Cytoreduction and heated intraperitoneal chemotherapy for colorectal cancer: Are we excluding patients who may benefit?
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
BACKGROUND: Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) are increasingly used to treat peritoneal carcinomatosis from colorectal cancer. It is still relatively unknown which poor prognostic factors to avoid in order to optimize patient selection for CRS + HIPEC. METHODS: Between February 2003 and October 2011, 68 consecutive colorectal cancer patients who underwent CRS + HIPEC with a complete cytoreduction were identified from a prospective database. Survival analysis was performed using the Kaplan-Meier method, with log rank testing of differences between groups. Multivariate analysis was conducted using Cox proportional hazard regression. RESULTS: Median follow-up was 30.3 (range, 2-88) months amongst survivors. Patients with a peritoneal cancer index (PCI) of 10 or less showed improved survival over those with a PCI of 11 or higher (P = 0.03). No difference in survival was seen for the other potentially poor prognostic variables including lymph node status, synchronous peritoneal disease, peri-operative systemic chemotherapy, and rectal cancer primary. CONCLUSIONS: A low PCI was associated with improved survival. Complete CRS + HIPEC appears to result in similar survival outcomes regardless of delivery of peri-operative systemic chemotherapy. Rectal origin, lymph node status, and synchronous peritoneal disease should not be used as an absolute exclusion criteria for CRS + HIPEC based on current data.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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