Microscopically Positive Margins for Primary Gastrointestinal Stromal Tumors: Analysis of Risk Factors and Tumor Recurrence
Bibliographic record
Abstract
BACKGROUND: Little is known about the outcomes of patients with microscopically positive (R1) resections for primary gastrointestinal stromal tumors (GIST) because existing retrospective series contain small numbers of patients. The objective of this study was to analyze factors associated with R1 resection and assess the risk of recurrence with and without imatinib. STUDY DESIGN: We reviewed operative and pathology reports for 819 patients undergoing resection of primary GIST from the North American branch of the American College of Surgeons Oncology Group (ACOSOG) Z9000 and Z9001 clinical trials at 230 institutions testing adjuvant imatinib after resection of primary GIST. Patient, tumor, operative characteristics, factors associated with R1 resections, and disease status were analyzed. RESULTS: Seventy-two (8.8%) patients had an R1 resection and were followed for a median of 49 months. Factors associated with R1 resection included tumor size (≥ 10 cm), location (rectum), and tumor rupture. The risk of disease recurrence in R1 patients was driven largely by the presence of tumor rupture. There was no significant difference in recurrence-free survival for patients undergoing an R1 vs R0 resection of GIST with (hazard ratio [HR] 1.095, 95% CI 0.66, 1.82, p = 0.73) or without (HR 1.51, 95% CI 0.76, 2.99, p = 0.24) adjuvant imatinib. CONCLUSIONS: Approximately 9% of 819 GIST patients had an R1 resection. Significant factors associated with R1 resection include tumor size ≥ 10 cm, location, and rupture. The difference in recurrence-free survival with or without imatinib therapy in those undergoing an R1 vs R0 resection was not statistically significant at a median follow-up of 4 years.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".