Dataset Information

The Physician Global Assessment and Body Surface Area composite tool is a simple alternative to the Psoriasis Area and Severity Index for assessment of psoriasis: post hoc analysis from PRISTINE and PRESTA.

ABSTRACT: Background:The product of Physician Global Assessment and Body Surface Area (PGA × BSA) is a new outcome measure for psoriasis severity and response to therapy. The objective of this study was to evaluate PGA × BSA as an alternative to Psoriasis Area and Severity Index (PASI) for psoriasis assessments. Methods:The relationship between PASI and PGA × BSA was assessed in a post hoc analysis of pooled data from the PRISTINE (NCT00663052) and PRESTA (NCT00245960) trials in patients with moderate-to-severe psoriasis who received etanercept 50 mg/week. Data were analyzed using Spearman and intra-class correlation coefficients, effect sizes, scatterplots, Bland-Altman plots, and Kappa statistics. Results:Spearman correlations at baseline, week 12, and week 24 were strong for PGA × BSA versus PASI (r=0.78, 0.87, and 0.90, respectively; all P<0.0001) as were intra-class correlations (0.76 [95% confidence interval 0.73-0.80], 0.80 [0.76-0.83], and 0.85 [0.82-0.87], respectively). The effect size was -1.53 for PASI and -0.94 for PGA × BSA (baseline to week 24). Scatterplots and Bland-Altman plots detected a trend across the range of measurement. Kappa statistics (at 12 and 24 weeks) between PASI50/75/90 and 50/75/90% improvement in PGA × BSA showed good agreement (0.58-0.69 at week 12 and 0.63-0.67, respectively; all P<0.0001). At baseline, the Spearman correlation coefficients were 0.96, 0.51, 0.19, and 0.17 for PGA × BSA versus BSA, PGA, Patient Global Assessment, and Dermatology Life Quality Index, respectively (all P<0.001). Conclusion:PGA × BSA has advantages over PASI for measuring moderate-to-severe psoriasis; it is intuitive, sensitive, and easy to use.

SUBMITTER: Walsh JA

PROVIDER: S-EPMC6181091 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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The Physician Global Assessment and Body Surface Area composite tool is a simple alternative to the Psoriasis Area and Severity Index for assessment of psoriasis: post hoc analysis from PRISTINE and PRESTA.

Walsh Jessica A JA Jones Heather H Mallbris Lotus L Duffin Kristina Callis KC Krueger Gerald G GG Clegg Daniel O DO Szumski Annette A

Psoriasis (Auckland, N.Z.) 20181008

<h4>Background</h4>The product of Physician Global Assessment and Body Surface Area (PGA × BSA) is a new outcome measure for psoriasis severity and response to therapy. The objective of this study was to evaluate PGA × BSA as an alternative to Psoriasis Area and Severity Index (PASI) for psoriasis assessments.<h4>Methods</h4>The relationship between PASI and PGA × BSA was assessed in a post hoc analysis of pooled data from the PRISTINE (NCT00663052) and PRESTA (NCT00245960) trials in patients wi ...[more]

PMID: 30324088

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Project description:BackgroundRisankizumab has demonstrated durable, high rates of efficacy in patients with moderate-to-severe plaque psoriasis as assessed by the achievement of relative Psoriasis Area and Severity Index (PASI) improvement and Dermatology Life Quality Index (DLQI) 0/1.ObjectivesThe aim of this post hoc analysis is to assess the achievement of absolute PASI thresholds and related improvements in health-related quality of life (HRQoL) in patients with moderate-to-severe plaque psoriasis treated with (i) risankizumab compared with ustekinumab, and (ii) long-term (>52 weeks to 172 weeks) risankizumab.MethodsData from patients randomised to 150 mg risankizumab or 45 or 90 mg ustekinumab in replicate randomised controlled trials UltIMMa-1 and UltIMMa-2 were analysed for the achievement of absolute PASI thresholds PASI ≤ 3, PASI ≤ 1, and PASI = 0, time to achieve these thresholds, and combined PASI and DLQI endpoints. Data from pat ients initially randomised to risankizumab who continued on risankizumab in the open-label extension study LIMMitless were analysed for the achievement of absolute PASI levels, mean DLQI scores, and DLQI 0/1.ResultsSignificantly greater proportions of patients treated with risankizumab compared with ustekinumab achieved PASI ≤ 3, PASI ≤ 1, and PASI = 0, as well as combined endpoints for absolute PASI and DLQI [(PASI ≤ 3 and DLQI ≤ 5) or (PASI ≤ 1 and DLQI 0/1)]. The median time to first achieve PASI ≤ 3, PASI ≤ 1, and PASI = 0 was significantly lower for risankizumab-treated patients compared with ustekinumab-treated patients. Among patients treated with long-term risankizumab, more than 90% achieved PASI ≤ 3 though week 172 and more than 80% achieved DLQI 0/1. Low absolute PASI scores corresponded with low mean absolute DLQI scores through week 172 of continuous risankizumab treatment.ConclusionsRisankizumab treatment demonstrated high rates of rapid and durable efficacy as measured by absolute PASI thresholds and improvements in patient HRQoL.

Project description:BackgroundThe 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.ObjectivesTo 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.MethodsImaging 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.ResultsIntraclass 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).ConclusionsConvolutional 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.

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Project description:Importance:Although physician visual assessment (PVA) of stenosis severity is a standard clinical practice to support decisions for coronary revascularization, there are concerns about its accuracy. Objective:To compare PVA with quantitative coronary angiography (QCA) as a means of assessing stenosis severity among patients undergoing percutaneous coronary intervention (PCI) in China. Design, Setting, and Participants:A cross-sectional study (2012-2013) of a random subset of 1295 patients from the China Patient-centered Evaluative Assessment of Cardiac Events (PEACE) Prospective PCI Study was carried out. The PEACE Prospective PCI study recruited a consecutive sample of patients undergoing PCI at 35 hospitals in 18 provinces of China. The coronary angiograms of this subset of participants were reviewed using QCA by 2 independent core laboratories blinded to PVA readings. Main Outcomes and Measures:Differences between PVA and QCA assessments of stenosis severity for lesions for which PCI was performed and variation of these differences among hospitals and physicians, stratified by the diagnosis of acute myocardial infarction (AMI). Results:In patients without AMI, the mean (SD) age was 62 (10) years, and 217 (31.5%) were women; in patients with AMI, the mean (SD) age was 60 (11) years, and 153 (25.2%) were women. The mean (SD) percent diameter stenosis by PVA was 16.0% (11.5%) greater than that by QCA in patients without AMI and 10.2% (12.3%) in those with AMI (P < .001 for both comparisons). In patients without AMI, of 837 lesions with 70% or more stenosis by PVA, 427 (50.6%) were less than 70% by QCA; in patients with AMI, similar patterns were observed to a lesser extent. Among patients without AMI, only 4 (0.47%) lesions were additionally assessed with fractional flow reserve. Among 30 hospitals, the difference between PVA and QCA readings of stenosis severity varied from 7.6% (95% CI, 0.4%-14.7%) to 21.3% (95% CI, 17.1%-24.9%) among non-AMI patients. Across 57 physicians, this difference varied from 6.9% (95% CI, -1.4%-15.3%) to 26.4% (95% CI, 21.5%-31.4%). Conclusions and Relevance:For coronary lesions treated with PCI in China, PVA reported substantially higher readings of stenosis severity than QCA, with large variation across hospitals and physicians. These findings highlight the need to improve the accuracy of information used to guide treatment decisions in catheterization laboratories.

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Dataset Information

The Physician Global Assessment and Body Surface Area composite tool is a simple alternative to the Psoriasis Area and Severity Index for assessment of psoriasis: post hoc analysis from PRISTINE and PRESTA.

Publications

The Physician Global Assessment and Body Surface Area composite tool is a simple alternative to the Psoriasis Area and Severity Index for assessment of psoriasis: post hoc analysis from PRISTINE and PRESTA.

Similar Datasets

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