A comparison of survival by site of metastatic resection (MR) in metastatic colorectal cancer (mCRC).
Bibliographic record
Abstract
3529 Background: MR of liver limited disease is an effective therapy for patients (pts) with mCRC. Despite limited data, this approach has been expanded to include MR in other sites. We compared survival for mCRC pts undergoing MR of liver metastasis vs MR in other sites. Methods: Pts with mCRC who underwent MR in British Columbia over 5 time cohorts between 1995 and 2010 were reviewed. Pts without data on the site of MR or survival were excluded. Overall survival (OS) was defined as the time from diagnosis of metastasis to death. Kaplan Meier methodology and log-rank tests were used to compare the impact of site of MR on OS. Multivariate Cox regression was performed to assess for the impact of MR on OS, adjusting for known prognostic factors. Results: 2,082 pts with mCRC were identified; 1,197 men (57.5%) and 885 women (42.5%); 236 (1995-96), 206 (2000), 351 (2003-4), 546 (2006), 743 (2009-10). Median age at diagnosis of mCRC was 69 (14-94). 544 pts (30.0%) received a MR: 207 liver (38.1%), 57 lung (10.5%), 11 liver and lung (2.0%), 98 peritoneal (18.0%), 50 ovarian (9.2%), 34 brain (6.3%) and 87 other (16.0%). Pts that did not undergo MR had an OS of 13.4 months (ms) vs 41.8 ms for those that had MR of liver, lung or ovary (HR 0.31 (0.27-0.36); p<0.0001). By MR subgroup, OS was 46.2 ms for liver, 43.0 for lung, 41.2 for liver and lung, 13.4 for peritoneum, 21.8 for ovary, and 15.8 for brain. When compared to MR of liver, no significant difference in OS was observed for MR in lung (p=0.61) or liver and lung (p=0.26). Multivariate OS data are shown in the Table. Conclusions: MR of lung and liver and lung appears to confer a comparable survival advantage to MR of liver limited disease. Additional investigation is needed to further select pts most likely to benefit from MR. Multivariate analysis for OS HR p-value MR (liver, lung, or ovar)y 0.36 (0.31-0.42) <0.0001 Age (< 65 vs ≥ 65) 0.89 (0.63-1.27) 0.54 Sex (M vs F) 1.03 (0.94-1.13) 0.51 Primary (colon vs rectum) 1.11 (1.00-1.20) 0.03 M1 at presentation (N vs Y) 0.85 (0.77-0.95) 0.0016 ChemoTx (Y vs N) 0.48 (0.24-0.82) 0.009 Primary resection (Y vs N) 0.57 (0.49-0.65) <0.0001 2000 vs 1995-96 1.40 (1.10-1.60) 0.0012 2003-4 vs 1995-96 1.30 (1.10-1.60) 0.005 2006 vs 1995-96 1.30 (1.10-1.60) 0.0006 2009-10 vs 1995-96 1.40 (1.20-1.60) 0.0001
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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 | 0.001 | 0.001 |
| 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".