MétaCan
Menu
Back to cohort
Record W4403897136 · doi:10.1016/j.jcyt.2024.10.008

Delphi-driven consensus definition for mesenchymal stromal cells and clinical reporting guidelines for mesenchymal stromal cell–based therapeutics

2024· article· en· W4403897136 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCytotherapy · 2024
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsToronto Rehabilitation InstituteUniversity Health NetworkHealth CanadaOttawa HospitalSimon Fraser UniversityUniversity of OttawaUniversity of British ColumbiaChildren's Hospital of Eastern Ontario
FundersHealth CanadaLeonard M. Miller School of Medicine, University of MiamiUniversity of California Davis School of MedicineLeonard M. Miller School of MedicineUniversity at BuffaloMansoura UniversityUniversität Duisburg-EssenUniversidade Federal do Rio de JaneiroUniversidad de AntioquiaNational Institute of Environmental Health SciencesFaculty of Medicine and Health, University of SydneyBerlin Institute of HealthStem Cell NetworkRWTH Aachen UniversityQueen's UniversityUniversiteit MaastrichtUniversity of MiamiUniversiti Tunku Abdul RahmanUniversity of GalwayMcGovern Medical SchoolSimon Fraser UniversityQueen's University Belfast
KeywordsDelphiMedical physicsDelphi methodIntensive care medicineMedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND AIMS: Despite promising results in pre-clinical studies, mesenchymal stromal cells (MSCs) face significant challenges in clinical translation. A scoping review by our group highlighted two key issues contributing to this gap: (i) lack of a clear and consensus definition for MSCs and (ii) under-reporting of critical parameters in MSC clinical studies. To address these issues, we conducted a modified Delphi study to establish and implement a consensus definition for MSCs and develop reporting guidelines for MSC clinical studies. METHODS: A steering committee of 22 international experts, including stakeholders from different MSC research fields, participated in the three Delphi rounds. For the first round, to obtain a broad perspective, additional investigators recommended by the steering committee were invited to participate. The first two rounds consisted of online surveys, whereas the third round took the form of a virtual meeting. Participants were asked to rate a series of potential defining characteristics of MSCs and items for reporting guidelines. Consensus was defined as at least 80% of the participants rating the item in the same category of importance. RESULTS: Eighty-seven international participants participated in the first round survey (spring 2023), 17 participants participated in the second online survey (fall 2023) and 15 participants participated in the final virtual consensus meeting (January 2024). For the MSC definition, 20 items were considered and nine reached consensus. Items included terminology (one item), cell marker expression (five items), tissue origin (one item), stemness (one item) and description of critical quality attributes (one item). For the reporting guidelines, with the 28 initial items and the additional items suggested during round 1, a total of 33 items to report were included. This included items on MSC intervention group and control (e.g., MSC product, dose and administration), MSC characteristics (e.g., MSC provenance, "fitness," viability and immune compatibility) and MSC culture conditions (e.g., oxygen environment, culture medium and use of serum). CONCLUSIONS: By applying a Delphi method to establish a consensus definition for MSCs and reporting guidelines for MSC-based clinical trials, this work represents a significant advance in improving transparency and reproducibility in the conduct and reporting of MSC research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.400
GPT teacher head0.496
Teacher spread0.097 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it