The use of psoriasis biomarkers, including trajectory of clinical response, to predict clearance and remission duration to UVB phototherapy

Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study

BACKGROUND

Identifying the risk of psoriasis relapse after discontinuing biologics can help optimize treatment strategies, potentially reducing relapse rates and alleviating the burden of disease management.

OBJECTIVE

To develop and validate a personalized prediction model for psoriasis relapse following the discontinuation of biologics.

METHODS

This study enrolled patients who achieved remission following biologic therapy. Relapse predictors were identified using the Boruta algorithm combined with multivariate Cox regression. A nomogram and an online calculator were created to aid in the visualization and computation of outcomes. The model's performance was thoroughly assessed using Receiver Operating Characteristic (ROC) curves, Area Under the Curve (AUC), C-statistics, calibration plots, and Decision Curve Analysis (DCA).

RESULTS

The study included 597 patients, with 534 in the derivation cohort and 63 in the validation cohort. Anxiety, disease duration, prior biologic treatments, treatment duration, time to achieve PASI 75, and maximum PASI response were identified as influential factors for relapse and were incorporated into the model. Both internal and external evaluations indicate that the model exhibits good predictive accuracy.

CONCLUSION

A multivariate model leveraging standard clinical data can relatively accurately predict the risk of psoriasis relapse post-biologic discontinuation, guiding personalized treatment strategies.

Home- vs Office-Based Narrowband UV-B Phototherapy for Patients With Psoriasis: The LITE Randomized Clinical Trial

Importance

Office-based phototherapy is cost-effective for psoriasis but difficult to access. Home-based phototherapy is patient preferred but has limited clinical data, particularly in patients with darker skin.

Objective

To compare the effectiveness of home- vs office-based narrowband UV-B phototherapy for psoriasis.

Design, Setting, and Participants

The Light Treatment Effectiveness study was an investigator-initiated, pragmatic, open-label, parallel-group, multicenter, noninferiority randomized clinical trial embedded in routine care at 42 academic and private clinical dermatology practices in the US. Enrollment occurred from March 1, 2019, to December 4, 2023, with follow-up through June 2024. Participants were 12 years and older with plaque or guttate psoriasis who were candidates for home- and office-based phototherapy.

Interventions

Participants were randomized to receive a home narrowband UV-B machine with guided mode dosimetry or routine care with office-based narrowband UV-B for 12 weeks, followed by an additional 12-week observation period.

Main Outcomes and Measures

The coprimary effectiveness outcomes were Physician Global Assessment (PGA) dichotomized as clear/almost clear skin (score of ≤1) at the end of the intervention period and Dermatology Life Quality Index (DLQI) score of 5 or lower (no to small effect on quality of life) at week 12.

Results

Of 783 patients enrolled (mean [SD] age, 48.0 [15.5] years; 376 [48.0%] female), 393 received home-based phototherapy and 390 received office-based phototherapy, with 350 (44.7%) having skin phototype (SPT) I/II, 350 (44.7%) having SPT III/IV, and 83 (10.6%) having SPT V/VI. A total of 93 patients (11.9%) were receiving systemic treatment. At baseline, mean (SD) PGA was 2.7 (0.8) and DLQI was 12.2 (7.2). At week 12, 129 patients (32.8%) receiving home-based phototherapy and 100 patients (25.6%) receiving office-based phototherapy achieved clear/almost clear skin, and 206 (52.4%) and 131 (33.6%) achieved DLQI of 5 or lower, respectively. Home-based phototherapy was noninferior to office-based phototherapy for PGA and DLQI in the overall population and across all SPTs. Home-based phototherapy, compared to office-based phototherapy, was associated with better treatment adherence (202 patients [51.4%] vs 62 patients [15.9%]; P < .001), lower burden of indirect costs to patients, and more episodes of persistent erythema (466 of 7957 treatments [5.9%] vs 46 of 3934 treatments [1.2%]; P < .001). Both treatments were well tolerated with no discontinuations due to adverse events.

Conclusions and Relevance

In this randomized clinical trial, home-based phototherapy was as effective as office-based phototherapy for plaque or guttate psoriasis in everyday clinical practice and had less burden to patients.

Trial Registration

ClinicalTrials.gov Identifier: NCT03726489.

Adjunctive Chinese medicine therapy reduces relapse of psoriasis vulgaris after discontinuation of biologics: a prospective registry-based cohort study

BACKGROUND

Biologics have revolutionized psoriasis treatment; however, relapse of psoriasis after discontinuation of biologics remains unresolved.

OBJECTIVE

To assess the impact of adjunctive Chinese medicine (CM) therapy on relapse of psoriasis vulgaris (PV) after discontinuation of biologics.

METHODS

We constructed a prospective cohort study through a psoriasis case registry platform that enrolled patients treated with biologics (in combination with or without CM). The endpoint event was relapse, defined as loss of psoriasis area and severity index (PASI) 75.

RESULTS

A total of 391 patients completed the study and were included in the analysis, of whom 169 (43.2%) experienced relapse during follow-up. To minimize the bias, a 1:1 propensity score matching (PSM) was performed, generating matched cohorts of 156 individuals per group. Adjuvant CM therapy significantly associated with reduced incidence of relapse (HR =0.418, 95% CI = 0.289 ∼ 0.604, p < 0.001), and the protective effect of CM in the subgroup analysis was significant. In addition, PASI 90 response and disease duration were associated with relapse (p < 0.05).

CONCLUSION

Adjunctive CM therapy is associated with reduced relapse incidence in PV after discontinuation of biologics.

Phototherapy for Psoriasis in the Age of Biologics

Phototherapy has utility as a psoriatic therapy, given its relatively high clinical efficacy, low side effect profile, and lower cost compared to newer effective treatments like biologics and small molecules. Phototherapy has shown Psoriasis Area and Severity Index (PASI)-75 and PASI-90 rates comparable to those of biologics and small molecules, with similarly rapid onsets of action, rates of remission, and quality of life scores. Certain patients may particularly benefit from phototherapy, such as those with localized disease or contraindications to systemic immunomodulatory medication. Phototherapy can be more cost-effective than biologics and conveniently administered at home, making it a valuable therapeutic option for the right patient.

The biological basis of disease recurrence in psoriasis

Despite the amazing advances produced in our understanding of the pathogenesis of psoriasis, which have led to a therapeutic revolution, our knowledge of the mechanisms of relapse and elicitation of lesions is just starting to unravel. This narrative review tours the different cell types and mechanisms involved in the priming, maintenance, and relapse of psoriasis vulgaris. Our discussion includes dendritic cells, T cells, tissue resident memory cells and mast cells, with a foray into the epigenetic mechanisms of inflammatory memory in keratinocytes. Increasing knowledge is providing a glimpse of a potential therapeutic window of opportunity in psoriasis, providing long term remission and eventual modification of the natural history of the disease.

Opportunities for implementing a patient-initiated follow-up pathway for patients with psoriasis completing phototherapy

We performed a retrospective case analysis to identify opportunities to introduce a patient-initiated follow-up (PIFU) pathway for patients with psoriasis completing narrowband ultraviolet B phototherapy at our centre. In total, 42 patients completed phototherapy between January 2016 and August 2018 and outcomes were observed for 36 months after phototherapy cessation. Had a PIFU pathway been in place, 24 routine follow-up appointments could have been saved and 8 nonattendances could have been avoided. Seven patients who were discharged or did not attend follow-up after phototherapy flared within 12 months and could have benefited from PIFU to re-access dermatology care. In total 21 patients (50.0%) experienced a relapse within 36 months of completion of phototherapy, and 18 of these (85.7%) relapsed at 0-12 months. The median time to relapse was 6 months. We conclude a post-phototherapy PIFU pathway could help eliminate unnecessary appointments for patients in remission and improve access for patients who relapse. A 12-month PIFU duration prior to discharge would be sufficient to capture the majority of relapses.

Individualised computational modelling of immune mediated disease onset, flare and clearance in psoriasis

Despite increased understanding about psoriasis pathophysiology, currently there is a lack of predictive computational models. We developed a personalisable ordinary differential equations model of human epidermis and psoriasis that incorporates immune cells and cytokine stimuli to regulate the transition between two stable steady states of clinically healthy (non-lesional) and disease (lesional psoriasis, plaque) skin. In line with experimental data, an immune stimulus initiated transition from healthy skin to psoriasis and apoptosis of immune and epidermal cells induced by UVB phototherapy returned the epidermis back to the healthy state. Notably, our model was able to distinguish disease flares. The flexibility of our model permitted the development of a patient-specific “UVB sensitivity” parameter that reflected subject-specific sensitivity to apoptosis and enabled simulation of individual patients’ clinical response trajectory. In a prospective clinical study of 94 patients, serial individual UVB doses and clinical response (Psoriasis Area Severity Index) values collected over the first three weeks of UVB therapy informed estimation of the “UVB sensitivity” parameter and the prediction of individual patient outcome at the end of phototherapy. An important advance of our model is its potential for direct clinical application through early assessment of response to UVB therapy, and for individualised optimisation of phototherapy regimes to improve clinical outcome. Additionally by incorporating the complex interaction of immune cells and epidermal keratinocytes, our model provides a basis to study and predict outcomes to biologic therapies in psoriasis.

We present a new computer model for psoriasis, an immune-mediated disabling skin disease which presents with red, raised scaly plaques that can appear over the whole body. Psoriasis affects millions of people in the UK alone and causes significant impairment to quality of life, and currently has no cure. Only a few treatments (including UVB phototherapy) can induce temporary remission. Despite our increased understanding about psoriasis, treatments are still given on a ‘trial and error’ basis and there are no reliable computer models that can a) elucidate the mechanisms behind psoriasis onset or flare and b) predict a patient’s response to a course of treatment (e.g., phototherapy) and the likelihood of inducing a period of remission. Our computer model addresses both these needs. First, it explicitly describes the interaction between the immune system and skin cells. Second, our model captures response to therapy at the individual patient level and enables personalised prediction of clinical outcomes. Notably, our model also supports prediction of amending individual UVB phototherapy regimes based on the patient’s initial response that include for example personalised delivery schedules (i.e., 3x weekly vs. 5x weekly phototherapy). Therefore, our work is a crucial step towards precision medicine for psoriasis treatment.