Patient preferences for stratified medicine in psoriasis: a discrete choice experiment

From Wiley via Jisc Publications RouterHistory: accepted 2021-05-13, pub-electronic 2021-07-29Article version: VoRPublication status: PublishedFunder: Riksbanken Jubileumsfond; Id: http://dx.doi.org/10.13039/501100004472Funder: Medical Research Council; Id: http://dx.doi.org/10.13039/501100000265; Grant(s): MR/L011808/1Summary: Background: New technologies have enabled the potential for stratified medicine in psoriasis. It is important to understand patients’ preferences to enable the informed introduction of stratified medicine, which is likely to involve a number of individual tests that could be collated into a prescribing algorithm for biological drug selection to be used in clinical practice. Objectives: To quantify patient preferences for an algorithm‐based approach to prescribing biologics (‘biologic calculator’) in psoriasis. Methods: An online survey comprising a discrete choice experiment (DCE) was conducted to elicit the preferences of two purposive samples of adults living with psoriasis in the UK, identified from a psoriasis patient organization (Psoriasis Association) and an online panel provider (Dynata). Respondents chose between two biologic calculators and conventional prescribing described using five attributes: treatment delay; positive predictive value; negative predictive value; risk of infection; and cost saving to the National Health Service. Each participant selected their preferred alternative from six hypothetical choice sets. Additional data, including sociodemographic characteristics, were collected. Choice data were analysed using conditional logit and fully correlated random parameters logit models. Results: Data from 212 respondents (67 from the Psoriasis Association and 145 from Dynata) were analysed. The signs of all estimated coefficients were consistent with a priori expectations. Respondents had a strong preference for a high predictive accuracy and avoiding serious infection, but there was evidence of systematic differences in preferences between the samples. Conclusions: This study indicates that individuals with psoriasis would value a biologic calculator and suggested that such a biologic calculator should have sufficient accuracy to predict future response and risk of serious infection from the biologic

Using Real-World Data to Guide Ustekinumab Dosing Strategies for Psoriasis: A Prospective Pharmacokinetic-Pharmacodynamic Study.

Variation in response to biologic therapy for inflammatory diseases, such as psoriasis, is partly driven by variation in drug exposure. Real-world psoriasis data were used to develop a pharmacokinetic/pharmacodynamic (PK/PD) model for the first-line therapeutic antibody ustekinumab. The impact of differing dosing strategies on response was explored. Data were collected from a UK prospective multicenter observational cohort (491 patients on ustekinumab monotherapy, drug levels, and anti-drug antibody measurements on 797 serum samples, 1,590 measurements of Psoriasis Area Severity Index (PASI)). Ustekinumab PKs were described with a linear one-compartment model. A maximum effect (Emax ) model inhibited progression of psoriatic skin lesions in the turnover PD mechanism describing PASI evolution while on treatment. A mixture model on half-maximal effective concentration identified a potential nonresponder group, with simulations suggesting that, in future, the model could be incorporated into a Bayesian therapeutic drug monitoring "dashboard" to individualize dosing and improve treatment outcomes

Author Correction: Enhanced NF-κB signaling in type-2 dendritic cells at baseline predicts non-response to adalimumab in psoriasis.

Funder: Department of HealthBiologic therapies have transformed the management of psoriasis, but clinical outcome is variable leaving an unmet clinical need for predictive biomarkers of response. Here we perform in-depth immunomonitoring of blood immune cells of 67 patients with psoriasis, before and during therapy with the anti-TNF drug adalimumab, to identify immune mediators of clinical response and evaluate their predictive value. Enhanced NF-κBp65 phosphorylation, induced by TNF and LPS in type-2 dendritic cells (DC) before therapy, significantly correlates with lack of clinical response after 12 weeks of treatment. The heightened NF-κB activation is linked to increased DC maturation in vitro and frequency of IL-17+ T cells in the blood of non-responders before therapy. Moreover, lesional skin of non-responders contains higher numbers of dermal DC expressing the maturation marker CD83 and producing IL-23, and increased numbers of IL-17+ T cells. Finally, we identify and clinically validate LPS-induced NF-κBp65 phosphorylation before therapy as a predictive biomarker of non-response to adalimumab, with 100% sensitivity and 90.1% specificity in an independent cohort. Our study uncovers important molecular and cellular mediators underpinning adalimumab mechanisms of action in psoriasis and we propose a blood biomarker for predicting clinical outcome

Defining the therapeutic range for adalimumab and predicting response in psoriasis: a multicenter prospective observational cohort study

Biologics have transformed management of inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by circulating drug levels has been proposed. We aimed to determine the real-world clinical utility of therapeutic drug monitoring in psoriasis. Within a multicenter (n=60) prospective observational cohort, 544 psoriasis patients were included who were on adalimumab monotherapy, with at least one serum sample and PASI (Psoriasis Area and Severity Index) score available within the first year. We present models giving individualized probabilities of response for any given drug level: a minimally effective drug level of 3.2 μg/ml discriminates responders (PASI75: 75% improvement in baseline PASI) from non-responders and gives an estimated PASI75 probability of 65% (95% CI 60-71%). At 7ug/ml, PASI75 probability is 81% (95% CI 76-86%); beyond 7ug/ml, the drug level/response curve plateaus. Crucially, drug levels are predictive of response 6 months later, whether sampled early or at steady state. We confirm serum drug level to be the most important factor determining treatment response, highlighting the need to take drug levels into account when searching for biomarkers of response. This real-world study with pragmatic drug level sampling provides evidence to support the proactive measurement of adalimumab levels in psoriasis to direct treatment strategy, and is relevant to other inflammatory diseases

Defining trajectories of response in patients with psoriasis treated with biologic therapies

From Wiley via Jisc Publications RouterHistory: accepted 2021-04-03, pub-electronic 2021-06-04Article version: VoRPublication status: PublishedFunder: Medical Research Council; Id: http://dx.doi.org/10.13039/501100000265; Grant(s): MR/K006665/1, MR/L011808/1, MR/N00583X/1Summary: Background: The effectiveness and cost‐effectiveness of biologic therapies for psoriasis are significantly compromised by variable treatment responses. Thus, more precise management of psoriasis is needed. Objectives: To identify subgroups of patients with psoriasis treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management. Methods: We applied latent class mixed modelling to identify trajectory‐based patient subgroups from longitudinal, routine clinical data on disease severity, as measured by the Psoriasis Area and Severity Index (PASI), from 3546 patients in the British Association of Dermatologists Biologics and Immunomodulators Register, as well as in an independent cohort of 2889 patients pooled across four clinical trials. Results: We discovered four discrete classes of global response trajectories, each characterized in terms of time to response, size of effect and relapse. Each class was associated with differing clinical characteristics, e.g. body mass index, baseline PASI and prevalence of different manifestations. The results were verified in a second cohort of clinical trial participants, where similar trajectories following the initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA‐C*06:02 between our registry‐identified trajectories. Conclusions: These subgroups, defined by change in disease over time, may be indicative of distinct endotypes driven by different biological mechanisms and may help inform the management of patients with psoriasis. Future work will aim to further delineate these mechanisms by extensively characterizing the subgroups with additional molecular and pharmacological data

Meeting Report: Psoriasis Stratification to Optimize Relevant Therapy Showcase

Meeting Repor

Identifying demographic, social and clinical predictors of biologic therapy effectiveness in psoriasis: a multicentre longitudinal cohort study

Background: Biologic therapies have revolutionized the treatment of moderate-to-severe psoriasis. However, for reasons largely unknown, many patients do not respond or lose response to these drugs. Objectives: To evaluate demographic, social and clinical factors that could be used to predict effectiveness and stratify response to biologic therapies in psoriasis. Methods: Using a multicentre, observational, prospective pharmacovigilance study (BADBIR), we identified biologic-naive patients starting biologics with outcome data at 6 (n = 3079) and 12 (n = 3110) months. Associations between 31 putative predictors and outcomes were investigated in univariate and multivariable regression analyses. Potential stratifiers of treatment response were investigated with statistical interactions. Results: Eight factors associated with reduced odds of achieving ≥ 90% improvement in Psoriasis Area and Severity Index (PASI 90) at 6 months were identified (described as odds ratio and 95% confidence interval): demographic (female sex, 0·78, 0·66–0·93); social (unemployment, 0·67, 0·45–0·99); unemployment due to ill health (0·62, 0·48–0·82); ex- and current smoking (0·81, 0·66–0·99 and 0·79, 0·63–0·99, respectively); clinical factors (high weight, 0·99, 0·99–0·99); psoriasis of the palms and/or soles (0·75, 0·61–0·91); and presence of small plaques only compared with small and large plaques (0·78, 0·62–0·96). White ethnicity (1·48, 1·12–1·97) and higher baseline PASI (1·04, 1·03–1·04) were associated with increased odds of achieving PASI 90. The findings were largely consistent at 12 months. There was little evidence for predictors of differential treatment response. Conclusions: Psoriasis phenotype and potentially modifiable factors are associated with poor outcomes with biologics, underscoring the need for lifestyle management. Effect sizes suggest that these factors alone cannot inform treatment selection

Interleukin-23-induced STAT3 translocation in circulating mucosal-associated invariant T cells is a potential biomarker of clinical response to ustekinumab in psoriasis

Meeting Abstrac