The Management of the Primary Tumor in Patients with Metastatic Colorectal Cancer
Bibliographic record
Abstract
Over the past decade, the role of surgery in stage IV colorectal cancer (CRC) has evolved, yet the optimal surgical management of the primary tumor in patients with metastatic CRC that is not amenable to curative resection is unknown. A high rate of surgical resection of the primary tumor has been reported in patients with unresectable metastatic disease. Resection of the primary tumor in patients with metastatic CRC is often performed to deal with presenting primary tumor symptoms and or to prevent future primary tumor complications. Nevertheless, with access to novel agents and their efficacy in the primary tumor as well as lack of major complications related to an intact primary tumor, surgery is less commonly performed today. Although the data regarding survival advantages of resection of the primary tumor are inconsistent, overall the evidence suggests potential survival benefit of removal of the primary tumor in patients with both symptomatic and asymptomatic primary tumors even with access to more effective combination chemotherapy. However, the published literature favoring surgery mostly comprises retrospective observational studies. Consequently, the survival benefit related to surgery has been attributed to selection bias, and in the absence of randomized controlled trial no definite conclusion can be drawn. Currently, two randomized controlled trials are enrolling patients to answer this important question in the management of metastatic CRC.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".