Agreement Between Physician Evaluation and the Composite Response Index in Diffuse Cutaneous Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: Diffuse cutaneous systemic sclerosis (SSc) is a highly heterogeneous disease. A provisionally approved Composite Response Index in diffuse cutaneous SSc (CRISS) was developed as a 1-year outcome measure for clinical trials. Our goal was to further validate the CRISS by examining agreement between CRISS definitions for improved/non-improved with physicians' evaluation of disease. METHODS: Patient profiles from a large observational cohort were created for 50 random diffuse cutaneous SSc patients of <5 years disease duration with improved CRISS scores after 1 year and 50 with non-improved CRISS scores. Profiles described disease features used during the initial CRISS development at baseline and at 1 year. Each profile was independently rated by 3 expert physicians. Majority opinion determined whether a patient was improved or not improved, and kappa agreement with the CRISS cutoff of 0.6 was calculated. RESULTS: Patients had mean ± SD disease duration of 2.2 ± 1.3 years. There was substantial agreement between the physician majority opinion about each case and the CRISS (κ = 0.76 [95% confidence interval (95% CI) 0.64-0.88]). The agreement between each individual physician opinion and the CRISS was also substantial (κ = 0.70 [95% CI 0.62-0.78]). All CRISS non-improvers were also rated as non-improved by physician majority; however, 12 CRISS improvers were rated as non-improved by physicians. CONCLUSION: There was substantial agreement between the dichotomous CRISS rating and physician assessment of diffuse cutaneous SSc patients after 1 year. This supports the use of a CRISS cutoff at 0.6 for improvement versus non-improvement, although the CRISS tended to rate more patients as improved than did physicians.
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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 | 0.040 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".