Resection of colorectal carcinoma liver metastases: A population-based study in outcomes and factors associated with recurrent disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To assess the hepatic disease-free survival (HDFS) and overall survival (OS) of patients who underwent resection of colorectal cancer liver metastases (CRCLM) in our population, and evaluate what factors are associated with these outcomes. Patients with resected non-mucinous CRCLM between January 2013-February 2020 were retrospectively identified. Dates of diagnosis, surgery, and, if applicable, death were recorded. HDFS and OS were calculated using a census date of 24 September 2022. Separate Cox multivariate regression analyses were performed to evaluate for association between HDFS and OS and the following factors: pre-operative imaging interval (<4 weeks vs. ≥4 weeks); pre-operative imaging modality (CT only vs. MRI+CT); extrahepatic disease at time of hepatectomy (yes vs. no); tumor burden score (TBS, where TBS2 = (largest axial dimension of CRCLM)2 + (number of CRCLM)2); pT and pN; and neoadjuvant chemotherapy. 137 subjects (mean age, 61±11 years, 86 males) were included. Associations with recurrent hepatic disease were found with chemotherapy (HR 2.11[95% CI=1.13–3.92]), TBS (HR 1.30[95% CI=1.17–1.45]), MRI+CT (HR 2.12[95% CI=1.29–3.48]), and extrahepatic disease at hepatectomy (HR 2.16[95% CI=1.08–4.35]). For mortality, associations were found with TBS (HR 1.22[95% CI=1.09–1.37]), pT (HR 1.45[95% CI=1.05–2.00]), and extrahepatic disease at hepatectomy (HR 2.10[95% CI=1.31–3.36]). In our population, non-imaging related factors TBS, neoadjuvant chemotherapy, pT and presence of extrahepatic disease at time of hepatectomy were associated with HDFS and/or OS. The preoperative imaging interval and use of preoperative MRI were not associated with improved patient outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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