceboGlobal1232644.1237 (72.7)8227.924.116 (4.9)5 (1.5)0 (0.0)
      Secukinumab1232744.5224 (68.5)8328.423.9249 (77.1)175 (54.2)78 (24.1)
      Zhu et al 2013 [22]PlaceboChina1216239.2123 (75.9)7022.718 (11.1)5 (3.1)1 (0.6)
      Ustekinumab 45 mg1216040.1125 (78.1)69.923.2132 (82.5)107 (66.9)38 (23.8)
      Igarashi et al 2012 [23]PlaceboJapan12324927 (83.9)71.225.330.32 (6.5)1 (3.2)
      Ustekinumab 45 mg12644553 (82.8)73.226.130.138 (59.4)21 (32.8)
      Ustekinumab 90 mg12624447 (75.8)71.125.728.742 (67.7)27 (43.5)
      Papp et al 2012 [24]PlaceboGlobal123841.822 (58)86.929.318.90 (0.0)0 (0.0)0 (0.0)
      Brodalumab124042.125 (62)90.429.820.633 (82)30 (75)25 (62)
      Yang et al 2012 [25]PlaceboChina104540.135 (77.8)67.425.31 (2.2)0 (0)
      Infliximab108439.460 (71.4)68.223.968 (81)48 (57.1)
      Tsai et al 2011 [26]PlaceboTaiwan, Korea126040.453 (88.3)74.622.93 (5.0)1 (1.7)0 (0.0)
      Ustekinumab 45 mg126140.950 (82)73.125.241 (67.2)30 (49.2)5 (8.2)
      Asahina et al 2010 [27]PlaceboJapan164643.941 (89.1)71.329.12 (4.3)0 (0.0)
      Adalimumab164344.235 (81.4)67.430.2427 (62.8)17 (39.5)
      Torii et al 2010 [28]PlaceboJapan101943.314 (73.7)69.724.933.10 (0.0)0 (0.0)
      Infliximab103546.922 (62.9)68.525.231.924 (68.6)19 (54.3)
      Leonardi et al 2008 [29]PlaceboGlobal1225544.8183 (71.8)94.220.48 (3.1)5 (2.0)0 (0.0)
      Ustekinumab 45 mg1225544.8175 (68.6)93.720.5171 (67.1)106 (41.6)32 (12.5)
      Ustekinumab 90 mg1225646.2173 (67.6)93.819.7170 (66.4)94 (36.7)28 (10.9)
      Menter et al 2008 [30]PlaceboNorth America1639845.4257 (64.6)94.118.826 (7)8 (2)4 (1)
      Adalimumab1681444.1546 (67.1)92.319.0578 (71)366 (45)163 (20)
      Papp et al 2008 [31]PlaceboGlobal1241047.0283 (69.0)91.119.415 (3.7)3 (0.7)0 (0.0)
      Ustekinumab 45 mg1240945.1283 (69.2)90.319.4273 (66.7)173 (42.3)74 (18.1)
      Ustekinumab 90 mg1241146.6274 (66.7)91.520.1311 (75.7)209 (50.9)75 (18.2)
      Saurat et al 2008 [32]PlaceboGlobal165340.735 (66.0)82.619.210 (18.9)6 (11.3)1 (1.9)
      Adalimumab1610842.970 (64.8)81.720.286 (79.6)56 (51.9)18 (16.7)
      Menter et al 2007 [33]PlaceboGlobal1020844.4144 (69.2)91.119.84 (1.9)1 (0.5)
      Infliximab1031444.5204 (65.0)92.220.4237 (75.5)142 (45.2)
      Gordon et al 2006 [34]PlaceboNorth America12524334 (65)9416.02 (4)0 (0)
      Adalimumab12454632 (71)9316.724 (53)11 (24)5 (11)
      Reich et al 2005 [35]PlaceboGlobal107743.861 (79)22.82 (3)1 (1)0
      Infliximab1030142.6208 (69)22.9242 (80)172 (57)77 (26)
      Gottlieb et al 2004 [36]PlaceboUSA10514531 (60.8)183 (5.9)1 (2.0)
      Infliximab10994473 (73.7)2087 (87.9)57 (57.6)
      Chaudhari et al 2001 [37]PlaceboUSA1011458 (72.7)8520.32 (18.2)
      Infliximab1011517 (63.6)8722.19 (81.8)
      BMI, body mass index; PASI, Psoriasis Area and Severity Index; y, years.
      a See list of reference in Appendix D.

      3.2 Risk of bias and publication bias

      Overall, the risk of bias was low or unclear based on random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, reporting bias, and high for incomplete outcome data in one eligible trial (2.4 %; Fig. S1). In one study, we observed a high risk of attrition bias because there was no description of how missing data were handled [
      • Yang H.Z.
      • Wang K.
      • Jin H.Z.
      • Gao T.W.
      • Xiao S.X.
      • Xu J.H.
      • Wang B.X.
      • Zhang F.R.
      • Li C.Y.
      • Liu X.M.
      • Tu C.X.
      • Ji S.Z.
      • Shen Y.
      • Zhu X.J.
      Infliximab monotherapy for Chinese patients with moderate to severe plaque psoriasis: a randomized, double-blind, placebo-controlled multicenter trial.
      ]. However, the table of relevant data in this study was reportedly from the intention-to-treat population, so we assumed that missing data had been handled appropriately and did not adjust our analysis to compensate. Additionally, publication bias in studies reporting PASI75, PASI90 and PASI100 outcomes were visually asymmetric using the comparison-adjusted funnel plots (Fig. S2).

      3.3 Network plots

      Comparisons among the nine different treatments (eight active interventions and placebo) were depicted as network plots for PASI100, 90 and 75 (Fig. 2). The PASI100, PASI90, and PASI75 network were organized by ten, eleven and eleven head-to-head drug comparisons, respectively. The PASI100, PASI90, and PASI75 network included 35 (78 %), 40 (80 %) and 42 (79 %) placebo-controlled studies, respectively (Fig. 2).
      Fig. 2
      Fig. 2Network graph of all eligible comparisons for (A) Psoriasis Area and Severity Index (PASI) 100, (B) PASI90, and (C) PASI75. The size of the nodes and the thickness of the lines are weighted according to the number of patients. Each line connecting 2 nodes indicates a direct comparison. The number above each line indicates the number of studies in that comparison, and the number below each line indicates the total number of patients enrolled into the relevant studies.
      There were three triangular closed loops in each network and all P-values of local inconsistency using loop-specific heterogeneity estimates were >.05 (Fig. S3). We selected the multivariate random effect model because of concern about the heterogeneity of treatment effects. Actually, heterogeneity was not necessarily observed in direct estimates (Table S2). The network evidence showed no significant global inconsistencies, with P-values >.05 for all outcomes (PASI100: P = 0.4623, PASI90: P = 0.1456, PASI75: P = 0.6894). Using forest plots, there was no substantial heterogeneity between the estimates from direct comparisons and the results of the NMA (Fig. S4).

      3.4 Efficacy estimates

      According to the NMA, all biologic agents significantly increased the rate of PASI100, PASI90 and PASI75 achievement rates relative to placebo (Fig. 3 and Fig. S5). The rate of PASI100 and PASI90 achievement with brodalumab was significantly higher than with secukinumab (RD of 0.13 [95 % Confidence intervals (CI) of 0.07–0.19] and 0.10 [0.03–0.18], respectively), infliximab (0.17 [0.07–0.27] and 0.19 [0.10–0.27], respectively), ustekinumab (0.26 [0.21–0.31] and 0.27 [0.21–0.33], respectively) or adalimumab (0.25 [0.20–0.31] and 0.26 [0.19–0.34], respectively). Significantly more patients achieved PASI100 and PASI90 during ixekizumab than during secukinumab (0.08 [0.02–0.15] and 0.09 [0.01–0.17], respectively), infliximab (0.12 [0.02–0.23] and 0.17 [0.09–0.26], respectively), ustekinumab (0.21 [0.16–0.27] and 0.25 [0.19–0.32], respectively) or adalimumab (0.21 [0.15–0.27] and 0.25 [0.17–0.33], respectively). Significantly more patients achieved PASI100 and PASI90 during risankizumab than during secukinumab (0.09 [0.03–0.16] and 0.12 [0.04–0.19], respectively), infliximab (0.13 [0.03–0.24] and 0.20 [0.11–0.29], respectively), ustekinumab (0.22 [0.17–0.28] and 0.28 [0.21–0.35], respectively) or adalimumab (0.22 [0.16–0.28] and 0.27[0.20–0.34], respectively). The rate of PASI100 and PASI90 achievement with guselkumab was significantly higher than with ustekinumab (0.18 [0.12–0.24] and 0.22 [0.15–0.28], respectively) or adalimumab (0.18 [0.12–0.24] and 0.21 [0.14–0.28], respectively). PASI100 and PASI90 achievement rate with secukinumab was significantly higher than with ustekinumab (0.13 [0.08-0.17] and 0.16 [0.11–0.22], respectively) or adalimumab (0.12 [0.07–0.18] and 0.16 [0.09–0.22], respectively). No marked differences in PASI100 or PASI90 achievement rates were noted between brodalumab, ixekizumab, risankizumab and guselkumab, but brodalumab was significantly superior to guselkumab (0.08 [0.01–0.15]) in the PASI100 comparison.
      Fig. 3
      Fig. 3Comparative efficacy according to the network meta-analysis. Leagues tables show: (A) Psoriasis Area and Severity Index (PASI) 100 achievement, (B)PASI90 achievement, and (C) PASI75 achievement. The data in the boxes are risk differences and numbers in parentheses indicate 95 % Confidence intervals. Numbers in bold represent statistically significant comparisons.

      3.5 Ranking estimates

      The cumulative probabilities for achieving PASI100, PASI90 and PASI75, based on SUCRAs of being ranked first to ninth, is shown in the rankogram (Fig. 4A-C). The cumulative probability among the agents was similar for each of the PASI endpoints (PASI100, PASI90 and PASI75) (Fig. 4A-C). The SUCRAs for PASI100, PASI90 and PASI75 achievement were 96.8 %, 86.8 %, and 71.9 %, respectively, with brodalumab; 82.6 %, 90.3 %, and 80.0 %, respectively, with risankizumab; 78.3 %, 80.9 %, and 97.7 %, respectively, with ixekizumab (Fig. 4D). By plotting the SUCRA for PASI100 achievement with that of PASI90, biologics are clustered into three groups: risankizumab – brodalumab – ixekizumab, guselkumab – secukinumab – infliximab, and adalimumab – ustekinumab (Fig. 4E).
      Fig. 4
      Fig. 4The cumulative probabilities for (A) for Psoriasis Area and Severity Index (PASI) 100, (B) PASI90 and (C) PASI75 achievement (D) The mean ranks and the probability of being best strategy are tabulated (higher numbers reflect higher probability of the efficacy). (E) Relationship between surface under the cumulative ranking (SUCRA) for PASI100 and 90 achievements. ADA, adalimumab; BRO, brodalumab; IFX, infliximab; IXE, ixekizumab; GUS, guselkumab; RIS, risankizumab; SEC, secukinumab; UST, ustekinumab.

      4. Discussion

      In this NMA of 41 trials in 19,248 participants with moderate-to-severe plaque psoriasis, three biologic agents – brodalumab, ixekizumab and risankizumab – were associated with higher rates of PASI100 and PASI90 achievement compared with the other biologics during the induction phase of therapy (Week 10–16). Based on the SUCRAs for achieving PASI100, PASI90, the biologics could be categorized into three groups: 1) brodalumab, ixekizumab and risankizumab 2) guselkumab, secukinumab and infliximab, and 3) ustekinumab and adalimumab. It is important to remember that SUCRAs provide an estimate of the likelihood that an agent will be the best treatment; nevertheless, compared with placebo, the agents in category 1 were associated with an incremental improvement in the rate of PASI100 achievement of 30–50 %, PASI90 achievement of ∼70 %, and PASI75 achievement of 80–90 %, according to the risk difference results from this NMA.
      The present NMA evaluated PASI achievement rates based on risk differences, while previous NMAs of biologics for psoriasis reported treatment comparisons based on risk ratios [
      • Geng W.
      • Zhao J.
      • Fu J.
      • Zhang H.
      • Qiao S.
      Efficacy of several biological therapies for treating moderate to severe psoriasis: a network meta-analysis.
      ,
      • Gomez-Garcia F.
      • Epstein D.
      • Isla-Tejera B.
      • Lorente A.
      • Velez Garcia-Nieto A.
      • Ruano J.
      Short-term efficacy and safety of new biological agents targeting the interleukin-23-T helper 17 pathway for moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
      ,
      • Jabbar-Lopez Z.K.
      • Yiu Z.Z.N.
      • Ward V.
      • Exton L.S.
      • Mohd Mustapa M.F.
      • Samarasekera E.
      • Burden A.D.
      • Murphy R.
      • Owen C.M.
      • Parslew R.
      • Venning V.
      • Warren R.B.
      • Smith C.H.
      Quantitative evaluation of biologic therapy options for psoriasis: a systematic review and network meta-analysis.
      ,
      • Loos A.M.
      • Liu S.
      • Segel C.
      • Ollendorf D.A.
      • Pearson S.D.
      • Linder J.A.
      Comparative effectiveness of targeted immunomodulators for the treatment of moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
      ,
      • Sawyer L.M.
      • Cornic L.
      • Levin L.A.
      • Gibbons C.
      • Moller A.H.
      • Jemec G.B.
      Long-term efficacy of novel therapies in moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis of PASI response.
      ,
      • Sbidian E.
      • Chaimani A.
      • Afach S.
      • Doney L.
      • Dressler C.
      • Hua C.
      • Mazaud C.
      • Phan C.
      • Hughes C.
      • Riddle D.
      • Naldi L.
      • Garcia-Doval I.
      • Le Cleach L.
      Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
      ]. In general, it would be difficult to interpret the risk in these analyses since some of the differences in risk ratios compared with placebo exceeded 100-fold; although the comparative risk ratios among agents were not so extremely large [
      • Geng W.
      • Zhao J.
      • Fu J.
      • Zhang H.
      • Qiao S.
      Efficacy of several biological therapies for treating moderate to severe psoriasis: a network meta-analysis.
      ,
      • Gomez-Garcia F.
      • Epstein D.
      • Isla-Tejera B.
      • Lorente A.
      • Velez Garcia-Nieto A.
      • Ruano J.
      Short-term efficacy and safety of new biological agents targeting the interleukin-23-T helper 17 pathway for moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
      ,
      • Jabbar-Lopez Z.K.
      • Yiu Z.Z.N.
      • Ward V.
      • Exton L.S.
      • Mohd Mustapa M.F.
      • Samarasekera E.
      • Burden A.D.
      • Murphy R.
      • Owen C.M.
      • Parslew R.
      • Venning V.
      • Warren R.B.
      • Smith C.H.
      Quantitative evaluation of biologic therapy options for psoriasis: a systematic review and network meta-analysis.
      ,
      • Loos A.M.
      • Liu S.
      • Segel C.
      • Ollendorf D.A.
      • Pearson S.D.
      • Linder J.A.
      Comparative effectiveness of targeted immunomodulators for the treatment of moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
      ,
      • Sawyer L.M.
      • Cornic L.
      • Levin L.A.
      • Gibbons C.
      • Moller A.H.
      • Jemec G.B.
      Long-term efficacy of novel therapies in moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis of PASI response.
      ,
      • Sbidian E.
      • Chaimani A.
      • Afach S.
      • Doney L.
      • Dressler C.
      • Hua C.
      • Mazaud C.
      • Phan C.
      • Hughes C.
      • Riddle D.
      • Naldi L.
      • Garcia-Doval I.
      • Le Cleach L.
      Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
      ]. However, for their clinical interpretability, we adopted risk differences in this NMA. For comparative purposes, we present sensitivity analysis results using risk ratios (Fig. S6). The ranking of the drugs and their statistical significance were a bit changed, e.g., for PASI100, the estimated most efficacious 3 drugs were brodalumab, ixekizumab, risankizumab, and the risk ratio for brodalumab vs ixekizumab was 1.30 (95 %CI 0.82, 2.04), brodalumab vs risankizumab was 1.00 (95 %CI 0.71, 1.39), and risankizumab vs ixekizumab was 0.77 (95 %CI 0.47, 1.27). The small discordance of the results was possibly caused by various complicated mathematical properties of these effect measures [
      • Rothman K.J.
      • Greenland S.
      • Lash T.L.
      Modern Epidemiology.
      ], and it cannot be clearly explained by current methodology of NMA. It should be a relevant methodological issue to be addressed in future methodological studies of NMA. The primary NMA results of this study is justified under the assumption that the statistical model in Section 2 was correct, but it is a substantial limitation of all of NMAs.
      NMAs using PASI90 achievement rates obtained different results to ours in terms of the presence/absence of statistically significant differences in risk ratios, particularly for secukinumab [
      • Loos A.M.
      • Liu S.
      • Segel C.
      • Ollendorf D.A.
      • Pearson S.D.
      • Linder J.A.
      Comparative effectiveness of targeted immunomodulators for the treatment of moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
      ]. In our NMA, brodalumab, ixekizumab and risankizumab were all associated with a significantly greater probability of PASI90 achievement compared with secukinumab, whereas the previous NMAs did not find any significant difference between secukinumab and brodalumab or guselkumab for this outcome [
      • Loos A.M.
      • Liu S.
      • Segel C.
      • Ollendorf D.A.
      • Pearson S.D.
      • Linder J.A.
      Comparative effectiveness of targeted immunomodulators for the treatment of moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
      ]. In addition, the NMA by the Cochrane group calculated the SUCRAs for PASI90 achievement as 0.885 for infliximab, 0.883 for ixekizumab, 0.875 for risankizumab, 0.835 for bimekizumab, 0.810 for guselkumab, 0.754 for secukinumab, 0.687 for brodalumab, concluding that those seven biologics are the best choice for achieving PASI90 [
      • Sbidian E.
      • Chaimani A.
      • Afach S.
      • Doney L.
      • Dressler C.
      • Hua C.
      • Mazaud C.
      • Phan C.
      • Hughes C.
      • Riddle D.
      • Naldi L.
      • Garcia-Doval I.
      • Le Cleach L.
      Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
      ]. Of note, the Cochrane group pooled data from any evaluated dose used in the studies, unlike our analysis in which we focused on licensed doses. In our NMA, although we obtained results for PASI90 similar to the Cochrane analysis, we conclude that ixekizumab, risankizumab and brodalumab are the best choice, considering the inclusion of PASI100. Because our aim was to establish the relative positioning of currently used biologics in terms of PASI achievement, we focused the analysis on the studies of biologics in the patients for whom they are indicated, so we excluded studies where patients received biologics for a non-approved indication (mild psoriasis), and did not include studies with small molecule inhibitors, such as apremilast and tofacitinib.
      Selecting the right biologic for a patient with psoriasis should take into account not only efficacy but also the patient’s condition such as HRQoL improvement, any comorbidities, and convenience or economic burden. In routine clinical practice, physicians may not administer biologics in the same way as they are given in clinical trials. For example, if patients have an insufficient response to adalimumab and infliximab, the dose may be increased or the inter-dose period shortened [
      Japanese Dermatological Association, Japanese Guidance for Use of Biologics for Psoriasis (the 2018 Version).
      ]; therefore, the results of the present analysis may not reflect the comparative treatment effect that can be obtained in clinical practice with some of these biologics. Nevertheless, understanding the comparative effects of the standard doses of these agents may help to guide treatment selection, dose escalation, dose-reduction and switching strategies for biologics in clinical practice. Understanding the long-term efficacy of biologics during maintenance treatment is also important information for decision-making, but was not addressed in this analysis because only 16 trials with long-term outcome were identified at the first screening of the literature search, and this was considered insufficient for conducting a statistically meaningful analysis.
      This study has several limitations. First, because all drugs had been approved within the preceding about three years, the number of head-to-head studies was low. More head-to-head studies would increase the closed-loop in the network plot and therefore provide more accurate estimations in future NMAs. A second limitation of our analysis was that some of newly been approved in Japan, have not been evaluated in this study, and new biologics are being developed. These limitations can be overcome in the future using the same methodology because the NMA can be performed again at any time.
      Finally, our analysis did not include safety endpoints. Recently the British Association of Dermatologists used a set of NMAs (including any evaluated dose rather than focusing on licensed doses) to inform their recommendations and suggest that the efficacy of a biologic agent is not correlated with its safety [
      • Smith C.H.
      • Yiu Z.Z.
      • Bale T.
      • Burden A.D.
      • Coates L.C.
      • Edwards W.
      • MacMahon E.
      • Mahil S.
      • McGuire A.
      • Murphy R.
      • Nelson-Piercy C.
      • Owen C.M.
      • Parslew R.
      • Uthman O.A.
      • Woolf R.T.
      • Manounah L.
      • Ezejimofor M.C.
      • Exton L.S.
      • Mohd M.F.
      • Mustapa U.
      British Association of Dermatologists’ Clinical Standards, British Association of Dermatologists guidelines for biologic therapy for psoriasis 2020 - a rapid update.
      ], i.e., a more effective biologic agent (relative to another) does not have a worse safety profile. One possible explanation for the high rate of early efficacy with these agents would be the role of their target cytokine in the cascade of psoriatic disease formation or the affinity of these drugs to the targeted molecules.
      In summary, this NMA found that the biologics were highly effective in achieving PASI75 and PASI90 improvement relative to placebo during the induction phase of therapy in patients with moderate-to-severe psoriasis. Of the biologics assessed, brodalumab, ixekizumab and risankizumab were associated with the greatest rates of PASI90 and PASI100 achievement at Week 10, Week 12 or Week 16, and a higher probability of being most effective, in the induction phase, compared with the other biologics.

      Author contributions

      Y. Tada supervised the research and manuscript development, had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors contributed to the concept and design of the study, and to the acquisition, analysis, and interpretation of data. Y. Tada, R. Watanabe and H. Noma obtained funding for the research and drafted the manuscript. All authors critically reviewed the manuscript for important intellectual content. The statistical analysis was undertaken by H. Noma and T. Nomura, and H. Noma provided administrative, technical and material support throughout.

      Funding support

      This research and manuscript development was funded by Kyowa Kirin Co., Ltd. Kyowa Kirin consulted with the authors on the design of the meta-analysis, assisted with the literature search, and had the opportunity to review the manuscript prior to submission, but were not involved in the conduct of the study; collection, management, analysis, and interpretation of the data.

      Declaration of Competing Interest

      Y. Tada reports grants and personal fees from Kyowa Kirin, Taiho Pharmaceutical, Novartis Pharma, Eisai, Eli Lilly Japan, Mitsubishi Tanabe Pharma, Maruho, Torii Pharmaceutical, AbbVie, personal fees from Janssen Pharmaceutical, outside the submitted work. R. Watanabe reports personal fees from Abbvie, Eli Lilly Japan, Jenssen Pharmaceutical, Kyowa Kirin, Maruho, Novartis Pharma, Taiho Pharmaceutical, grants from Jenssen Pharmaceutical, outside the submitted work. H. Noma reports personal fees from Kyowa Kirin, during the conduct of the study; personal fees from Boehringer Ingelheim, outside the submitted work. Y. Kanai, T. Nomura and K. Kaneko are employees of Kyowa Kirin.

      Acknowledgements

      The authors would like to thank Ms Ryo Kato of Kyowa Media Service, Co. Ltd., Japan for performing literature search for this study, and Ms Tracy Harrison, of inScience Communications, Springer Healthcare, for preparing the first draft of this manuscript, respectively. Ms Catherine Rees of inScience Communications, Springer Healthcare provided additional writing support. All writing assistance was funded by Kyowa Kirin Co., Ltd. Japan.

      Appendix A. Supplementary data

      References

        • Greb J.E.
        • Goldminz A.M.
        • Elder J.T.
        • Lebwohl M.G.
        • Gladman D.D.
        • Wu J.J.
        • Mehta N.N.
        • Finlay A.Y.
        • Gottlieb A.B.
        Psoriasis.
        Nat. Rev. Dis. Primers. 2016; 2: 16082
        • Parisi R.
        • Symmons D.P.
        • Griffiths C.E.
        • Ashcroft D.M.
        Global epidemiology of psoriasis: a systematic review of incidence and prevalence.
        J. Invest. Dermatol. 2013; 133: 377-385
        • Duvetorp A.
        • Ostergaard M.
        • Skov L.
        • Seifert O.
        • Tveit K.S.
        • Danielsen K.
        • Iversen L.
        Quality of life and contact with healthcare systems among patients with psoriasis and psoriatic arthritis: results from the NORdic PAtient survey of Psoriasis and Psoriatic arthritis (NORPAPP).
        Arch. Dermatol. Res. 2019; 311: 351-360
        • Rapp S.R.
        • Feldman S.R.
        • Exum M.L.
        • Fleischer Jr., A.B.
        • Reboussin D.M.
        Psoriasis causes as much disability as other major medical diseases.
        J. Am. Acad. Dermatol. 1999; 41: 401-407
        • Elewski B.E.
        • Puig L.
        • Mordin M.
        • Gilloteau I.
        • Sherif B.
        • Fox T.
        • Gnanasakthy A.
        • Papavassilis C.
        • Strober B.E.
        Psoriasis patients with psoriasis Area and Severity Index (PASI) 90 response achieve greater health-related quality-of-life improvements than those with PASI 75-89 response: results from two phase 3 studies of secukinumab.
        J. Dermatolog. Treat. 2017; 28: 492-499
        • Blome C.
        • Gosau R.
        • Radtke M.A.
        • Reich K.
        • Rustenbach S.J.
        • Spehr C.
        • Thaci D.
        • Augustin M.
        Patient-relevant treatment goals in psoriasis.
        Arch. Dermatol. Res. 2016; 308: 69-78
        • Jansen J.P.
        • Fleurence R.
        • Devine B.
        • Itzler R.
        • Barrett A.
        • Hawkins N.
        • Lee K.
        • Boersma C.
        • Annemans L.
        • Cappelleri J.C.
        Interpreting indirect treatment comparisons and network meta-analysis for health-care decision making: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 1.
        Value Health. 2011; 14: 417-428
        • Higgins J.P.
        • Altman D.G.
        • Gotzsche P.C.
        • Juni P.
        • Moher D.
        • Oxman A.D.
        • Savovic J.
        • Schulz K.F.
        • Weeks L.
        • Sterne J.A.
        The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials.
        BMJ. 2011; 343: d5928
        • Salanti G.
        Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool.
        Res. Synth. Methods. 2012; 3: 80-97
        • DerSimonian R.
        • Larid N.M.
        Meta-analysis in clinical trials.
        Control. Clin. Trials. 1986; 7: 177-188
        • Salanti G.
        • Higgins J.P.
        • Ades A.E.
        • Ioannidis J.P.
        Evaluation of networks of randomized trials.
        Stat. Methods Med. Res. 2008; 17: 279-301
        • White I.R.
        • Barrett J.K.
        • Jackson D.
        • Higgins J.P.
        Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression.
        Res. Synth. Methods. 2012; 3: 111-125
        • Hutton B.
        • Salanti G.
        • Caldwell D.M.
        • Chaimani A.
        • Schmid C.H.
        • Cameron C.
        • Ioannidis J.P.
        • Straus S.
        • Thorlund K.
        • Jansen J.P.
        • Mulrow C.
        • Catala-Lopez F.
        • Gotzsche P.C.
        • Dickersin K.
        • Boutron I.
        • Altman D.G.
        • Moher D.
        The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations.
        Ann. Intern. Med. 2015; 162: 777-784
        • Bucher H.C.
        • Guyatt G.H.
        • Griffith L.E.
        • Walter S.D.
        The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials.
        J. Clin. Epidemiol. 1997; 50: 683-691
        • Higgins J.P.
        • Jackson D.
        • Barrett J.K.
        • Lu G.
        • Ades A.E.
        • White I.R.
        Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies.
        Res. Synth. Methods. 2012; 3: 98-110
        • Yang H.Z.
        • Wang K.
        • Jin H.Z.
        • Gao T.W.
        • Xiao S.X.
        • Xu J.H.
        • Wang B.X.
        • Zhang F.R.
        • Li C.Y.
        • Liu X.M.
        • Tu C.X.
        • Ji S.Z.
        • Shen Y.
        • Zhu X.J.
        Infliximab monotherapy for Chinese patients with moderate to severe plaque psoriasis: a randomized, double-blind, placebo-controlled multicenter trial.
        Chin Med J (Engl). 2012; 125: 1845-1851
        • Geng W.
        • Zhao J.
        • Fu J.
        • Zhang H.
        • Qiao S.
        Efficacy of several biological therapies for treating moderate to severe psoriasis: a network meta-analysis.
        Exp. Ther. Med. 2018; 16: 5085-5095
        • Gomez-Garcia F.
        • Epstein D.
        • Isla-Tejera B.
        • Lorente A.
        • Velez Garcia-Nieto A.
        • Ruano J.
        Short-term efficacy and safety of new biological agents targeting the interleukin-23-T helper 17 pathway for moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
        Br. J. Dermatol. 2017; 176: 594-603
        • Jabbar-Lopez Z.K.
        • Yiu Z.Z.N.
        • Ward V.
        • Exton L.S.
        • Mohd Mustapa M.F.
        • Samarasekera E.
        • Burden A.D.
        • Murphy R.
        • Owen C.M.
        • Parslew R.
        • Venning V.
        • Warren R.B.
        • Smith C.H.
        Quantitative evaluation of biologic therapy options for psoriasis: a systematic review and network meta-analysis.
        J. Invest. Dermatol. 2017; 137: 1646-1654
        • Loos A.M.
        • Liu S.
        • Segel C.
        • Ollendorf D.A.
        • Pearson S.D.
        • Linder J.A.
        Comparative effectiveness of targeted immunomodulators for the treatment of moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis.
        J. Am. Acad. Dermatol. 2018; 79135-144.e7
        • Sawyer L.M.
        • Cornic L.
        • Levin L.A.
        • Gibbons C.
        • Moller A.H.
        • Jemec G.B.
        Long-term efficacy of novel therapies in moderate-to-severe plaque psoriasis: a systematic review and network meta-analysis of PASI response.
        J. Eur. Acad. Dermatol. Venereol. 2019; 33: 355-366
        • Sbidian E.
        • Chaimani A.
        • Afach S.
        • Doney L.
        • Dressler C.
        • Hua C.
        • Mazaud C.
        • Phan C.
        • Hughes C.
        • Riddle D.
        • Naldi L.
        • Garcia-Doval I.
        • Le Cleach L.
        Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.
        Cochrane Database Syst. Rev. 2020; 1CD011535
        • Rothman K.J.
        • Greenland S.
        • Lash T.L.
        Modern Epidemiology.
        3rd ed. Wolters Kluwer Health/Lippincott Williams & Wilkins, Philadelphia2008
      1. Japanese Dermatological Association, Japanese Guidance for Use of Biologics for Psoriasis (the 2018 Version).
        2018 (Accessed 23 April 2019)
        • Smith C.H.
        • Yiu Z.Z.
        • Bale T.
        • Burden A.D.
        • Coates L.C.
        • Edwards W.
        • MacMahon E.
        • Mahil S.
        • McGuire A.
        • Murphy R.
        • Nelson-Piercy C.
        • Owen C.M.
        • Parslew R.
        • Uthman O.A.
        • Woolf R.T.
        • Manounah L.
        • Ezejimofor M.C.
        • Exton L.S.
        • Mohd M.F.
        • Mustapa U.
        British Association of Dermatologists’ Clinical Standards, British Association of Dermatologists guidelines for biologic therapy for psoriasis 2020 - a rapid update.
        Br. J. Dermatol. 2020;