Gastrointestinal Stromal Tumors: 10-Year Experience in Cancer Center—The Ottawa Hospital (TOH)
Bibliographic record
Abstract
(1) Background: The management of gastrointestinal stromal tumors (GIST) has significantly evolved over the last two decades, with the introduction of tyrosine kinase inhibitors (TKI). We aim to report 10 years of experience of GIST management at a regional cancer center in Canada. (2) Methods: We retrospectively analyzed the records of 248 consecutive patients diagnosed with GIST between 2011 and 2021. We describe the clinical and pathological data, management, and outcome, including survival. (3) Results: The most common GIST sites were the stomach 63% (156), followed by the small bowel 29% (73). At diagnosis, 83% (206) of patients had localized disease (stage I–III). According to the modified National Institutes of Health consensus criteria (NIH) for GIST, around 45% (90) had intermediate or high-risk disease. Most patients, 86% (213), underwent curative surgical resection. Forty-nine patients received adjuvant imatinib, while forty-three patients had advanced disease and received at least one line of TKI. With a median follow-up of 47 months, the 5-year recurrence-free survival (RFS) rates for very low and low risk were 100% and 94%, respectively, while those for intermediate and high risk were 84% and 51%, respectively. The 5-year overall survival (OS) rates for very low and low risk were 100% and 94%, while intermediate, high risk, and advanced were 91%, 88%, and 65%, respectively. Using the Kaplan–Meier method, there were statistically significant differences in RFS and OS between NIH risk groups, p < 0.0005. In univariate analysis, ECOG, site, mitosis, secondary malignancy, and size were predictors for OS. High mitosis and large size (>5 cm) were associated with worse RFS. (4) Conclusions: Curative surgical resection remains the gold standard management of GIST. Our results are comparable to the reported literature. Further research is needed to explore histology’s role in risk stratification and initiating adjuvant TKI.
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.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".