British Journal of Dermatology 2023; 00:1–8
MARIN DIT BERTOUD Q., BERTOLD C., EZZEDINE K., PANDYA A., CHEREL M., CASTILLO MARTINEZ A., SEGUY MA., ABDALLAH M., BAE JM., BÖHM M., PARSAD D., ROSMARIN D., WOLKERSTORFER A., BAHADORAN P., BLAISE M., DUGOURD PM., PHILIPPO V., DELAVAL JM., PASSERON T. (2023)
Université Côte d’Azur, CHU Nice, Department of Dermatology, Nice, France.
Department of Dermatology, AP-HP, Henri Mondor University Hospital, Créteil, France.
Université Paris Est (UPEC), EpiDermE Research Unit, Paris, France.
Palo Alto Foundation Medical Group, Sunnyvale, CA, USA.
Department of Dermatology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Department of Dermatology, Andrology and Venereology, Ain Shams University, Cairo, Egypt.
Department of Dermatology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Department of Dermatology, University of Münster, Münster, Germany.
Department of Dermatology, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
Department of Dermatology, Indiana University School of Medicine, Indianapolis, IN, USA.
Department of Dermatology, Netherlands Institute for Pigment Disorders, Amsterdam University Medical Centers, Amsterdam,
the Netherlands.
Université Côte d’Azur, INSERM, U1065, C3M, Nice, France.
Newtone Technologies, Research and Development, Lyon, France.
Abstract
Background Facial repigmentation is the primary outcome measure for most vitiligo trials. The Facial Vitiligo Area Scoring Index (F-VASI) score is often chosen as the primary outcome measure to assess the efficacy of treatments for facial vitiligo. Although useful, this scoring system remains subjective and has several limitations.
Objectives To assess the agreement and reliability of an algorithmic method to measure the percentage depigmentation of vitiligo on the face.
Methods We developed a dedicated algorithm called Vitil-IA® to assess depigmentation on standardized facial ultraviolet (UV) pictures. We then conducted a cross-sectional study using the framework of the ERASE trial (NCT04843059) in 22 consecutive patients attending a tertiary care centre for vitiligo. Depigmentation was analysed before any treatment and, for 7 of them, after 3 and 6 months of narrowband UVB treatment combined with 16 mg methylprednisolone, both used twice weekly. Interoperator and interacquisition repeatability measures were assessed for the algorithm. The results of the algorithmic measurement were then compared with the F-VASI and the percentage of depigmented skin scores assessed by 13 raters, including 7 experts in the grading of vitiligo lesions.
Results Thirty-one sets of pictures were analysed with the algorithmic method. Internal validation showed excellent reproducibility, with a variation of < 3%. The percentage of depigmentation assessed by the system showed high agreement with the percentage of depigmentation assessed by raters [mean error (ME) –11.94 and mean absolute error (MAE) 12.71 for the nonexpert group; ME 0.43 and MAE 5.57 for the expert group]. The intraclass correlation coefficient (ICC) for F-VASI was 0.45 [95% confidence interval (CI) 0.29–0.62] and 0.52 (95% CI 0.37–0.68) for nonexperts and experts, respectively. When the results were analysed separately for homogeneous and heterogeneous depigmentation, the ICC for homogeneous depigmentation was 0.47 (95% CI 0.31–0.77) and 0.85 (95% CI 0.72–0.94) for nonexperts and experts, respectively. When grading heterogeneous depigmentation, the ICC was 0.19 (95% CI 0.05–0.43) and 0.38 (95% CI 0.20–0.62) for nonexperts and experts, respectively.
Conclusions We demonstrated that the Vitil-IA algorithm provides a reliable assessment of facial involvement in vitiligo. The study underlines the limitations of the F-VASI score when performed by nonexperts for homogeneous vitiligo depigmentation, and in all raters when depigmentation is heterogeneous..
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© The Author(s) 2023.
