Developing classification criteria for skin‐predominant dermatomyositis: the Delphi process
Bibliographic record
Abstract
BACKGROUND: The European League Against Rheumatism/American College of Rheumatology classification criteria for inflammatory myopathies are able to classify patients with skin-predominant dermatomyositis (DM). However, approximately 25% of patients with skin-predominant DM do not meet two of the three hallmark skin signs and fail to meet the criteria. OBJECTIVES: To develop a set of skin-focused classification criteria that will distinguish cutaneous DM from mimickers and allow a more inclusive definition of skin-predominant disease. METHODS: An extensive literature review was done to generate items for the Delphi process. Items were grouped into categories of distribution, morphology, symptoms, antibodies, histology and contextual factors. Using REDCap™, participants rated these items in terms of appropriateness and distinguishing ability from mimickers. The relevance score ranged from 1 to 100, and the median score determined a rank-ordered list. A prespecified median score cut-off was decided by the steering committee and the participants. There was a pre-Delphi and two rounds of actual Delphi. RESULTS: There were 50 participating dermatologists and rheumatologists from North America, South America, Europe and Asia. After a cut-off score of 70 during the first round, 37 of the initial 54 items were retained and carried over to the next round. The cut-off was raised to 80 during round two and a list of 25 items was generated. CONCLUSIONS: This project is a key step in the development of prospectively validated classification criteria that will create a more inclusive population of patients with DM for clinical research. What's already known about this topic? Proper classification of patients with skin-predominant dermatomyositis (DM) is indispensable in the appropriate conduct of clinical/translational research in the field. The only validated European League Against Rheumatism/American College of Rheumatology criteria for idiopathic inflammatory myopathies are able to classify skin-predominant DM. However, a quarter of amyopathic patients still fail the criteria and does not meet the disease classification. What does this study add? A list of 25 potential criteria divided into categories of distribution, morphology, symptomatology, pathology and contextual factors has been generated after several rounds of consensus exercise among experts in the field of DM. This Delphi project is a prerequisite to the development of a validated classification criteria set for skin-predominant DM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.247 | 0.227 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".