The American College of Rheumatology Provisional Composite Response Index for Clinical Trials in Early Diffuse Cutaneous Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: Early diffuse cutaneous systemic sclerosis (dcSSc) is characterized by rapid changes in the skin and internal organs. The objective of this study was to develop a composite response index in dcSSc (CRISS) for use in randomized controlled trials (RCTs). METHODS: We developed 150 paper patient profiles with standardized clinical outcome elements (core set items) using patients with dcSSc. Forty scleroderma experts rated 20 patient profiles each and assessed whether each patient had improved or not improved over a period of 1 year. Using the profiles for which raters had reached a consensus on whether the patients were improved versus not improved (79% of the profiles examined), we fit logistic regression models in which the binary outcome referred to whether the patient was improved or not, and the changes in the core set items from baseline to followup were entered as covariates. We tested the final index in a previously completed RCT. RESULTS: Sixteen of 31 core items were included in the patient profiles after a consensus meeting and review of test characteristics of patient-level data. In the logistic regression model in which the included core set items were change over 1 year in the modified Rodnan skin thickness score, the forced vital capacity, the patient and physician global assessments, and the Health Assessment Questionnaire disability index, sensitivity was 0.982 (95% confidence interval 0.982-0.983) and specificity was 0.931 (95% confidence interval 0.930-0.932), and the model with these 5 items had the highest face validity. Subjects with a significant worsening of renal or cardiopulmonary involvement were classified as not improved, regardless of improvements in other core items. With use of the index, the effect of methotrexate could be differentiated from the effect of placebo in a 1-year RCT (P = 0.02). CONCLUSION: We have developed a CRISS that is appropriate for use as an outcome assessment in RCTs of early dcSSc.
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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 | 0.296 | 0.481 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".