The GOLD ReGISTry: a Global, Prospective, Observational Registry Collecting Longitudinal Data on Patients with Advanced and Localised Gastrointestinal Stromal Tumours
Bibliographic record
Abstract
BACKGROUND: Gastrointestinal stromal tumours (GISTs) are the most common gastrointestinal sarcomas. This global, prospective registry followed patients with advanced or localised GIST (2007-2011). METHODS: Current and evolving diagnostics, treatments and outcome measures in patients with GIST were assessed. Eligible patients were diagnosed with advanced or localised GIST within 15months of registry entry. No treatment plan was prescribed, and no visit schedule was mandated. Treating physicians recorded patient information, including tumour response, diagnostic methods, medications, surgeries performed, mutation status and adverse events leading to dose/medication changes. Survival outcomes were estimated using the Kaplan-Meier method. Other data were analysed using descriptive statistics. RESULTS: The registry included 1663 patients (advanced GIST, n=1095; localised GIST, n=537). Medications (e.g. tyrosine kinase inhibitor use and dosing), disease progression or recurrence and physician assessment of response to treatment in registry patients were consistent with controlled trials and prevailing clinical recommendations. In advanced GIST, estimated 30-month progression-free survival (PFS) (59.8%) and overall survival (OS) (82.7%) were higher than results from previously reported trials (≈40% and ≈70%, respectively). Consistent with treatment guidelines, the most common initial treatments were imatinib for advanced GIST, and complete surgical resection for localised GIST. Computed tomography scans were the most common imaging technique used at diagnosis and follow-up. Mutation analysis was performed at diagnosis in only 15.3% and 14.5% of patients with advanced and localised GIST, respectively. CONCLUSIONS: In this real-world GIST registry, patients with advanced GIST were treated with imatinib and patients with localised GIST received surgical resection, in accordance with prevailing clinical recommendations.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".