Global Guidelines in Dermatology Mapping Project (GUIDEMAP): a scoping review of dermatology clinical practice guidelines.

BACKGROUND: Clinical practice guidelines (CPGs) play a critical role in standardizing and improving treatment outcomes based on the available evidence. It is unclear how many CPGs are available globally to assist clinicians in the management of patients with skin disease. OBJECTIVES: To search for and identify CPGs for dermatological conditions with the highest burden globally. METHODS: We adapted a list of 12 dermatological conditions with the highest burden from the Global Burden of Disease (GBD) study 2019. A systematic literature search was done to identify CPGs published between October 2014 to October 2019. The scoping review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. RESULTS: A total of 226 CPGs were included. Melanoma had the greatest representation in the CPGs, followed by dermatitis and psoriasis. Skin cancers had a relatively high CPG representation but with lower GBD disease burden ranking. There was an uneven distribution by geographical region, with resource-poor settings being under-represented. The skin disease categories of the CPGs correlated weakly with the GBD disability-adjusted life-years metrics. Eighty-nine CPGs did not have funding disclosures and 34 CPGs were behind a paywall. CONCLUSIONS: The global production of dermatology CPGs showed wide variation in geographical representation, article accessibility and reporting of funding. The number of skin disease CPGs were not commensurate with its disease burden. Future work will critically appraise the methodology and quality of dermatology CPGs and lead to the production of an accessible online resource summarizing these findings.

Comparing the efficacy and tolerability of biologic therapies in psoriasis: an updated network meta-analysis.

BACKGROUND: The rapid expansion of psoriasis biologics has led to an urgent need to understand their relative efficacy and tolerability to inform treatment decisions better and, specifically, to inform guideline development. OBJECTIVES: To update a 2017 meta-analysis on the comparative efficacy and tolerability of biologic treatments for psoriasis. METHODS: We searched the MEDLINE, PubMed, Embase and Cochrane databases for randomized controlled trials (RCTs), published up to 7 September 2018, of 11 licensed, NICE-approved biologics targeting tumour necrosis factor (adalimumab, etanercept, infliximab, certolizumab pegol), interleukin (IL)-12/IL-23p40 (ustekinumab), IL-17A (secukinumab, ixekizumab), IL-17RA (brodalumab) and IL-23p19 (guselkumab, tildrakizumab, risankizumab). A frequentist network meta-analysis ascertained direct or indirect evidence comparing biologics with one another, methotrexate or placebo. This was combined with hierarchical cluster analyses to consider efficacy (≥ 90% improvement in Psoriasis Area and Severity Index (PASI 90) or Physician's Global Assessment 0 or 1; PASI 75; Dermatology Life Quality Index improvement) and tolerability (drug withdrawal due to adverse events) outcomes at 10-16 weeks, followed by assessments of study quality, heterogeneity and inconsistency. RESULTS: We identified 62 RCTs presenting data on direct comparisons (31 899 participants). All biologics were efficacious compared with placebo or methotrexate at 10-16 weeks. Hierarchical cluster analyses revealed that adalimumab, brodalumab, certolizumab pegol, guselkumab, risankizumab, secukinumab, tildrakizumab and ustekinumab were comparable with respect to high short-term efficacy and tolerability. Infliximab and ixekizumab clustered together, with high short-term efficacy but relatively lower tolerability than the other agents, although the number of drug withdrawal events across the network was low, so these findings should be treated with caution. CONCLUSIONS: Using our methodology we found that most biologics cluster together with respect to short-term efficacy and tolerability, and we did not identify any single agent as 'best'. These data need to be interpreted in the context of longer-term efficacy, effectiveness data, safety, posology and drug acquisition costs when making treatment decisions.