Dataset Information

Validation of a Patient Global Assessment for extent, severity and impact to define the severity strata for the Self Assessment Vitiligo Extent Score (SA-VES).

ABSTRACT:

Background

The Self Assessment Vitiligo Extent Score (SA-VES) is a validated, patient-reported outcome measure to assess the body surface area affected with vitiligo. Information on how to translate the obtained score into extent, severity and impact strata (mild-moderate-severe) is still lacking. Stratification is helpful to define inclusion criteria for trials, enables comparison and pooling of trial results and can be used for epidemiological research.

Objectives

The aim was to develop extent, severity and impact strata for the SA-VES based on validated anchor-based questions.

Methods

In total, 315 patients with vitiligo (non-segmental; age ? 16) recruited at the Ghent University Hospital (Belgium) completed a questionnaire that was conducted in cooperation with the Dutch Society for vitiligo patients to ensure content validity. First three anchor questions included in the questionnaire [Patient Global Assessment (PtGA) for vitiligo extent, severity and impact] were assessed for content validity, construct validity and intrarater reliability. Subsequently, the PtGAs were used to stratify the SA-VES based on ROC analysis.

Results

For all PtGAs (PtGA extent, PtGA severity, PtGA impact), at least 75% of hypotheses evaluated for construct validity were confirmed. Intrarater reliability of all PtGAs was good to excellent (ICCs PtGA extent: 0.623; PtGA severity: 0.828; PtGA impact: 0.851). The optimal cut-off values of the SA-VES between the three global categories (mild/limited - moderate - severe/extensive) were 1.05% and 6.45% based on PtGA extent, 2.07% and 4.8% based on PtGA severity and 2% and 3.35% based on PtGA impact.

Conclusion

This study provides the first guide for the interpretation of the numerical output obtained by the SA-VES (vitiligo extent) and enables the translation into a global vitiligo grading for extent, severity and impact. As patients' interpretation of vitiligo extent, severity and impact may vary amongst patients worldwide, future international studies will be required.

SUBMITTER: van Geel N

PROVIDER: S-EPMC7818448 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Validation of a Patient Global Assessment for extent, severity and impact to define the severity strata for the Self Assessment Vitiligo Extent Score (SA-VES).

van Geel N N Uitentuis S E SE Zuidgeest M M Wolkerstorfer A A Bekkenk M W MW Moock C C Van Goethem C C Verlaeckt E E Smet C C Grine L L Speeckaert R R

Journal of the European Academy of Dermatology and Venereology : JEADV 20200901 1

<h4>Background</h4>The Self Assessment Vitiligo Extent Score (SA-VES) is a validated, patient-reported outcome measure to assess the body surface area affected with vitiligo. Information on how to translate the obtained score into extent, severity and impact strata (mild-moderate-severe) is still lacking. Stratification is helpful to define inclusion criteria for trials, enables comparison and pooling of trial results and can be used for epidemiological research.<h4>Objectives</h4>The aim was to ...[more]

PMID: 32452565

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Project description:BackgroundWe aimed to establish and validate a deep learning-based hybrid artificial intelligence (AI) model for the objective morphometric and colorimetric assessment of vitiligo lesions.MethodsTwo main datasets containing curated images of vitiligo lesions from Chinese patients (Fitzpatrick skin types III or IV) were established, including one with 2,720 images for lesion localization study and the other with 1,262 images for lesion segmentation study. Besides, an additional test set containing 145 images of vitiligo lesions from other Fitzpatrick skin types (I, II, or V) was also generated. A 3-stage hybrid model was constructed. YOLO v3 (You Only Look Once, v3) architecture was trained and validated to classify and localize vitiligo lesions, with sensitivity and error rate as primary performance outcomes. Then a segmentation study comparing 3 deep convolutional neural networks (DCNNs), Pyramid Scene Parsing Network (PSPNet), UNet, and UNet++, was carried out based on the Jaccard index (JI). The architecture with the best performance was integrated into the model. Three add-on metrics, namely VAreaA, VAreaR, and VColor were finally developed to measure absolute, relative size changes and pigmentation, respectively. Agreement between the AI model and dermatologist evaluators were assessed.ResultsThe sensitivity of the YOLO v3 architecture to detect vitiligo lesions was 92.91% with an error rate of 14.98%. The UNet++ architecture outperformed the others in the segmentation study (JI, 0.79) and was integrated into the model. On the additional test set, however, the model achieved a lower detection sensitivity (72.41%) and a lower segmentation score (JI, 0.69). With respect to size changes, no difference was observed between the AI model, trained dermatologists (W=0.812, P<0.05), and Photoshop analysis (P=0.075, P=0.212 respectively), which all displayed good concordance.ConclusionsWe developed a novel, convenient, objective, and quantitative deep learning-based hybrid model which simultaneously evaluated both morphometric and colorimetric vitiligo lesions from patients with Fitzpatrick skin types III or IV, rendering it suitable for the assessment of severity of vitiligo lesions in Asians in both clinic and research scenarios. More work is also warranted for its use in other ethnic skin groups.

Project description:BackgroundThe associations between disease activity and several clinical signs in vitiligo have been described, but a widely accepted and validated scoring system is lacking.ObjectivesTo validate the Vitiligo Signs of Activity Score (VSAS) for physicians.MethodsThree visible clinical signs were scored on 15 body locations: confetti-like depigmentation (c), Koebner phenomenon (k) and hypochromic areas/borders (h). The inter- and intrarater reliability of the global VSAS and VSAS subscores (c-VSAS, k-VSAS and h-VSAS) were tested by four and three raters (physicians), respectively. Construct validity and feasibility were evaluated.ResultsThe VSAS demonstrated good inter-rater reliability, with an intraclass correlation coefficient (ICC) of 0·87 in the first round and 0·90 in the second round. The intrarater reliability ICCs were all ≥ 0·86. The inter-rater reliabilities of the subscores were excellent for c-VSAS and fair for k-VSAS and h-VSAS (ICC 0·83, 0·51 and 0·53, respectively, in the first round). Evidence for construct validity was provided. The completion time by the raters (median 2·18 min per patient) improved during the second round (median 1·33 min per patient). A limitation of the study is the low number of patients, mainly of skin phototypes II-III, from a single tertiary centre.ConclusionsThe VSAS appears to be a valid and reliable instrument to score visible clinical signs linked to disease activity in a standardized way. What is already known about this topic? Evidence exists for a possible link between several visible clinical signs in vitiligo and disease activity. A widely accepted and validated scoring system to quantify these clinical signs is lacking. What does this study add? The Vitiligo Signs of Activity Score (VSAS) underwent preliminary validation and may assist quantification of visible clinical signs linked to disease activity in a standardized way in clinical practice and trials. What are the clinical implications of this work? VSAS may be used for future trials that aim to establish the clinical significance of the specific visible clinical signs in vitiligo in a more controlled setting. Linked Comment: Eleftheriadou. Br J Dermatol 2020; 183:801-802.

Dataset Information

Validation of a Patient Global Assessment for extent, severity and impact to define the severity strata for the Self Assessment Vitiligo Extent Score (SA-VES).

Background

Objectives

Methods

Results

Conclusion

Publications

Validation of a Patient Global Assessment for extent, severity and impact to define the severity strata for the Self Assessment Vitiligo Extent Score (SA-VES).

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