The impact of additional malignancies in patients diagnosed with gastrointestinal stromal tumors
Bibliographic record
Abstract
A higher incidence of additional malignancies has been described in patients diagnosed with gastrointestinal stromal tumors (GIST). This study aimed to identify risk factors for developing additional malignancies in patients diagnosed with GIST and evaluate the impact on survival. Individuals diagnosed with GIST from 2001 to2009 were identified from the SEER database. Logistic regression was used to identify predictors of additional malignancies and Cox-proportional hazards regression used to identify predictors of survival. In the study period, 1705 cases of GIST were identified, with 181 (10.6%) patients developing additional malignancies. Colorectal cancer was the most common cancer developing within 6 months of GIST diagnosis (30%). The median time to diagnosis of a malignancy after 6 months of GIST diagnosis was 21.9 months. Older age (p < 0.0001) and extraoesophagogastric GIST (p = 0.0027) were significant prognostic factors associated with additional malignancies. The overall 5-year survival was 65%, with the presence of additional malignancies within 6 months of GIST diagnosis associated with poor overall survival (54%, HR 1.55 1.05-2.3 95% CI, p = 0.04). Predictive factors of additional malignancies in patients diagnosed with GIST are increasing age and the primary disease site. Developing additional malignancies within 6 months of GIST diagnosis is associated with poorer overall survival. Targeted surveillance may be warranted in patients diagnosed with GIST that are at high risk of developing additional malignancies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".