Establishment of a consensus definition for mesenchymal stromal cells (MSC) and reporting guidelines for clinical trials of MSC therapy: a modified Delphi study protocol
Bibliographic record
Abstract
INTRODUCTION: Despite being more than two decades of research, mesenchymal stromal cell (MSC) treatments are still struggling to cross the translational gap. Two key issues that likely contribute to these failures are (1) the lack of clear definition for MSC and (2) poor quality of reporting in MSC clinical studies. To address these issues, we propose a modified Delphi study to establish a consensus definition for MSC and reporting guidelines for clinical trials of MSC therapy. METHODS AND ANALYSIS: We will conduct a three-round international modified Delphi survey. Findings from a recent scoping review examining how MSCs are defined and reported in preclinical and clinical studies were used to draft the initial survey for round 1 of our Delphi. Participants will include a 'core group' of individuals as well as researchers whose work was captured in our scoping review. The core group will include stakeholders from different research fields including developmental biology, translational science, research methods, regulatory practices, scholarly journal editing and industry. The first two survey rounds will be online, and the final round will take place in person. Each participant will be asked to rate their agreement on potential MSC definition characteristics and reporting items using a Likert scale. After each round, we will analyse the data to determine which items have reached consensus for inclusion/exclusion, and then develop a revised questionnaire for any new items, or items that did not reach consensus. ETHICS AND DISSEMINATION: This study received ethical approval from the Ottawa Health Research Network Research Ethics Board. To support the dissemination of our findings, we will use an evidence-based 'integrated knowledge translation' approach to engage knowledge users from the inception of the research. This will allow us to develop a tailored end-of-project knowledge translation plan to support and ensure dissemination and implementation of the Delphi results.
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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 | 0.297 | 0.222 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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; the direct Gemma label and the distilled Codex classifier 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".