Optimal Management of Gastric Cancer
Bibliographic record
Abstract
OBJECTIVE: Defining processes of care, which are appropriate and necessary for management of gastric cancer (GC), is an important step toward improving outcomes. METHODS: Using a RAND/UCLA Appropriateness Method, an international multidisciplinary expert panel created 22 statements reflecting optimal management. All statements were scored for appropriateness and necessity. RESULTS: The following tenets were scored appropriate and necessary: (1) preoperative staging by computed tomography of abdomen/pelvis; (2) positron-emission tomographic scans not routinely indicated; (3) consideration for adjuvant therapy; (4) further clinical trials; (5) multidisciplinary decision making; (6) sufficient support at hospitals; (7) assessment of 16 or more lymph nodes (LNs); (8) in metastatic disease, surgery only for palliation of major symptoms; (9) surgeons experienced in GC management; (10) and surgeons experienced in both GC management and advanced laparoscopic surgery for laparoscopic resection. The following were scored appropriate, but of indeterminate necessity: (1) diagnostic laparoscopy before treatment; (2) a multidisciplinary approach to linitis plastica; (3) genetic assessment for diffuse GC and family history, or age less than 45 years; (4) endoscopic removal of select T1aN0 lesions; (5) D2 LN dissection in curative intent cases; (6) D1 LN dissection for early GC or patients with comorbidities; (7) frozen section analysis of margins; (8) nonemergent cases performed in a hospital with a volume of more than 15 resections per year; and (9) by a surgeon with more than 6 resection per year. CONCLUSIONS: The expert panel has created 22 statements for the perioperative management of GC patients, to provide guidance to clinicians and improve the care received by patients.
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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".