The role of cytology in patients undergoing pressurized intraperitoneal aerosol chemotherapy (PIPAC) treatment for peritoneal carcinomatosis
Bibliographic record
Abstract
Objectives: Cytology of ascites or peritoneal washing is a routine part of staging of peritoneal metastases (PM). We aim to determine value of cytology in patients undergoing pressurized intraperitoneal aerosol chemotherapy (PIPAC). Methods: Single-center retrospective cohort study included consecutive patients having PIPAC for PM of different primary between January 2015 and January 2020. Results: A total of 75 patients (median 63 years (IQR 51-70), 67 % female) underwent a total of 144 PIPAC. At PIPAC 1 59 % patients had positive and 41 % patients had negative cytology. Patients with negative and positive cytology only differed in terms of symptoms of ascites (16% vs. 39 % respectively, p=0.04), median ascites volume (100 vs. 0 mL, p=0.01) and median PCI (9 vs. 19, p<0.01). Among 20 patients who completed 3 PIPACs (per protocol), cytology changed in one from positive to negative, and in two from negative to positive. Median overall survival was 30.9 months in the per protocol group and 12.9 months in patients having <3 PIPACs (=0.519). Conclusions: Positive cytology under PIPAC treatment is more frequently encountered in patients with higher PCI and symptomatic ascites. Cytoversion was rarely observed and cytology status had no impact on treatment decisions in this cohort.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".