Predictors of a true complete response among disappearing liver metastases from colorectal cancer after chemotherapy
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: During chemotherapy, some colorectal liver metastases (LMs) disappear on serial imaging. This disappearance may represent a complete response (CR) or a reduction in the sensitivity of imaging during chemotherapy. The objective of the current study was to determine the fate of disappearing LMs (DLMs) and the factors that predict a true CR. METHODS: Between 2000 and 2003, 435 patients who were evaluated by hepatobiliary surgeons received chemotherapy before they were considered for resection. Inclusion criteria were <12 LMs before chemotherapy, at least 1 DLM on a computed tomography (CT) scan, and either surgical resection or 1 year of clinical follow-up after the disappearance of LMs. A true CR was defined as either a pathologic CR (no tumor detected in the resection specimen) or a durable clinical CR (did not reappear on follow-up imaging). Clinical and pathologic factors were analyzed to identify those associated with a true CR. RESULTS: During chemotherapy, 39 patients (9%) had a total of 118 DLMs on follow-up CT scans. Sixty-eight DLMs were resected, and 50 were followed clinically. Overall, 75 DLMs (64%) were true CRs, including 44 pathologic CRs and 31 durable clinical CRs. On multivariate analysis, the use of hepatic arterial infusion (HAI) chemotherapy (odds ratio [OR], 6.2; P = .02), the inability to observe the DLM on a magnetic resonance image (OR, 4.7; P = .005), and normalization of serum carcinoembryonic antigen levels (OR, 4.6; P = .006) were associated independently with a true CR. CONCLUSIONS: Approximately 66% of DLMs represented a true CR according to assessment by resection or radiologic follow-up. Predictive factors may help to stratify patients who are likely to harbor residual disease.
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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) | 0.004 | 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 it