The Myositis Clinical Trials Consortium: an international collaborative initiative to promote clinical trials in adult and juvenile myositis
Bibliographic record
Abstract
Idiopathic inflammatory myopathies (IIM), or myositis, are a heterogeneous group of systemic autoimmune disorders that are associated with significant morbidity and mortality. Conducting high-quality clinical trials in IIM is challenging due to the rare and variable presentations of disease. To address this challenge, the Myositis Clinical Trials Consortium (MCTC) was formed. MCTC is a collaborative international alliance dedicated to facilitating, promoting, coordinating and conducting clinical trials and related research in IIM. This partnership works to advance the discovery of effective evidence-based treatments for IIM by integrating a diverse group of clinical investigators, research professionals, medical centres, patient groups, and industry partners. The Steering Committee, Core Group, and Paediatric Subcommittee of MCTC are comprised of myositis experts and junior investigators from around the world, representing a diversity of genders, geographies, and subspecialties. MCTC works alongside other current myositis organisations to complement existing work by concentrating on the operationalisation of clinical trials. Our pilot Myositis Investigators' Information Survey gathered responses from 173 myositis investigators globally and found considerable variability in proficiency with outcome measures, geographic disparities in patient recruitment, and a significant disconnect between investigators' routine myositis patient load and clinical trial enrolment. MCTC will meet the need to support and diversify myositis clinical trials by facilitating trial planning, feasibility assessments, site selection, and the training and mentoring of junior investigators/centres to establish their readiness for clinical trial participation. Through experienced leadership, strategic collaborations, and interdisciplinary discussions, MCTC will establish standards for IIM clinical trial design, protocols, and outcome measures in myositis.
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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 | 0.024 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".