Treatment of Peritoneal Surface Malignancies with Hyperthermic Intraperitoneal Chemotherapy—Current Perspectives
Bibliographic record
Abstract
Peritoneal carcinomatosis (ptc) represents advanced malignant disease and has generally been associated with a grim prognosis. Peritoneal surface malignancy is often the major source of morbidity and mortality; it is of major concern in cancer management. Although ptc is categorized as metastatic disease, it represents a special disease pattern considered to be a locoregional disease limited to the abdominal cavity. The combination of cytoreductive surgery (crs) and intraoperative hyperthermic intraperitoneal chemotherapy (hipec) has successfully been used as locoregional treatment for selected patients with ptc from gastric, colorectal, and ovarian cancer; with mesothelioma; and with pseudomyxoma peritonei. In the prophylactic setting, hipec can also be used to prevent ptc in high-risk patients, and the first results of the "second-look" approach are promising. Patient selection-in which the risks of perioperative morbidity and mortality, which are analogous to those for any other major gastrointestinal surgery, are assessed-is of utmost importance. Those risks have to be weighed against the anticipated survival benefit, which depends mainly on tumour biology, extent of disease, and probability of achieving complete crs. The present review discusses the principles of crs and hipec, the most significant recent clinical data, and current perspectives concerning the application of this treatment modality in various malignancies. Ongoing trials and future directions are noted. It appears that the combination of crs and hipec is an indispensable tool in the oncologist's armamentarium.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".