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  ["project_date_type"]=>
  string(91) "Individual Participant-Level Data, which includes Full CSR and all supporting documentation"
  ["property_scientific_abstract"]=>
  string(2192) "Background

Psoriasis is a frequent immune-mediated disease with either skin or joint manifestations, which has a major impact on quality of life. Although there is no cure for psoriasis, various treatment strategies allow sustained control of disease signs and symptoms. Although a living Cochrane systematic review and network meta-analysis (NMA) has been conducted on the efficacy and safety of systemic treatments (STs) for people with moderate-to-severe psoriasis, there is no NMA on individual data to date.1 In daily practice, choosing the best intervention option for a given patient is a challenging question and depends on whether or not prognostic factors of drug persistence rate (sex, weight, comorbidities, previous treatment lines). Thus, an Individual Patient Data (IPD) NMA is required to compare the efficacy and the safety of STs for psoriasis, using all available evidence from randomized trials to conduct a valid comparison between drugs and help clinicians to choose the better drug for a given patient. 

Objective

To compare the efficacy and safety of STs for people with moderate-to-severe psoriasis and provide a ranking of these STs according to their efficacy and safety by conducting NMAs. To identify factors that may predict which participant would respond best to an intervention.

Study design

Randomized controlled trials of phase II, III, or IV. 

Participants

Adults (over 18 years of age) with moderate-to-severe plaque psoriasis (i.e., needed systemic treatment) and who were at any stage of treatment.

Main Outcome Measures

The proportion of participants who achieved clear or almost clear skin, at least psoriasis area and severity index 90 and with serious adverse events at induction phase (less than 24 weeks).

Statistical Analysis

We will analyze dichotomous data as odds ratios with 95% confidence intervals (CIs) and continuous outcomes as standardized mean differences with 95% CIs. We will combine IPD and aggregated data using the two?stage method. An NMA using all available IPD and aggregate data from trials that do not provide IPD will be our primary analysis for each outcome"
  ["project_brief_bg"]=>
  string(2753) "Psoriasis is a frequent immune-mediated disease with either skin or joint manifestations, or both, which 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.

In that context, we performed a living Cochrane systematic review and network meta-analysis (NMA) to compare the efficacy and safety of non-biological systemic agents, small molecules, and biologics for people with moderate-to-severe psoriasis (a total of 20 interventions), and to provide a ranking of these treatments according to their efficacy and safety.1 A NMA allows for the best use of available direct and indirect information to determine the relative efficacy of treatments. In other words, a NMA identifies missing head-to-head comparisons that are necessary to guide clinical practice. Our review, including 158 randomised controlled trials (57,831 patients) and 133 RCTs in the NMA showed that compared to placebo, some biologics infliximab (TNF inhibitors), bimekizumab (IL23 inhibitors), ixekizumab (IL17 inhibitors), and risankizumab (IL23 inhibitors) were the most effective treatments for achieving clearance or almost clearance of psoriasis in people with moderate-to-severe disease based on high-certainty evidence. However, as this NMA used aggregated data, subgroups analyses were not possible.

In daily practice, choosing the best intervention option for a given patient is a challenging question and depends on the presence or not of a psoriatic arthritis, on patient's co-morbidities or patient's previous systemic treatment lines. Some of these characteristics were identified as prognostic factors of drug persistence rate (sex, weight, co-morbidities, previous treatment lines).

Thus, an Individual Patient Data (IPD) NMA is required to compare the efficacy and the safety of systemic interventions for psoriasis, using all available evidence from randomized trials to conduct a valid comparison between drugs and to help clinicians to choose the better drug for a given patient.

For IPD, we requested IPD through http://vivli.org.  and https://www.clinicalstudydatarequest.com and we contacted the pharmaceutical companies which market the following systemic treatments:

Systemic non-biological treatments: Fumaric acid esters, Acitretin, Ciclosporin, Methotrexate

Small molecules: Apremilast, deucravacitinib

Anti-TNF alpha: Infliximab, Etanercept, Adalimumab, Certolizumab

Anti-IL12/23: Ustekinumab

Anti-IL17: Secukinumab, Brodalumab, Ixekizumab, Bimekizumab

Anti-IL23: Tildrakizumab, Guselkumab, Risankizumab

All the identified studies are detailed in the supplemental table."
  ["project_specific_aims"]=>
  string(320) "To compare the efficacy and safety of systemic treatments for people with moderate-to-severe psoriasis and provide a ranking of these treatments according to their efficacy and safety by conducting network meta-analyses.

To identify factors that may predict which participant would respond best to an intervention."
  ["project_study_design"]=>
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  ["project_purposes"]=>
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    [0]=>
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      ["value"]=>
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      ["label"]=>
      string(114) "New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations"
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    [1]=>
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      ["value"]=>
      string(76) "Confirm or validate previously conducted research on treatment effectiveness"
      ["label"]=>
      string(76) "Confirm or validate previously conducted research on treatment effectiveness"
    }
    [2]=>
    array(2) {
      ["value"]=>
      string(69) "Confirm or validate previously conducted research on treatment safety"
      ["label"]=>
      string(69) "Confirm or validate previously conducted research on treatment safety"
    }
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      ["value"]=>
      string(36) "Participant-level data meta-analysis"
      ["label"]=>
      string(36) "Participant-level data meta-analysis"
    }
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      ["value"]=>
      string(69) "Meta-analysis using data from the YODA Project and other data sources"
      ["label"]=>
      string(69) "Meta-analysis using data from the YODA Project and other data sources"
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      ["label"]=>
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  string(877) "Data source

We will select all randomized controlled trials (RCTs) from the most version of the living Cochrane review and network meta-analysis of chronic plaque psoriasis evaluating a systemic treatment (biologic, non-biologic, and small-molecule).1 

Inclusion/Exclusion criteria

We will include RCTs of phases II, III, or IV including adults (over 18 years of age) with moderate-to-severe plaque psoriasis (i.e., needed systemic treatment) who were at any stage of treatment. 

Phase I trials will not be eligible because participants, outcomes, dosages, and schema of administration of interventions are too different from phase II, III, and IV studies. Cross-over trials will be not eligible (because of the unpredictable evolution of psoriasis and risk of carry-over bias). Non-randomized studies, including follow-up studies, will be not eligible."
  ["project_main_outcome_measure"]=>
  string(732) "The main outcome measures will be :

- The proportion of participants who achieved clear or almost clear skin, that is, at least PASI 90 at induction phase (less than 24 weeks). It will be categorized as a dichotomous variable.

- The proportion of participants with serious adverse events (SAEs) at induction phase. It will be categorized as a dichotomous variable.

These two outcomes will be categorized as dichotomous variables and analyzed as odds ratios (ORs) with 95% confidence intervals (CIs).

For continuous outcomes (Quality of life as a secondary outcome measure), standardised mean difference (SMD) with 95% CIs will be calculated because different scales of patient-reported outcomes are expected."
  ["project_main_predictor_indep"]=>
  string(1186) "For each study, the clinical predictors that will be examined in this study are: duration of psoriasis (years, continuous variable), severity of psoriasis (PASI from 0 to 72, body surface index(%), physician global assessment from 0 to 5, as continuous variable), the presence of co-morbidities or no (hypertension, diabetes, dyslipidemia, previous history of stroke, myocardial infarction, viral B or C hepatitis, kidney failure, chronic obstructive pulmonary disease, smoking status, personal history of malignancy, alcohol use, past history of cancer, psoriatic arthritis, inflammatory rheumatism, chronic inflammatory bowel disorder, dichotomous variable) and previous exposure to psoriasis treatment [methotrexate, ciclosporin, acitretin, phototherapy, biologics (which one), dichotomous variable].

Demographic moderators that will be examined in this study are: sex (dichotomous variable); ethnicity; age (years), body weight (Kg), and body mass index (Kg/m2), all continuous variables.

For dichotomous variables, odds ratios with 95% confidence intervals (CIs) will be calculated. For continuous outcomes, standardised mean difference with 95% CIs will be calculated."
  ["project_other_variables_interest"]=>
  string(1233) "- Proportion of participants who achieve PASI 75 at induction phase (dichotomous variable).

- Proportion of participants who achieve PASI 75 and PASI 90 during the maintenance phase (from 44 to 60 weeks) (dichotomous variable).

- Quality of life measured by Dermatology Life Quality Index (DLQI), Skindex, Psoriasis Disability Index (PDI), or Psoriasis Symptom Inventory (PSI) at induction phase (continuous variable).

- Proportions of participants with adverse events (AEs) of interest at induction phase and maintenance phase (dichotomous variables):

?	Number of Major Adverse Cardiovascular Events (MACEs) (nonfatal stroke, nonfatal myocardial infarction or cardiovascular death),

?	Number of serious infections (any infection meeting the regulatory definition of a SAE)

?	Number of malignancies excluding non-melanoma skin cancer (NMSC) and carcinoma in situ of the cervix,

?	Number of NMSC and carcinoma in situ of the cervix,

?	Number of cases of inflammatory bowel diseases, psychiatric disorders (depression, suicidal ideation behavior; neurotic, stress-related, or somatoform disorders; and personality and behavioral disorders), renal and hepatic injury, bone marrow toxicity"
  ["project_stat_analysis_plan"]=>
  string(4044) "Unit of analysis issues

The primary unit of analysis will be the participant. We will treat comparisons from studies with multiple intervention groups as independent two-arm studies in the pairwise meta-analyses (MAs). At the NMA stage, we will account for the within-study correlation.

Missing data

The percentage of individual participant missing data (baseline characteristics, event status and time to event or censoring) will be recorded for each study. We will apply multiple imputation for missing data and perform a sensitivity analysis using imputed and completed data.

Assessment of heterogeneity

We will undertake MAs only if we judge participants, interventions, comparisons, and outcomes to be sufficiently similar. In the classical MA, we will assess statistical heterogeneity by visual inspection of the forest plots and using the Q-test and the I2 statistic. In the NMA, the assessment of statistical heterogeneity in the entire network will be based on the estimated heterogeneity variance parameter (tau) estimated from the NMA models. We will estimate the prediction intervals to assess how much the estimated heterogeneity affects the relative effects concerning the additional uncertainly anticipated in future studies. We will investigate the possible sources if heterogeneity is detected by conducting subgroup analyses and meta-regression.

Assessment of reporting biases

We will use a 'comparison-adjusted funnel plot' to assess reporting biases for all comparisons of an active treatment against a placebo. If substantial funnel plot asymmetry is detected, we will investigate small study-effects in the network meta-regression.

Data synthesis

We will combine IPD and aggregated data for all outcomes using the two?stage method.2,3 When IPD is available, we will calculate the outcome measure using appropriate logistic regression models. For studies where IPD are not available, we will use the aggregate outcome measure provided in the pertinent publication, if available. We will perform all MAs using R, as only pairwise analyses are implemented in Review Manager 5.4. We will use a frequentist random?effects model because we expect non?explainable heterogeneity.

Pairwise MA

We will perform pairwise random?effects MAs for all outcomes within a frequentist framework at the trial level. Each pairwise meta?analytical comparison will be restricted to the corresponding trial results irrespective of whether a third treatment arm was investigated. Where IPD are available, we will calculate the outcome measures from the provided data. The analyses will be performed according to the intention?to?treat principle. For studies where IPD are unavailable, we will use the aggregated outcome measures provided in the pertinent publication. Pooled effect sizes will be estimated from the mean or median of the posterior distribution. We will estimate 95% credibility intervals from the 2.5th and 97.5th percentiles of the highest posterior density interval; not necessarily be symmetric.

NMA using IPD and aggregate data

An NMA using all available IPD and aggregate data from trials that do not provide IPD will be our primary analysis for each outcome. As for conventional pairwise MA, IPD is preferred over aggregate data from all included studies in an NMA.  In sensitivity analyses, to examine the overall effects of the interventions compared with control and assess the modifying effect of study and individual-level variables on prognostic and predictive value, we will also conduct one-stage random-effects IPD MAs. Subgroups of analysis will be performed depending on sex, age, ethnicity, presence of psoriatic arthritis or not, previous systemic treatment lines, and comorbidities.

All work on participant-level will take place within the YODA platform. We will not exporte participant-level from the platform. We will export summary representation of data and will combine these summary level results outside of the platform."
  ["project_timeline"]=>
  string(407) "The project's start date will begin as soon as we have the results, i.e., the 3rd quarter of 2022. Data curation will be completed 2nd quarter of 2023. The completion date of the analysis will be the end of 2023. We will get the final results the 1st quarter of 2024. Then we will start writing the manuscript in the 2nd quarter of 2024, with the first submission for publication in the 3rd quarter of 2024."
  ["project_dissemination_plan"]=>
  string(740) "The use of individual participant data enabled us to identify prognostic factors and effect modifiers and thereby estimate the relative personalized effects between different interventions, depending on individual patient characteristics. This information may be important for clinical practice, considering the changes in psoriasis treatment strategies and the increasing number of available treatments.

We aim to publish these results in a general journal (e.g., the British Medical Journal (BMJ)) because of the frequency of psoriasis in the general population and the high impact of the expected results on international guidelines for psoriasis. The target audience is physicians, guideline developers, and patient organizations."
  ["project_bibliography"]=>
  string(613) "
1	Sbidian E, Chaimani A, Garcia-Doval I, et al. Systemic pharmacological treatments for chronic plaque psoriasis: a network meta?analysis. Cochrane Database Syst Rev 2021. doi:10.1002/14651858.CD011535.pub4.

2	Burke DL, Ensor J, Riley RD. Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ. Stat Med 2017; 36:855?75.

3	Riley RD, Simmonds MC, Look MP. Evidence synthesis combining individual patient data and aggregate data: a systematic review identified current practice and possible methods. J Clin Epidemiol 2007; 60:431.e1-431.e12.
"
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data partner
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pi country
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pi affil
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products
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num of trials
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res
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