Publications, References, and Further Reading

The evidence for automated CLASI rests on two literatures: the validation of the CLASI instrument itself, and the peer-reviewed measurement methods behind the device's component models. This page collects both. How they combine, and what remains to be validated in CLE specifically, is discussed on the Clinical evidence page.

The CLASI instrument

Development and reliability. Albrecht J, Taylor L, Berlin JA, et al. The CLASI (Cutaneous Lupus Erythematosus Disease Area and Severity Index): an outcome instrument for cutaneous lupus erythematosus. Journal of Investigative Dermatology. 2005;125(5):889-894. PubMed

The original instrument. Introduced the separation of a reversible activity score (erythema, scale/hypertrophy, mucosal involvement, hair loss) from a cumulative damage score (dyspigmentation, scarring), with content validity assessed by a dermato-rheumatology panel and inter- and intra-rater reliability estimated on real patients.

Responsiveness and severity strata. Klein R, Moghadam-Kia S, LoMonico J, et al. Development of the CLASI as a tool to measure disease severity and responsiveness to therapy in cutaneous lupus erythematosus. Archives of Dermatology. 2011;147(2):203-208. PubMed

Established the activity severity strata used throughout these pages (mild 0–9, moderate 10–20, severe 21–70) and found that a clinically meaningful response corresponds to roughly a 4-point or 20% fall in the CLASI activity score.

Reliability across specialties and ages. Reliability and validity of the CLASI in paediatric cutaneous lupus, among paediatric dermatologists and rheumatologists. British Journal of Dermatology. 2019;180(1):165. Journal

Narrative review. Chakka S, et al. The CLASI, a validated tool for the evaluation of skin disease in lupus erythematosus: a narrative review. Annals of Translational Medicine. Journal

Contemporary context. Severity Scores for Cutaneous Lupus Erythematosus. Journal of Investigative Dermatology. Journal

The methods behind our CLASI components

The device measures the individual signs CLASI is built from, using models published in the indications they were developed for. None is CLE-specific, which is the boundary set out on the Clinical evidence page, but each documents the underlying measurement method and its reliability.

• Erythema, scale and induration are the intensity signs behind automated PASI and the acne composite; see the acne and psoriasis publications, including the peer-reviewed ALADIN work.
• Lesion detection and counting methodology is shared with the automated IHS4; see the hidradenitis suppurativa publications.
• Image quality is governed by DIQA (Dermatology Image Quality Assessment); see the DIQA validation.

Regulatory and quality context

The device is CE-marked and built on an ISO 13485-certified quality management system, with performance claims maintained in the technical documentation rather than asserted on these pages. The Compliance and security page covers the framework.

Further reading

📄️Scoring Methodology

Item-by-item technical detail on how the AI quantifies the CLASI Activity and CLASI Damage components, the 13-region structure, scale alignment between sign models and CLASI item scales, and how per-image values aggregate into a CLASI score.

📄️Imaging Protocol

Image capture protocol for cutaneous lupus erythematosus clinical trials, covering the 13-region CLASI capture set, target lesions, the metadata required to assemble a CLASI score, DIQA quality control, colour and scale calibration for erythema, pigmentation and lesion area, and facial anonymization.

📄️Clinical Evidence

The evidence base for automated CLASI in cutaneous lupus erythematosus. The CLASI instrument's own validation, the component models' validation in their source indications, feasibility findings on CLE imagery, and the validation pathway.

📄️Trial Workflow

End-to-end workflow for cutaneous lupus erythematosus severity endpoints, covering retrospective image analysis versus prospective CLASI reconstruction, protocol design, capture, scoring, review, longitudinal tracking, and EDC data export.

📄️Sample Outputs

What sponsors, CROs and investigators receive from a cutaneous lupus erythematosus assessment. A per-visit report with real device outputs, the repigmentation signal CLASI-D cannot express, segmentation overlays, and structured EDC export fields.

📄️Publications

Key references for automated CLASI in cutaneous lupus erythematosus. The CLASI instrument's development, validation and responsiveness literature, and the peer-reviewed methods behind the device's component measurements.

📄️Limitations

Transparent documentation of what AI CLASI component scoring can and cannot do in cutaneous lupus erythematosus, covering the items not derived from an image, the scarring and alopecia boundaries, region traceability, skin phototype, and CLE-specific validation status.