Phase I dose escalation study for In Vivo Lung Perfusion (IVLP) as an adjuvant treatment for patients with resectable pulmonary metastasis of bone or soft tissue sarcomas
Bibliographic record
Abstract
Background Metastatic sarcoma is an aggressive disease with few effective treatment options. Standard of care for limited pulmonary metastasis is surgical resection, however micrometastasis are often present and go undetected. Here, we determine the maximal tolerated dose and safety of doxorubicin delivered via In Vivo Lung Perfusion (IVLP) for patients with resectable sarcoma pulmonary metastases. Methods This is a phase I dose escalation study using doxorubicin during IVLP in sarcoma patients with surgically resectable bilateral pulmonary metastases from 2017 to 2022. While the bilateral disease was surgically resected, only a single side underwent IVLP with doxorubicin at different dose levels (DL 1-3). Intraoperative serum, perfusate and lung tissue were collected and evaluated for doxorubicin levels. Patients were closely monitored intra- and post-operatively for adverse events. Results 8 patients consented and six patients met the inclusion criteria, while 2 patients had progressive disease before surgery and were excluded. Initial dose of 5ucg/ml perfusate of doxorubicin (DL1) was used in 1 patient, 3 patients had a dose escalation to 7ucg/ml (DL2), 2 patients with the final dose escalation of doxorubicin to 9ucg/ml (DL3). With DL3, lung infiltrates were observed, therefore it was declared as the maximal administered dose and DL2 was deemed to be the recommended phase 2 dose (RP2D). There were no safety concerns during the IVLP procedure and no deaths within the first 90 days. Conclusions Here, we demonstrate the safety and feasibility of doxorubicin as a treatment during IVLP for resectable limited pulmonary metastases for sarcomas.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".