Surgical resection and peri-operative chemotherapy for colorectal cancer (CRC) liver metastases in routine clinical practice: A population-based outcomes study.
Bibliographic record
Abstract
3632 Background: Resection of liver metastases combined with peri-operative chemotherapy is an important treatment option for patients with advanced CRC. Most of the literature describes outcomes achieved in highly selected patients treated at a few high volume institutions. Here we report the results of a population-based study of the management and outcome of all patients who underwent resection of CRC liver metastases in Ontario, Canada. Methods: All cases of CRC in Ontario who underwent surgical resection of liver metastases in 1994-2009 were identified using the population-based Ontario Cancer Registry (OCR). The OCR captures diagnostic and demographic information on ~98% of all incident cancer cases in Ontario. We linked electronic records of treatment to the OCR to identify surgery, neoadjuvant (NACT) and adjuvant chemotherapy (ACT). We describe time trends in treatment and survival using 3 study periods: 1994-1999, 2000-2004, 2005-2009. Results: During 1994-2009, 2717 patients underwent resection of CRC liver metastases in Ontario; mean age was 65 years and 61% were male. From 1994-2009 there was a 103% increase in the number of patients undergoing resection of liver metastases (117/year to 237/year) while incident cases of CRC during this time increased by 31% (5285/year to 6956/year). Use of NACT increased over the study period: 94-99, 11% (78/700); 00-04, 15% (124/830); 05-09, 36%; (424/1187), (p<0.001). Use of ACT also increased: 94-99, 38% (263/700); 00-04, 40% (335/830); 05-09, 45% (532/1187), (p=0.006). In 2005-2009 there was substantial variation across geographic regions in use of NACT (range 19% to 46%, p=0.029) and ACT (range 31% to 56%, p=0.015). Five year overall survival during the 3 study periods was 36% (95%CI 32-39%), 40% (95%CI 36-43%), and 47% (95%CI 43-51%) (p<0.001). Conclusions: Resection of CRC liver metastases in routine practice in the general population of Ontario is associated with survival outcomes that are comparable to those reported in case series from leading comprehensive cancer centres. Survival improved over the study period despite a greater proportion of patients with CRC undergoing liver resection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".