Capturing uveal melanoma (UM) global practice patterns and clinical outcomes in the collaborative ocular melanoma natural history (OMNi) study (NCT04588662).
Bibliographic record
Abstract
TPS9610 Background: Geographical differences in the management of primary UM, surveillance for recurrence, and care of metastatic disease have emerged based upon local expertise, treatment availability and insurance coverage. We have initiated accrual to OMNi (NCT04588662), an ambispective database developed to provide contemporary real-world data of UM, capturing its natural history and serving as a virtual biospecimen repository. The overall objectives of OMNi are to characterize regional/international UM management practice patterns and associated clinical outcomes in an effort to inform best practice recommendations. Methods: OMNi utilizes the Pulse Infoframe Healthie platform, a globally compliant platform which enables the structured collection of data mapped to Observational Medical Outcomes Partnership. The data fields created permit longitudinal capture of data including baseline patient and tumor characteristics, treatment of primary lesion and outcomes, surveillance patterns, time to disease recurrence, treatment of recurrent disease with outcomes, and survival. Inclusion criteria include a diagnosis of uveal melanoma and the ability to provide written informed consent for participation in the prospective registry or an institutional waiver by the IRB/ethics committee for retrospective data collection without written informed consent. We have initiated data collection at 3 US and 3 Australian centers, with 184 patients enrolled to date. Based upon feasibility assessment, we anticipate retrospective data entry for ̃2,000 patients and annual recruitment of ̃700 patients once all centers are active. Data collected in this OMNi collaboration, which will include additional US, UK and Australian sites, will facilitate new insights, hypothesis testing, as well as clinical trial development and conduct, and through a governance structure, will be made accessible for research. The OMNi dataset can serve and aid in interpretation of clinical trial outcomes in the real-world, facilitate cutting-edge research, and accelerate the development of diagnostics and therapeutics. Clinical trial information: NCT04588662.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".