Comparative Study of Short-Term Efficacy and Safety of Mitomycin versus Lobaplatin for Hyperthermic Intraperitoneal Chemotherapy after Radical Surgery in Colorectal Cancer with High-Risk Factors for Peritoneal Carcinomatosis: A Propensity Score Matching Analysis
Bibliographic record
Abstract
Background: The drug selection of radical surgery (RS), with hyperthermic intraperitoneal chemotherapy (HIPEC), in pT4 colorectal cancer (CRC) remains controversial. Methods: Adverse events after HIPEC were estimated by common terminology criteria for adverse events version 5.0. The efficacy was evaluated using overall survival (OS) and recurrence-free rate (RFR). Propensity score matching (PSM) was used to reduce the influence of confounders between Mitomycin and Lobaplatin groups. Results: Of the 146 patients, from April 2020 to March 2021, 47 were managed with mitomycin and 99 with lobaplatin. There was no significant difference in the incidence of all adverse events between the two groups after PSM. OS and RFR were not significantly different between the two groups at 22 months (p = 0.410; p = 0.310). OS and RFR of the two groups also showed no significant difference for patients with T4a or T4b stage, tumor size < or ≥ 5 cm. Among patients with colon cancer, RFR at 22 months of the two groups was significantly different (100.0% vs. 63.2%, p = 0.028). Conclusions: In summary, the safety of mitomycin and lobaplatin for HIPEC was not different. Compared with lobaplatin, mitomycin for HIPEC after RS could benefit patients with colon cancer in RFR.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".