Standardization of terminology, definitions and outcome criteria in immune thrombocytopenic purpura of adults and children: report from an international working group
Bibliographic record
Abstract
Diagnosis and management of immune thrombocytopenic purpura (ITP) remain largely dependent on clinical expertise and observations more than on evidence derived from clinical trials of high scientific quality. One major obstacle to the implementation of such studies and in producing reliable meta-analyses of existing data is a lack of consensus on standardized critical definitions, outcome criteria, and terminology. Moreover, the demand for comparative clinical trials has dramatically increased since the introduction of new classes of therapeutic agents, such as thrombopoietin receptor agonists, and innovative treatment modalities, such as anti-CD 20 antibodies. To overcome the present heterogeneity, an International Working Group of recognized expert clinicians convened a 2-day structured meeting (the Vicenza Consensus Conference) to define standard terminology and definitions for primary ITP and its different phases and criteria for the grading of severity, and clinically meaningful outcomes and response. These consensus criteria and definitions could be used by investigational clinical trials or cohort studies. Adoption of these recommendations would serve to improve communication among investigators, to enhance comparability among clinical trials, to facilitate meta-analyses and development of therapeutic guidelines, and to provide a standardized framework for regulatory agencies.
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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 | 0.200 | 0.162 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".