Early postoperative intraperitoneal chemotherapy for lower gastrointestinal neoplasms with peritoneal metastasis: a systematic review and critical analysis
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: Early postoperative intraperitoneal chemotherapy (EPIC) can be used in combination with cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) to treat patients with peritoneal carcinomatosis (PC) of multiple origins. The present study is a systematic review to evaluate the role of EPIC after CRS + HIPEC for appendiceal and colorectal cancers with PC. CONTENT: We conducted a systematic search in PubMed according to the PRISMA guidelines and included all studies published before June 27 of 2019 comparing EPIC to HIPEC or the combination of both. Our search found 79 articles. After excluding non-relevant articles, a total of 13 retrospective clinical studies reporting on the efficacy and safety of EPIC compared to HIPEC or as a combination therapy for lower gastrointestinal neoplasms were analyzed. Initial EPIC reports led to its declined usage because of concerns with increased postoperative morbidity and uncertain added benefit on survival. Recent retrospective studies have been promising, showing significant improvements in OS and fewer issues with complications when adding EPIC to CRS + HIPEC. CONCLUSIONS: Current evidence is entirely retrospective and is conflicting. It is hoped that ongoing clinical trials and additional studies will clarify EPIC's role in the treatment of patients with PC.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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