PASI vs PO‐PASI: Patient‐Oriented PASI (PO‐PASI) is comparable to clinician score PASI

Pedrosa, Abraham Montes de Oca; Oakley, Amanda; Rogers, Jean; Epiha, Mikey Rangaitaha

doi:10.1111/ajd.13738

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…Baseline demographic and clinical data, including age, gender, and laboratory markers, were collected. Disease severity was assessed using the Psoriasis Area and Severity Index (PASI) scores ( 29 ), with assessments conducted at Weeks 0 and 16 by the same physician. A PASI 75 score indicates a 75% or greater reduction in PASI score from baseline, representing significant disease improvement.…”

Section: Methodsmentioning

confidence: 99%

IL-17A inhibitors alleviate Psoriasis with concomitant restoration of intestinal/skin microbiota homeostasis and altered microbiota function

Zhao,

Shang,

Zhang

et al. 2024

Front. Immunol.

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BackgroundDisturbed gut microbiota and associated metabolic dysfunction exist in Psoriasis. Despite the growing use of interleukin-17 inhibitor (anti-IL17) therapy, the effect of anti-IL17 on gut/skin microbiota function is not fully understood in patients with Psoriasis.ObjectiveTherefore, we explored whether Psoriasis is associated with alterations in selected gut/skin microbiota in a study cohort, and a longitudinal cohort study to reveal the effects of IL-17A inhibitor treatment on gut microbiota in Psoriasis.MethodsIn a case-control study, 14 patients with Psoriasis and 10 age, sex and body mass index-matched Healthy Controls were recruited. Longitudinal mapping of the gut microbiome was performed using 16S rRNA gene sequencing. Mouse models were used to further study and validate the interrelationship between the skin microbiome and the gut microbiome in Psoriasis. PICRUST2 was applied to predict the function of the bacterial community.ResultsIn Psoriasis patients, gut microbiota dysbiosis was present with increased heterogeneity: decreased Bacteroidota and increased Firmicutes as well as Actinobacteriota predominating in Psoriasis. Escherichia-Shigella enrichment was associated with reduction in serum levels of total bile acid and markers in Apoptotic pathways. After IL-17A inhibitor treatment in Psoriasis patients, longitudinal studies observed a trend toward a normal distribution of the gut microbiome and modulation of apoptosis-related metabolic pathways. Results from a mouse model showed dysregulation of the skin microbiota in Psoriasis characterized by Staphylococcus colonization.ConclusionThe psoriatic gut/skin microbiota exhibits loss of community stability and pathogen enrichment. IL-17A inhibitors restore microbiota homeostasis and metabolic pathways, reduce pro-inflammatory cytokine expression, and alleviate symptoms in patients with Psoriasis.

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Section: Methodsmentioning

confidence: 99%

IL-17A inhibitors alleviate Psoriasis with concomitant restoration of intestinal/skin microbiota homeostasis and altered microbiota function

Zhao,

Shang,

Zhang

et al. 2024

Front. Immunol.

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“…PASI is a composite score based on the clinical assessment of BSA, erythema, induration and scaling of psoriasis on different areas of the body (head, trunk, upper limbs and lower limbs) by dermatologists. 56 Savolainen et al discovered that the computer image analysis system offers a possibility to quantify the actual surface area in patients with psoriasis, which could be used for developing quality control when evaluating different treatment efficacies. 57,58 Additionally, psoriasis area assessment methods are being developed based on ML technology, achieving an accuracy of more than 90% in 77% of images with an 8.1% difference from physician's area.…”

Section: Lesion Severity and Area Scoringmentioning

confidence: 99%

Artificial intelligence in psoriasis: Where we are and where we are going

Liu,

Wang,

et al. 2023

Experimental Dermatology

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Artificial intelligence (AI) is a field of computer science that involves the development of programs designed to replicate human cognitive processes and the analysis of complex data. In dermatology, which is predominantly a visual‐based diagnostic field, AI has become increasingly important in improving professional processes, particularly in the diagnosis of psoriasis. In this review, we summarized current AI applications in psoriasis: (i) diagnosis, including identification, classification, lesion segmentation, lesion severity and area scoring; (ii) treatment, including prediction treatment efficiency and prediction candidate drugs; (iii) management, including e‐health and preventive medicine. Key challenges and future aspects of AI in psoriasis were also discussed, in hope of providing potential directions for future studies.

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“…Plaque-type psoriasis, which occurs in 85-90% of affected patients, is the most common form of psoriasis and it is characterized by oval or irregularly shaped, red, sharply demarcated raised plaques covered by silvery scales. The latter are accompanied by itching that usually affects the elbows, knees, scalp and lower back, but can appear anywhere on the body surface with different degrees of severity as measured by the Psoriasis Area and Severity Index (PASI), Body Surface Area, and/or the Physician's Global Assessment (PGA) [13]. It is now well established that psoriasis is a multi-factorial disease, the onset of which is characterized by "triggering factors".…”

Section: Introductionmentioning

confidence: 99%

A Familial Novel Putative-Pathogenic Mutation Identified in Plaque-Psoriasis by a Multigene Panel Analysis

Nunziato

Balato

Ruocco

et al. 2023

IJMS

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Psoriasis is a chronic multifactorial skin disorder with an immune basis. It is characterized by patches of skin that are usually red, flaky and crusty, and that often release silvery scales. The patches appear predominantly on the elbows, knees, scalp and lower back, although they may also appear on other body areas and severity may be variable. The majority of patients (about 90%) present small patches known as “plaque psoriasis”. The roles of environmental triggers such as stress, mechanical trauma and streptococcal infections are well described in psoriasis onset, but much effort is still needed to unravel the genetic component. The principal aim of this study was to use a next-generation sequencing technologies-based approach together with a 96 customized multigene panel in the attempt to determine if there are germline alterations that can explain the onset of the disease, and thus to find associations between genotypes and phenotypes. To this aim, we analyzed a family in which the mother showed mild psoriasis, and her 31-year-old daughter had suffered from psoriasis for several years, whereas an unaffected sister served as a negative control. We found variants already associated directly to psoriasis in the TRAF3IP2 gene, and interestingly we found a missense variant in the NAT9 gene. The use of multigene panels in such a complex pathology such as psoriasis can be of great help in identifying new susceptibility genes, and in being able to make early diagnoses especially in families with affected subjects.

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PASI vs PO‐PASI: Patient‐Oriented PASI (PO‐PASI) is comparable to clinician score PASI

Cited by 6 publications

References 7 publications

IL-17A inhibitors alleviate Psoriasis with concomitant restoration of intestinal/skin microbiota homeostasis and altered microbiota function

IL-17A inhibitors alleviate Psoriasis with concomitant restoration of intestinal/skin microbiota homeostasis and altered microbiota function

Artificial intelligence in psoriasis: Where we are and where we are going

A Familial Novel Putative-Pathogenic Mutation Identified in Plaque-Psoriasis by a Multigene Panel Analysis

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