RESUMO
BACKGROUND: Generalized pustular psoriasis (GPP) is a rare, inflammatory skin disease characterized by widespread eruption of sterile pustules with or without systemic symptoms. OBJECTIVES: This study aimed to describe the demographics of patients with GPP in Central and Eastern Europe (CEE), present the clinical characteristics of individual GPP flares and explore the current treatment landscape. METHODS: Patient demographics were collected at the times of last observation and previous treatment. Characteristics of a patient's last (most recent) and most severe (from all documented episodes) flare were provided at clinician's discretion. RESULTS: Fifty-eight patients were recruited from 12 centres in nine CEE countries; median (range) age was 61 (16-92) years and 60.3% (35 out of 58) were female. The most common comorbidities were hypertension (43.1% [25 out of 58]) and hyperlipidaemia (32.8% [19 out of 58]). Thirty-four patients (58.6%) presented with concomitant plaque psoriasis before or during the course of GPP. Data from two separate flares were recorded in 26 individuals; in 32 patients, the most recent flare was reported as the most severe. Over 90% of patients with a flare episode classified as most severe by clinicians were hospitalized, with >75% of these individuals having a Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) total score of 3 or 4. Systemic symptoms were more common in patients with a GPPGA score of 3 or 4 but were also manifest in individuals with a GPPGA score ≤2. A significant correlation was observed between a combined systemic disease score of clinical and laboratory features and both GPPGA total score (r = 0.385, p < 0.001) and GPPGA pustulation subscore (r = 0.305, p < 0.05). CONCLUSIONS: Considerable heterogeneity in the presentation of GPP flares was observed, both between patients and within-patient. All GPP flares were associated with a significant clinical burden, highlighting the unmet need for accurate and early diagnosis.
Assuntos
Psoríase , Humanos , Psoríase/terapia , Psoríase/epidemiologia , Psoríase/complicações , Feminino , Adulto , Masculino , Pessoa de Meia-Idade , Adolescente , Idoso , Adulto Jovem , Idoso de 80 Anos ou mais , Europa Oriental/epidemiologia , Europa (Continente)/epidemiologia , Índice de Gravidade de Doença , Hipertensão/epidemiologia , Hipertensão/complicaçõesRESUMO
BACKGROUND: Deep-learning convolutional neural networks (CNNs) have outperformed even experienced dermatologists in dermoscopic melanoma detection under controlled conditions. It remains unexplored how real-world dermoscopic image transformations affect CNN robustness. OBJECTIVES: To investigate the consistency of melanoma risk assessment by two commercially available CNNs to help formulate recommendations for current clinical use. METHODS: A comparative cohort study was conducted from January to July 2022 at the Department of Dermatology, University Hospital Basel. Five dermoscopic images of 116 different lesions on the torso of 66 patients were captured consecutively by the same operator without deliberate rotation. Classification was performed by two CNNs (CNN-1/CNN-2). Lesions were divided into four subgroups based on their initial risk scoring and clinical dignity assessment. Reliability was assessed by variation and intraclass correlation coefficients. Excisions were performed for melanoma suspicion or two consecutively elevated CNN risk scores, and benign lesions were confirmed by expert consensus (n = 3). RESULTS: 117 repeated image series of 116 melanocytic lesions (2 melanomas, 16 dysplastic naevi, 29 naevi, 1 solar lentigo, 1 suspicious and 67 benign) were classified. CNN-1 demonstrated superior measurement repeatability for clinically benign lesions with an initial malignant risk score (mean variation coefficient (mvc): CNN-1: 49.5(±34.3)%; CNN-2: 71.4(±22.5)%; p = 0.03), while CNN-2 outperformed for clinically benign lesions with benign scoring (mvc: CNN-1: 49.7(±22.7)%; CNN-2: 23.8(±29.3)%; p = 0.002). Both systems exhibited lowest score consistency for lesions with an initial malignant risk score and benign assessment. In this context, averaging three initial risk scores achieved highest sensitivity of dignity assessment (CNN-1: 94%; CNN-2: 89%). Intraclass correlation coefficients indicated 'moderate'-to-'good' reliability for both systems (CNN-1: 0.80, 95% CI:0.71-0.87, p < 0.001; CNN-2: 0.67, 95% CI:0.55-0.77, p < 0.001). CONCLUSIONS: Potential user-induced image changes can significantly influence CNN classification. For clinical application, we recommend using the average of three initial risk scores. Furthermore, we advocate for CNN robustness optimization by cross-validation with repeated image sets. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04605822).