Inter-observer reliability of the PASI in a clinical setting

Add-on effects of Chinese herbal medicine external application (FZHFZY) to topical urea for mild-to-moderate psoriasis vulgaris: Protocol for a double-blinded randomized controlled pilot trial embedded with a qualitative study

Psoriasis vulgaris is a chronic dermatological disease with a high global prevalence. It significantly reduces patients' quality of life and is associated with a substantial economic burden. Conventional therapies for mild-to-moderate psoriasis are often associated with insufficient long-term symptomatic relief and side effects. Chinese herbal medicine (CHM) is commonly used for psoriasis management. A CHM formula, namely Fu zheng he fu zhi yang (FZHFZY), has shown promising treatment effects in clinical practice when used as a bath therapy. However, its efficacy and safety has not been evaluated by a rigorous randomized controlled trial (RCT). Therefore, we designed a double-blinded pilot RCT embedded with a qualitative study on CHM formula FZHFZY plus topical urea for mild-to-moderate psoriasis vulgaris to advance the evidence development and practice of CHM external application for psoriasis. This will be a mixed-method design consisting of a pilot RCT and a qualitative study. The pilot RCT is a two-arm, parallel, placebo-controlled, double-blinded trial. Sixty eligible participants will be randomized at a 1:1 ratio to receive eight weeks' treatment of either FZHFZY plus 10% urea cream, or placebo plus 10% urea cream, with 12-week follow-up visits after the treatment phase. The CHM or placebo will be administered externally as a bath therapy. Outcome measures include trial feasibility, efficacy and safety. The primary efficacy outcome will be Psoriasis Area Severity Index (PASI). Secondary efficacy outcomes include Physician Global Assessment, PASI-75, PASI-50, Body Surface Area, Dermatology Life Quality Index, Skindex-16, itch visual analogue scale and relapse. The qualitative study will be conducted to collect participants' feedback on CHM external application and their experience with the pilot RCT. This study will advance the evidence-based clinical practice of using CHM for psoriasis vulgaris and then to support translation of findings into clinical practice in the future. Trial registration number: ChiCTR2200064092.

Artificial Intelligence-Based Psoriasis Severity Assessment: Real-world Study and Application

BACKGROUND

Psoriasis is one of the most frequent inflammatory skin conditions and could be treated via tele-dermatology, provided that the current lack of reliable tools for objective severity assessments is overcome. Psoriasis Area and Severity Index (PASI) has a prominent level of subjectivity and is rarely used in real practice, although it is the most widely accepted metric for measuring psoriasis severity currently.

OBJECTIVE

This study aimed to develop an image-artificial intelligence (AI)-based validated system for severity assessment with the explicit intention of facilitating long-term management of patients with psoriasis.

METHODS

A deep learning system was trained to estimate the PASI score by using 14,096 images from 2367 patients with psoriasis. We used 1962 patients from January 2015 to April 2021 to train the model and the other 405 patients from May 2021 to July 2021 to validate it. A multiview feature enhancement block was designed to combine vision features from different perspectives to better simulate the visual diagnostic method in clinical practice. A classification header along with a regression header was simultaneously applied to generate PASI scores, and an extra cross-teacher header after these 2 headers was designed to revise their output. The mean average error (MAE) was used as the metric to evaluate the accuracy of the predicted PASI score. By making the model minimize the MAE value, the model becomes closer to the target value. Then, the proposed model was compared with 43 experienced dermatologists. Finally, the proposed model was deployed into an app named SkinTeller on the WeChat platform.

RESULTS

The proposed image-AI-based PASI-estimating model outperformed the average performance of 43 experienced dermatologists with a 33.2% performance gain in the overall PASI score. The model achieved the smallest MAE of 2.05 at 3 input images by the ablation experiment. In other words, for the task of psoriasis severity assessment, the severity score predicted by our model was close to the PASI score diagnosed by experienced dermatologists. The SkinTeller app has been used 3369 times for PASI scoring in 1497 patients from 18 hospitals, and its excellent performance was confirmed by a feedback survey of 43 dermatologist users.

CONCLUSIONS

An image-AI-based psoriasis severity assessment model has been proposed to automatically calculate PASI scores in an efficient, objective, and accurate manner. The SkinTeller app may be a promising alternative for dermatologists' accurate assessment in the real world and chronic disease self-management in patients with psoriasis.

Efficacy and Safety of Apremilast Monotherapy in moderate-to-severe Plaque Psoriasis: A Systematic Review and Meta-analysis

Psoriasis is a chronic, inflammatory, immune-mediated disease of the skin and joints. Plaque psoriasis is the most common clinical phenotype of psoriasis. Apremilast is an oral phosphodiesterase type 4 inhibitor recently approved by the US Food and Drug Administration (FDA) for the management of plaque psoriasis. To assess the efficacy and safety of apremilast monotherapy for the treatment of moderate-to-severe plaque psoriasis. This systematic review included randomized controlled trials (RCTs) comparing apremilast 20 mg twice daily (BID) and 30 mg BID with placebo for its efficacy on plaque psoriasis. We searched the Embase, Medline, and CENTRAL databases. We sought to evaluate the following outcomes: psoriasis area and severity index score (PASI)-50, PASI-75, PASI-90, static Physician Global Assessment (sPGA), and adverse events. The risk ratio (RR) was used to represent dichotomous outcomes and adverse events, and the data were pooled using the inverse variance weighting method. Eight RCTs that enrolled 2635 participants were deemed eligible. Apremilast 30 mg BID and 20 mg BID were significantly more efficacious than placebo in achieving PASI-75 over 16 weeks (RR = 4.60, 95% CI 3.29-6.41, and RR = 3.15, 95% CI 1.96-5.07, respectively). Apremilast 30 mg BID showed a significantly higher rate of adverse events than the placebo (RR = 1.24, 95% CI 1.16-1.33), whereas apremilast 20 mg BID did not exhibit any significant difference (RR = 1.13, 95% CI 0.91-1.42). This meta-analysis demonstrated that apremilast monotherapy is an effective therapeutic option for moderate-to-severe plaque psoriasis with acceptable tolerability and safety profile.

Follow-Up Comparison of Fluorescence Optical Imaging With Musculoskeletal Ultrasound for Early Detection of Psoriatic Arthritis

Objectives

Early diagnosis of psoriatic arthritis (PsA) is crucial for a patient outcome but hampered by heterogenous manifestation and a lack of specific biomarkers. We recently showed that fluorescence optical imaging (FOI) can differentiate between patients with confirmed and suspected PsA. This study aims to follow-up (FU) patients with confirmed and suspected PsA focusing on patients with a change from suspected to confirmed PsA by the use of FOI in comparison with musculoskeletal ultrasound (MSUS).

Methods

Follow-up examination of patients included in the study performed by Erdmann-Keding et al. in which FOI of both hands was performed in a standardized manner using three predefined phases (p1–p3) and PrimaVista Mode (PVM). The comparison was drawn to grayscale–power Doppler (GS/PD) MSUS of the clinically dominant hand (wrist, MCP, PIP, DIP 2–5) from dorsal or palmar.

Results

Patients with a change from suspected to diagnosed PsA showed an increased prevalence of joints with pathological enhancement in FOI (p = 0.046) with an unchanged joint distribution pattern, especially with a dominant involvement of DIP joints. Compared to the baseline, these patients were three times more common to show enhancement in FOI p3 at FU. Newly detected pathologic joints by FOI (PVM, p2) and MSUS at FU were positively associated with the change of diagnosis from suspected to confirmed PsA (FOI: AUC 0.78; GSUS: AUC 0.77).

Conclusion

Fluorescence optical imaging appears to be a helpful tool to detect early PsA and to distinguish between acute and chronic disease stages. It could thereby become a suitable tool as a screening method to select psoriasis patients with an indication for further rheumatological evaluation.

Systemic glucocorticoid use and the occurrence of flares in psoriatic arthritis and psoriasis: a systematic review

Objectives

The use of systemic glucocorticoids (SGCs) is traditionally discouraged in the treatment of PsA and psoriasis due to the risk of psoriatic flares. However, despite this recommendation, SGCs are frequently prescribed for these patients. In this study we reappraise the old paradigm that SGCs are contra-indicated in the treatment of PsA and psoriasis.

Methods

A systematic search of MEDLINE, EMBASE and the Cochrane Library databases was performed in November 2019 to identify articles on any SGC use compared with no use in the PsA and psoriasis population. Topical glucocorticoid treatment was excluded. Our two primary outcomes focused on the prescribing characteristics and the occurrence of any type of flare.

Results

Our search yielded 4922 articles, and of these 21 full-text articles were eligible for inclusion. There were 11 retro- and prospective cohorts involving a total of 4,171,307 patients. Of these, 6727 (37.82%) of the patients with PsA and 1 460 793 (35.17%) of the patients with psoriasis were treated with any type of SGC. Ten observational/interventional studies did not report an increased risk or occurrence of psoriatic flares related to SGC use.

Conclusion

Our results indicate that SGCs are frequently prescribed for PsA and psoriasis patients. The occurrence of psoriatic flares appears to be low upon SGC exposure. In patients with a clear indication for SGCs, e.g. in need of rapid anti-inflammatory therapy or bridging of therapies, the use of SGCs should be considered in view of the low risk of skin flaring. It remains of importance to weigh risks for short- and long-term SGC-related side effects in clinical decision making.

Image-based automated Psoriasis Area Severity Index scoring by Convolutional Neural Networks

Background

The Psoriasis Area and Severity Index (PASI) score is commonly used in clinical practice and research to monitor disease severity and determine treatment efficacy. Automating the PASI score with deep learning algorithms, like Convolutional Neural Networks (CNNs), could enable objective and efficient PASI scoring.

Objectives

To assess the performance of image‐based automated PASI scoring in anatomical regions by CNNs and compare the performance of CNNs to image‐based scoring by physicians.

Methods

Imaging series were matched to PASI subscores determined in real life by the treating physician. CNNs were trained using standardized imaging series of 576 trunk, 614 arm and 541 leg regions. CNNs were separately trained for each PASI subscore (erythema, desquamation, induration and area) in each anatomical region (trunk, arms and legs). The head region was excluded for anonymity. Additionally, PASI‐trained physicians retrospectively determined image‐based subscores on the test set images of the trunk. Agreement with the real‐life scores was determined with the intraclass correlation coefficient (ICC) and compared between the CNNs and physicians.

Results

Intraclass correlation coefficients between the CNN and real‐life scores of the trunk region were 0.616, 0.580, 0.580 and 0.793 for erythema, desquamation, induration and area, respectively, with similar results for the arms and legs region. PASI‐trained physicians (N = 5) were in moderate–good agreement (ICCs 0.706–0.793) with each other for image‐based PASI scoring of the trunk region. ICCs between the CNN and real‐life scores were slightly higher for erythema (0.616 vs. 0.558), induration (0.580 vs. 0.573) and area scoring (0.793 vs. 0.694) than image‐based scoring by physicians. Physicians slightly outperformed the CNN on desquamation scoring (0.580 vs. 0.589).

Conclusions

Convolutional Neural Networks have the potential to automatically and objectively perform image‐based PASI scoring at an anatomical region level. For erythema, desquamation and induration scoring, CNNs performed similar to physicians, while for area scoring CNNs outperformed physicians on image‐based PASI scoring.

Platelets: Underestimated Regulators of Autoinflammation in Psoriasis

Platelets have long been known as mediators of hemostasis and, more recently, as mediators of thromboinflammation, although their physiopathological role has mostly been investigated in the context of disease of internal organs, such as liver and kidney, or systemic disorders. Of late, exciting recent data suggest that platelets may also play a role in inflammation at distal sites such as the skin: recent studies show that platelets, by engaging polymorphonuclear neutrophils (PMNs), contribute to local inflammation in the frequent skin disorder, psoriasis. In an experimental model, systemic depletion of platelets drastically attenuated skin inflammation by preventing PMN infiltration of the skin. A broader role of platelets in different types of skin inflammation is therefore likely, and in this paper, we specifically review recent advances in psoriasis. Special emphasis is given to the crosstalk with systemic platelet effects, which may be of interest in psoriasis-related cardiovascular comorbidities. Furthermore, we discuss the potential for platelet-centered interventions in the therapy for psoriasis.

Joint AAD-NPF Guidelines of care for the management and treatment of psoriasis with topical therapy and alternative medicine modalities for psoriasis severity measures

Psoriasis is a chronic, inflammatory, multisystem disease that affects up to 3.2% of the United States population. This guideline addresses important clinical questions that arise in psoriasis management and care and provides recommendations based on the available evidence. The treatment of psoriasis with topical agents and with alternative medicine will be reviewed, emphasizing treatment recommendations and the role of dermatologists in monitoring and educating patients regarding benefits as well as risks that may be associated. This guideline will also address the severity assessment methods of psoriasis in adults.

Assessment and Clinical Relevance of Serum IL-19 Levels in Psoriasis and Atopic Dermatitis Using a Sensitive and Specific Novel Immunoassay

Because development of reliable biomarkers in psoriasis and atopic dermatitis has lagged behind therapeutic progress, we created a blood-based test to fill the void in objective methods available for dermatological assessments. Our novel interleukin-19 (IL-19) immunoassay was initially tested to determine concentrations of IL-19 serum levels, then correlated with the psoriasis activity and severity index (PASI) in psoriasis, and the eczema area and severity index (EASI) in atopic dermatitis. Not only was IL-19 increased in psoriasis and correlated to PASI, but ixekizumab administration led to rapid, sustained IL-19 decreases to normal levels, with decreases at 2-weeks correlating with PASI improvement at 16-weeks. IL-19 increased upon ixekizumab withdraw, prior to relapse, and decreased following re-treatment. In baricitinib- and etanercept-treated psoriasis patients, IL-19 decreases also correlated with improvement. Many patients with limited skin disease, including genital psoriasis and psoriatic arthritis patients, also had increased IL-19, which was reduced to normal levels upon ixekizumab treatment, correlating with PASI improvement. We also measured IL-19 in baricitinib-treated atopic dermatitis patients. In atopic dermatitis, IL-19 was significantly elevated, correlated with EASI scores, and decreased with skin improvement. Therefore, measurement of serum IL-19 provides clinicians with an objective disease-activity assessment tool for psoriasis and atopic dermatitis patients.

Intra- and interobserver variability of image-based PASI assessments in 120 patients suffering from plaque-type psoriasis

BACKGROUND

The Psoriasis Area and Severity Index (PASI) is the standard for psoriasis severity assessment. However, PASI measurement is complex and subjective, frequently leading to a high intra- and interobserver variability. To date, the precise extent of variability in PASI measurements and its underlying causes remain unknown.

OBJECTIVE

To determine the inter- and intrarater variability of image-based PASI measurements by calculating Intra-Class-Correlation-Coefficients (ICCs) and to investigate the impact of the different PASI components and specific anatomic regions on the extent of variability.

METHODS

First, the methodology of 'image-based' vs. commonly used 'live' PASI measurements was validated in a pilot study. Next, in an observational cohort study, PASI scores of 120 patients affected by plaque psoriasis were prospectively evaluated by three formally trained physicians by means of total body images (TBI). Each observer independently performed two rounds of image-based PASI calculations in all patients at two different time points.

RESULTS

Overall, 720 image-based PASI scores were calculated with a mean PASI of 8.8 (range 0.7-34.8). An interrater variability with an ICC of 0.895 and mean absolute difference (MAD) of 3.3 PASI points were observed. Intrarater variability showed a mean ICC of 0.877 and a MAD of 2.2 points. When considering specific PASI components, the highest agreement was found for the assessment of the involved body surface area (BSA), while the lowest ICCs were calculated for severity scoring of 'scaling' and 'induration'. As BSA scores serve as a multiplier in the calculation of PASI, minor inaccuracies were capable of inducing a large share of variability.

CONCLUSION

The overall inter- and intrarater reliability of image-based PASI measurements in this study was good. However, physicians were formally trained and experienced, which frequently is not the case in a real-life clinical setting. Therefore, new strategies for higher standardization and objectivity of PASI calculations are needed.

The metabolic analysis of psoriasis identifies the associated metabolites while providing computational models for the monitoring of the disease

The majority of studies on psoriasis have focused on explaining the genetic background and its associations with the immune system’s response. The aim of this study was to identify the low-molecular weight compounds contributing to the metabolomic profile of psoriasis and to provide computational models that help with the classification and monitoring of the severity of the disease. We compared the results from targeted and untargeted analyses of patients’ serums with plaque psoriasis to controls. The main differences were found in the concentrations of acylcarnitines, phosphatidylcholines, amino acids, urea, phytol, and 1,11-undecanedicarboxylic acid. The data from the targeted analysis were used to build classification models for psoriasis. The results from this study provide an overview of the metabolomic serum profile of psoriasis along with promising statistical models for the monitoring of the disease.