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      • Round 1
        • Item 0: Background & Action Plan
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          • task-3b10-legacy-pms-document-hierarchy-refactor
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            • Appraisal log — CRIT1–7 rolling table
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            • references
              • diagnostic-accuracy
                • Conic 2018 — Impact of melanoma surgical timing on survival (NCDB)
                • Daneshjou 2022 — Disparities in dermatology AI performance on a diverse clinical image set (DDI) [BALANCING]
                • Dick 2019 — Accuracy of computer-aided diagnosis of melanoma: a meta-analysis
                • Esteva 2017 — Dermatologist-level classification of skin cancer with deep neural networks
                • Freeman 2020 — Algorithm-based smartphone apps for skin cancer risk: BMJ systematic review [BALANCING]
                • Gershenwald 2017 — AJCC 8th edition: melanoma staging and survival gradient
                • Haenssle 2018 — Man against machine: CNN vs 58 dermatologists for melanoma recognition
                • Haenssle 2020 — Man against machine reloaded: market-approved CNN (Moleanalyzer Pro) vs 96 dermatologists
                • Han 2018 — Clinical-image classification for benign and malignant tumours (cross-ethnicity) [BALANCING]
                • Liu 2020 — A deep learning system for differential diagnosis of skin diseases
                • Salinas 2024 — Systematic review and meta-analysis of AI vs. clinicians for skin cancer diagnosis
                • Tschandl 2020 — Human–computer collaboration for skin cancer recognition
                • Winkler 2023 — Dermatologists cooperating with a CNN: prospective clinical study
              • referral-optimisation
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            • Research prompts — external deep-research tools
            • Surrogate-Endpoint Validity in Dermatology AI — Structured Literature Review
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        • Coverage matrix
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  • diagnostic-accuracy
  • Gershenwald 2017 — AJCC 8th edition: melanoma staging and survival gradient

Gershenwald 2017 — AJCC 8th edition: melanoma staging and survival gradient

Citation​

Gershenwald JE, Scolyer RA, Hess KR, Sondak VK, Long GV, Ross MI, et al. Melanoma staging: evidence-based changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin. 2017 Nov;67(6):472–492. DOI: 10.3322/caac.21409. PMID 29028110.

Study design and population​

Pooled international retrospective and prospective cohort underpinning the AJCC 8th edition melanoma staging system. >46,000 stage I–III melanoma patients from 10 international centres in the International Melanoma Database and Discovery Platform.

Reported metrics​

5-year melanoma-specific survival (MSS) by substage:

  • IA 99 %; IB 97 %; IIA 94 %; IIB 87 %; IIC 82 %
  • IIIA 93 %; IIIB 83 %; IIIC 69 %; IIID 32 %

Per-stratum 95 % CIs in primary tabular data. Tumour thickness (Breslow), ulceration and N-status confirmed as independent prognostic factors.

Surrogate-to-outcome linkage​

Provides the load-bearing quantitative anchor for the entire Pillar-1 diagnostic-accuracy-to-outcome chain: stage-at-detection is the dominant determinant of melanoma-specific survival. Any intervention (including AI-assisted diagnosis) that moves detection to earlier T-stage translates, via this gradient, into measurable melanoma-specific survival gain. This is the regulator-recognised causal link that licenses diagnostic accuracy as a proxy in AI-dermatology devices targeting melanoma.

CRIT1–7 appraisal​

CriterionScoreJustification
CRIT1 Relevance3Foundational evidence for the stage-to-survival link anchoring the surrogate argument.
CRIT2 Methodology3Pooled international multi-centre cohort; AJCC evidence base; very large sample.
CRIT3 Reporting3Substage MSS with CIs; Cox regression with adjusted hazard ratios.
CRIT4 Applicability3Contemporary staging system; regulator-recognised.
CRIT5 Evidence weight2Very large pooled cohort (not RCT, not meta-analysis — but highest-weight observational evidence available for this question).
CRIT6 Risk of bias2Retrospective pooling; heterogeneity across centres; pre-immunotherapy adjuvant era for earlier survival readouts.
CRIT7 Contribution3Central quantitative anchor — without this, the diagnostic-accuracy surrogate lacks an outcome linkage.

Aggregate: very strong.

Limitations and notes​

Retrospective pooling; heterogeneity; primarily Caucasian populations; pre-immunotherapy adjuvant-treatment era for earlier cohorts.

Strength as anchor​

Essential. This is the quantitative anchor for the stage-at-detection → survival surrogate-to-outcome claim. Without Gershenwald 2017 (or the preceding Balch 2001 / AJCC 7th), the directional argument is qualitative rather than quantitative.

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Haenssle 2018 — Man against machine: CNN vs 58 dermatologists for melanoma recognition
  • Citation
  • Study design and population
  • Reported metrics
  • Surrogate-to-outcome linkage
  • CRIT1–7 appraisal
  • Limitations and notes
  • Strength as anchor
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