8 research outputs found

    Association of Clinical and Demographic Factors With the Severity of Palmoplantar Pustulosis.

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    Importance: Although palmoplantar pustulosis (PPP) can significantly impact quality of life, the factors underlying disease severity have not been studied. Objective: To examine the factors associated with PPP severity. Design, Setting, and Participants: An observational, cross-sectional study of 2 cohorts was conducted. A UK data set including 203 patients was obtained through the Anakinra in Pustular Psoriasis, Response in a Controlled Trial (2016-2019) and its sister research study Pustular Psoriasis, Elucidating Underlying Mechanisms (2016-2020). A Northern European cohort including 193 patients was independently ascertained by the European Rare and Severe Psoriasis Expert Network (2014-2017). Patients had been recruited in secondary or tertiary dermatology referral centers. All patients were of European descent. The PPP diagnosis was established by dermatologists, based on clinical examination and/or published consensus criteria. The present study was conducted from October 1, 2014, to March 15, 2020. Main Outcomes and Measures: Demographic characteristics, comorbidities, smoking status, Palmoplantar Pustulosis Psoriasis Area Severity Index (PPPASI), measuring severity from 0 (no sign of disease) to 72 (very severe disease), or Physician Global Assessment (PGA), measuring severity as 0 (clear), 1 (almost clear), 2 (mild), 3 (moderate), and 4 (severe). Results: Among the 203 UK patients (43 men [21%], 160 women [79%]; median age at onset, 48 [interquartile range (IQR), 38-59] years), the PPPASI was inversely correlated with age of onset (r = -0.18, P = .01). Similarly, in the 159 Northern European patients who were eligible for inclusion in this analysis (25 men [16%], 134 women [84%]; median age at onset, 45 [IQR, 34-53.3] years), the median age at onset was lower in individuals with a moderate to severe PGA score (41 years [IQR, 30.5-52 years]) compared with those with a clear to mild PGA score (46.5 years [IQR, 35-55 years]) (P = .04). In the UK sample, the median PPPASI score was higher in women (9.6 [IQR, 3.0-16.2]) vs men (4.0 [IQR, 1.0-11.7]) (P = .01). Likewise, moderate to severe PPP was more prevalent among Northern European women (57 of 134 [43%]) compared with men (5 of 25 [20%]) (P = .03). In the UK cohort, the median PPPASI score was increased in current smokers (10.7 [IQR, 4.2-17.5]) compared with former smokers (7 [IQR, 2.0-14.4]) and nonsmokers (2.2 [IQR, 1-6]) (P = .003). Comparable differences were observed in the Northern European data set, as the prevalence of moderate to severe PPP was higher in former and current smokers (51 of 130 [39%]) compared with nonsmokers (6 of 24 [25%]) (P = .14). Conclusions and Relevance: The findings of this study suggest that PPP severity is associated with early-onset disease, female sex, and smoking status. Thus, smoking cessation intervention might be beneficial

    Successful intra-class switching among IL-17 antagonists: a multicentre, multinational, retrospective study

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    IL-17 blockers are among the newer anti-psoriatic treatment options and little is known about the interclass switching. We have thus initiated a multi-center, multi-national, retrospective study to assess the treatment response of patients who were switched from one IL-17 blocker to another. Analysis consisted of data from patients with moderate-to-severe psoriasis who did not respond satisfactorily to one of the available IL-17 blockers (secukinumab, ixekizumab, brodalumab) and were subsequently switched to another drug of this class. After 12 weeks of treatment, patients’ PASIs were evaluated. Treatment success was defined as reaching PASI 75 after 12 weeks. Topical treatment was allowed and used in all patients. 26 patients were included (13 male, 13 female) and 29 switches were evaluated. Overall, 29 switches in 21 patients were evaluated. 18 patients changed their therapy from secukinumab to ixekizumab, or in 7 cases to brodalumab. Brodalumab was used in 3 cases after failure of treatment with ixekizumab. Only in one case, non-response of brodalumab resulted in a therapy switch to secukinumab. In 15 (52%) cases, PASI 75 was reached. In 6 (20%) patients, the switch led to a PASI 50 response. No success of treatment was seen among 8 (28%) participants. When patients fail to respond or do not tolerate an IL-17 blocker, switching to another anti-IL-17A/RA is a promising viable option. Larger studies are needed to confirm our results

    Clinical and genetic differences between pustular psoriasis subtypes

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    The term pustular psoriasis indicates a group of severe skin disorders characterized by eruptions of neutrophil-filled pustules. The disease, which often manifests with concurrent psoriasis vulgaris, can have an acute systemic (generalized pustular psoriasis [GPP]) or chronic localized (palmoplantar pustulosis [PPP] and acrodermatitis continua of Hallopeau [ACH]) presentation. Although mutations have been uncovered in IL36RN and AP1S3, the rarity of the disease has hindered the study of genotype-phenotype correlations. We sought to characterize the clinical and genetic features of pustular psoriasis through the analysis of an extended patient cohort. We ascertained a data set of unprecedented size, including 863 unrelated patients (251 with GPP, 560 with PPP, 28 with ACH, and 24 with multiple diagnoses). We undertook mutation screening in 473 cases. Psoriasis vulgaris concurrence was lowest in PPP (15.8% vs 54.4% in GPP and 46.2% in ACH, P <.0005 for both), whereas the mean age of onset was earliest in GPP (31.0 vs 43.7 years in PPP and 51.8 years in ACH, P <.0001 for both). The percentage of female patients was greater in PPP (77.0%) than in GPP (62.5%; P = 5.8 × 10 ). The same applied to the prevalence of smokers (79.8% vs 28.3%, P < 10 ). Although AP1S3 alleles had similar frequency (0.03-0.05) across disease subtypes, IL36RN mutations were less common in patients with PPP (0.03) than in those with GPP (0.19) and ACH (0.16; P = 1.9 × 10 and.002, respectively). Importantly, IL36RN disease alleles had a dose-dependent effect on age of onset in all forms of pustular psoriasis (P =.003). The analysis of an unparalleled resource revealed key clinical and genetic differences between patients with PPP and those with GPP

    Clinical and genetic differences between pustular psoriasis subtypes

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    Background: The term pustular psoriasis indicates a group of severe skin disorders characterized by eruptions of neutrophil-filled pustules. The disease, which often manifests with concurrent psoriasis vulgaris, can have an acute systemic (generalized pustular psoriasis [GPP]) or chronic localized (palmoplantar pustulosis [PPP] and acrodermatitis continua of Hallopeau [ACH]) presentation. Although mutations have been uncovered in IL36RN and AP1S3, the rarity of the disease has hindered the study of genotype-phenotype correlations. Objective: We sought to characterize the clinical and genetic features of pustular psoriasis through the analysis of an extended patient cohort. Methods: We ascertained a data set of unprecedented size, including 863 unrelated patients (251 with GPP, 560 with PPP, 28 with ACH, and 24 with multiple diagnoses). We undertook mutation screening in 473 cases. Results: Psoriasis vulgaris concurrence was lowest in PPP (15.8% vs 54.4% in GPP and 46.2% in ACH, P &lt; .0005 for both), whereas the mean age of onset was earliest in GPP (31.0 vs 43.7 years in PPP and 51.8 years in ACH, P &lt; .0001 for both). The percentage of female patients was greater in PPP (77.0%) than in GPP (62.5%; P = 5.8 × 10−5). The same applied to the prevalence of smokers (79.8% vs 28.3%, P &lt; 10−15). Although AP1S3 alleles had similar frequency (0.03-0.05) across disease subtypes, IL36RN mutations were less common in patients with PPP (0.03) than in those with GPP (0.19) and ACH (0.16; P = 1.9 × 10−14 and .002, respectively). Importantly, IL36RN disease alleles had a dose-dependent effect on age of onset in all forms of pustular psoriasis (P = .003). Conclusions: The analysis of an unparalleled resource revealed key clinical and genetic differences between patients with PPP and those with GPP

    Association of clinical and demographic factors with the severity of Palmoplantar Pustulosis

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    Importance Although palmoplantar pustulosis (PPP) can significantly impact quality of life, the factors underlying disease severity have not been studied. Objective To examine the factors associated with PPP severity. Design, Setting, and Participants An observational, cross-sectional study of 2 cohorts was conducted. A UK data set including 203 patients was obtained through the Anakinra in Pustular Psoriasis, Response in a Controlled Trial (2016-2019) and its sister research study Pustular Psoriasis, Elucidating Underlying Mechanisms (2016-2020). A Northern European cohort including 193 patients was independently ascertained by the European Rare and Severe Psoriasis Expert Network (2014-2017). Patients had been recruited in secondary or tertiary dermatology referral centers. All patients were of European descent. The PPP diagnosis was established by dermatologists, based on clinical examination and/or published consensus criteria. The present study was conducted from October 1, 2014, to March 15, 2020. Main Outcomes and Measures Demographic characteristics, comorbidities, smoking status, Palmoplantar Pustulosis Psoriasis Area Severity Index (PPPASI), measuring severity from 0 (no sign of disease) to 72 (very severe disease), or Physician Global Assessment (PGA), measuring severity as 0 (clear), 1 (almost clear), 2 (mild), 3 (moderate), and 4 (severe). Results Among the 203 UK patients (43 men [21%], 160 women [79%]; median age at onset, 48 [interquartile range (IQR), 38-59] years), the PPPASI was inversely correlated with age of onset (r = −0.18, P = .01). Similarly, in the 159 Northern European patients who were eligible for inclusion in this analysis (25 men [16%], 134 women [84%]; median age at onset, 45 [IQR, 34-53.3] years), the median age at onset was lower in individuals with a moderate to severe PGA score (41 years [IQR, 30.5-52 years]) compared with those with a clear to mild PGA score (46.5 years [IQR, 35-55 years]) (P = .04). In the UK sample, the median PPPASI score was higher in women (9.6 [IQR, 3.0-16.2]) vs men (4.0 [IQR, 1.0-11.7]) (P = .01). Likewise, moderate to severe PPP was more prevalent among Northern European women (57 of 134 [43%]) compared with men (5 of 25 [20%]) (P = .03). In the UK cohort, the median PPPASI score was increased in current smokers (10.7 [IQR, 4.2-17.5]) compared with former smokers (7 [IQR, 2.0-14.4]) and nonsmokers (2.2 [IQR, 1-6]) (P = .003). Comparable differences were observed in the Northern European data set, as the prevalence of moderate to severe PPP was higher in former and current smokers (51 of 130 [39%]) compared with nonsmokers (6 of 24 [25%]) (P = .14). Conclusions and Relevance The findings of this study suggest that PPP severity is associated with early-onset disease, female sex, and smoking status. Thus, smoking cessation intervention might be beneficial

    Superior skin cancer classification by the combination of human and artificial intelligence

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    Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. However, the combination of classifiers frequently yields superior results, both in machine learning and among humans. In this study, we investigated the potential benefit of combining human and artificial intelligence for skin cancer classification. Methods: Using 11,444 dermoscopic images, which were divided into five diagnostic categories, novel deep learning techniques were used to train a single CNN. Then, both 112 dermatologists of 13 German university hospitals and the trained CNN independently classified a set of 300 biopsy-verified skin lesions into those five classes. Taking into account the certainty of the decisions, the two independently determined diagnoses were combined to a new classifier with the help of a gradient boosting method. The primary end-point of the study was the correct classification of the images into five designated categories, whereas the secondary end-point was the correct classification of lesions as either benign or malignant (binary classification). Findings: Regarding the multiclass task, the combination of man and machine achieved an accuracy of 82.95%. This was 1.36% higher than the best of the two individual classifiers (81.59% achieved by the CNN). Owing to the class imbalance in the binary problem, sensitivity, but not accuracy, was examined and demonstrated to be superior (89%) to the best individual classifier (CNN with 86.1%). The specificity in the combined classifier decreased from 89.2% to 84%. However, at an equal sensitivity of 89%, the CNN achieved a specificity of only 81.5% Interpretation: Our findings indicate that the combination of human and artificial intelligence achieves superior results over the independent results of both of these systems. (C) 2019 The Author(s). Published by Elsevier Ltd

    Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks

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    Background: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer screenings in which multiple diagnoses need to be taken into account. Methods: Using 11,444 dermoscopic images, which covered dermatologic diagnoses comprising the majority of commonly pigmented skin lesions commonly faced in skin cancer screenings, a CNN was trained through novel deep learning techniques. A test set of 300 biopsy-verified images was used to compare the classifier's performance with that of 112 dermatologists from 13 German university hospitals. The primary end-point was the correct classification of the different lesions into benign and malignant. The secondary end-point was the correct classification of the images into one of the five diagnostic categories. Findings: Sensitivity and specificity of dermatologists for the primary end-point were 74.4% (95% confidence interval [CI]: 67.0-81.8%) and 59.8% (95% CI: 49.8-69.8%), respectively. At equal sensitivity, the algorithm achieved a specificity of 91.3% (95% CI: 85.5-97.1%). For the secondary end-point, the mean sensitivity and specificity of the dermatologists were at 56.5% (95% CI: 42.8-70.2%) and 89.2% (95% CI: 85.0-93.3%), respectively. At equal sensitivity, the algorithm achieved a specificity of 98.8%. Two-sided McNemar tests revealed significance for the primary end-point (p < 0.001). For the secondary end-point, outperformance (p < 0.001) was achieved except for basal cell carcinoma (on-par performance). Interpretation: Our findings show that automated classification of dermoscopic melanoma and nevi images is extendable to a multiclass classification problem, thus better reflecting clinical differential diagnoses, while still outperforming dermatologists at a significant level (p < 0.001). (C) 2019 The Author(s). Published by Elsevier Ltd

    Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks

    No full text
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