The effect of doxorubicin loading on response and toxicity with drug-eluting embolization in resectable hepatoma: a dose escalation study.
Bibliographic record
Abstract
AIM: The dose-response relationship between doxorubicin and superabsorbent drug-eluting microspheres has not been established. In this study, we investigated the relationships between dose and delivery parameters as they pertain to toxicity and response in surgically resectable hepatocellular carcinoma (HCC). PATIENTS AND METHODS: Twenty-five patients with resectable HCC were randomly assigned and divided into four groups, each receiving either bland, 25 mg, 50 mg or 75 mg of doxorubicin loaded Super Absorbent Polymer microspheres, with 24 patients undergoing surgical resection. Response Evaluation and Criteria in Solid Tumors (RECIST) 1.0 and European Association for the Study of the Liver (EASL)-based volumetric response was performed at one month and surgical resection of the reference tumor was performed at two months. Adverse events were collected at regular intervals. RESULTS: Fifty-six percent of patients demonstrated complete response according to EASL criteria as opposed to 0% according to RECIST (v1.0) criteria. Residual tumor was identified in all groups (0 mg: 35%±28.5%; 25 mg: 42%±30.4%; 50 mg: 3.6%±3.3%; and 75 mg: 49.29%±32.6%. A total of 112 adverse events of grades 1-3 occurred (average 5.1 per patient), with no grade 4 or 5. No difference was noted between bland embolic and drug-loaded groups. Subset analysis did demonstrate a significantly increased degree of necrosis in the 50 mg-loaded group (p=0.018). Strong correlation existed between arterial phase Computer Tomography EASL-based response and histopathology (r=0.81; p<0.0001). All groups had residual tumor. CONCLUSION: Histology correlates strongly with one-month post-procedural imaging and response optimized at 50 mg of loading per vial. Adverse events were a reflection of embolization, with no relationship between loading dose or administered dose of doxorubicin.
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.
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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".