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                • EMA 2004 — Guideline on clinical investigation of medicinal products for psoriasis (CHMP/EWP/2454/02)
                • Fink 2018 — Inter- and intra-observer variability of image-based PASI
                • Huang 2023 — AI-based PASI severity assessment: real-world study (SkinTeller)
                • King 2022 — Baricitinib BRAVE-AA1 / BRAVE-AA2 (SALT as FDA / EMA primary endpoint)
                • Mattei 2014 — PASI ↔ DLQI correlation in biologic RCTs (r² = 0.80)
                • Mrowietz 2011 — European treat-to-target consensus for moderate-to-severe psoriasis
                • Olsen 2004 — Alopecia areata investigational assessment guidelines (SALT definition, NAAF)
                • Schaap 2022 — CNN-based automated PASI scoring
                • Schmitt 2014 — HOME IV: EASI as core instrument for clinical signs of atopic eczema
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  • Fink 2018 — Inter- and intra-observer variability of image-based PASI

Fink 2018 — Inter- and intra-observer variability of image-based PASI

Citation​

Fink C, Alt C, Uhlmann L, Klose C, Enk A, Haenssle HA. Intra- and interobserver variability of image-based PASI assessments in 120 patients suffering from plaque-type psoriasis. J Eur Acad Dermatol Venereol. 2018 Aug;32(8):1314–1319. DOI: 10.1111/jdv.14960. PMID 29569769.

Study design and population​

Prospective observational reliability study. 120 adults with plaque psoriasis; total-body images scored by 3 trained physicians; 720 image-based PASI scores across two rounds. University Hospital Heidelberg.

Reported metrics​

  • Inter-rater ICC 0.895
  • Intra-rater mean ICC 0.877
  • Mean absolute difference 3.3 PASI points between raters
  • Sub-score variability greatest for induration and scaling; lowest for BSA
  • 95 % CIs not reported

Surrogate-to-outcome linkage​

Even trained physicians produce ~3-point PASI variability between raters — enough to flip treatment-escalation decisions at borderline thresholds (PASI ≥ 10 for biologic eligibility, PASI-75 vs. PASI-90 response). Manual measurement error is the clinical headroom that automated / AI scoring addresses; supports the operational claim that AI severity scoring reduces decision-threshold uncertainty.

CRIT1–7 appraisal​

CriterionScoreJustification
CRIT1 Relevance3Direct — manual-PASI reliability ceiling, the denominator for AI-scoring claims.
CRIT2 Methodology2Prospective, single-centre, trained raters only.
CRIT3 Reporting2Point-estimate ICCs and MAD reported; no 95 % CIs.
CRIT4 Applicability3Image-based, matches the CDS modality.
CRIT5 Evidence weight1Methodology / validation study, prospective.
CRIT6 Risk of bias2Only 3 raters; single centre; all-Caucasian cohort; image-based not live PASI.
CRIT7 Contribution3Core anchor for the reliability-gap claim that motivates AI-assisted scoring.

Aggregate: strong.

Limitations and notes​

Small rater sample (n = 3); single centre; head region excluded; all-Caucasian cohort.

Strength as anchor​

Strong — one of the most-cited modern PASI reliability studies and the direct motivation for automated scoring. Complements Gourraud 2012 (simulation-based demonstration that manual PASI crosses therapeutic thresholds between raters).

Previous
EMA 2004 — Guideline on clinical investigation of medicinal products for psoriasis (CHMP/EWP/2454/02)
Next
Huang 2023 — AI-based PASI severity assessment: real-world study (SkinTeller)
  • Citation
  • Study design and population
  • Reported metrics
  • Surrogate-to-outcome linkage
  • CRIT1–7 appraisal
  • Limitations and notes
  • Strength as anchor
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