Measures of Response in Clinical Trials of Systemic Sclerosis: The Combined Response Index for Systemic Sclerosis (CRISS) and Outcome Measures in Pulmonary Arterial Hypertension Related to Systemic Sclerosis (EPOSS)
Bibliographic record
Abstract
There have been steady efforts to develop a combined response index for systemic sclerosis (CRISS). A parallel and equally successful effort has been made by an Expert Panel on Outcome Measures in PAH related to Systemic Sclerosis (EPOSS) to measure effect in treatment of pulmonary arterial hypertension of systemic sclerosis (PAH-SSc). CRISS conducted a Delphi process combined with expert review to identify 11 candidate domains for inclusion in a core set of outcomes for SSc clinical trials: soluble biomarkers, cardiac, digital ulcers, gastrointestinal, global health, health related quality of life (HRQOL) and function, musculoskeletal, pulmonary, Raynaud's, renal, and skin. Tools within domains were also agreed upon. Concentrating on one aspect of disease, PAH, EPOSS also conducted a Delphi process and judged the following domains as the most appropriate for randomized controlled trials in PAH-SSc: lung vascular/pulmonary arterial pressure, cardiac function, exercise testing; severity of dyspnea, discontinuation of treatment; quality of life/activities of daily living; global state; and survival. Possible useful tools within each domain were also agreed on. Patient derived, physician derived, and objective measures of response will be included and combined with the idea that each reflects different aspects of PAH (EPOSS) and overall disease (CRISS) although this assumption may not prove true and can be separated if statistically and clinically valid to do so. In either case, prospective studies will require measurement of all domains, and tools are required and will be developed to define appropriate combined measures of response. CRISS and EPOSS are being developed through the OMERACT process. Through Delphi process and literature review significant progress has been made for both indices, and prospective data are being collected.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".