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

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

Establishing an academic–industrial stratified medicine consortium: psoriasis stratification to optimize relevant therapy

No abstract available

Clinical Impact of Antibodies against Ustekinumab in Psoriasis: An Observational, Cross-Sectional, Multicenter Study

Ustekinumab is an effective treatment for psoriasis, but response varies between patients. The formation of anti-drug antibodies (ADAs) may explain part of this variation by reducing the free ustekinumab level. Currently, published analyses of the clinical impact of ADAs are incomplete. In this observational cross-sectional multicenter study of 340 patients, we evaluated the impact of ADAs on ustekinumab level and clinical response as assessed by the PASI. Circulating ADA levels were measured using two assays: a drug-sensitive radioimmunoassay and a drug-tolerant ELISA. Circulating ustekinumab levels were measured using an ELISA. ADAs were detected in 3.8% (95% confidence interval [CI] = 3.2–4.2) and in 10.6% (95% CI = 7.9–13.9) of patients using the radioimmunoassay and drug-tolerant ELISA, respectively. At least 85% of the ADAs were neutralizing. Compared with patients negative for ADAs, ADA positivity in the radioimmunoassay and drug-tolerant ELISA were associated with lower median ustekinumab levels (−0.62 μg/ml [95% CI = −1.190 to −0.30] and −0.74 μg/ml [95% CI = −1.09 to −0.47], respectively) and higher absolute PASI (6.6 [95% CI = 3.0–9.9] and 1.9 [95% CI = 0.4–4.0], respectively). Absence of detectable ustekinumab regardless of ADA status correlated with poor clinical outcome (median sample PASI 10.1, 6.5 [95% CI = 3.9–8.8] compared with patients positive for ustekinumab). In conclusion, substantially reduced drug exposure resulting from ADAs formation is associated with impaired clinical response

HLA-C*06:02 genotype is a predictive biomarker of biologic treatment response in psoriasis

Background: Biologic therapies can be highly effective for the treatment of severe psoriasis, but response for individual patients can vary according to drug. Predictive biomarkers to guide treatment selection could improve patient outcomes and treatment cost-effectiveness. Objective: We sought to test whether HLA-C*06:02, the primary genetic susceptibility allele for psoriasis, predisposes patients to respond differently to the 2 most commonly prescribed biologics for psoriasis: adalimumab (anti–TNF-α) and ustekinumab (anti–IL-12/23). Methods: This study uses a national psoriasis registry that includes longitudinal treatment and response observations and detailed clinical data. HLA alleles were imputed from genome-wide genotype data for 1326 patients for whom 90% reduction in Psoriasis Area and Severity Index score (PASI90) response status was observed after 3, 6, or 12 months of treatment. We developed regression models of PASI90 response, examining the interaction between HLA-C*06:02 and drug type (adalimumab or ustekinumab) while accounting for potentially confounding clinical variables. Results: HLA-C*06:02–negative patients were significantly more likely to respond to adalimumab than ustekinumab at all time points (most strongly at 6 months: odds ratio [OR], 2.95; P = 5.85 × 10−7), and the difference was greater in HLA-C*06:02–negative patients with psoriatic arthritis (OR, 5.98; P = 6.89 × 10−5). Biologic-naive patients who were HLA-C*06:02 positive and psoriatic arthritis negative demonstrated significantly poorer response to adalimumab at 12 months (OR, 0.31; P = 3.42 × 10−4). Results from HLA-wide analyses were consistent with HLA-C*06:02 itself being the primary effect allele. We found no evidence for genetic interaction between HLA-C*06:02 and ERAP1. Conclusion: This large observational study suggests that reference to HLA-C*06:02 status could offer substantial clinical benefit when selecting treatments for severe psoriasis