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Comparative Study
. 2019 Feb;180(2):390-396.
doi: 10.1111/bjd.17200. Epub 2018 Oct 14.

Precision and reproducibility of automated computer-guided Psoriasis Area and Severity Index measurements in comparison with trained physicians

Affiliations
Comparative Study

Precision and reproducibility of automated computer-guided Psoriasis Area and Severity Index measurements in comparison with trained physicians

C Fink et al. Br J Dermatol. 2019 Feb.

Abstract

Background: The Psoriasis Area and Severity Index (PASI) represents the gold standard for psoriasis severity assessments but is limited by its subjectivity and low intra- and inter-rater consistency.

Objectives: To investigate the precision and reproducibility of automated, computer-guided PASI measurements (ACPMs) in comparison with three trained physicians.

Methods: This was a comparative observational study assessing ACPMs attained by automated total-body imaging and computerized digital image analysis in a cohort of 120 patients affected by plaque psoriasis of various severities. The level of agreement between ACPMs and physicians' PASI measurements was calculated by the intraclass correlation coefficient (ICC). The reproducibility of ACPMs in comparison with physicians' PASI measurements was investigated by performing two successive 'repeat PASI calculations' in the same patients.

Results: The agreement between ACPMs and physicians' PASI calculations in 120 fully evaluable patients was high (ICC 0·86, 95% confidence interval 0·80-0·90, mean absolute difference 2·5 PASI points). Repeat ACPMs to measure the reproducibility showed an excellent ICC of 0·99 (95% confidence interval 0·98-0·99) with a mean absolute difference of 0·5 PASI points. The ACPMs thus outperformed the three physicians for intrarater reliability (mean ICC 0·86).

Conclusions: The results of this first clinical study investigating ACPMs in 120 patients with psoriasis indicate a similar precision and higher reproducibility in comparison with trained physicians. Limitations arise from poorly observable body sites and from patients unable to attain predefined postures during automated image acquisition.

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