Gemcitabine-Containing Chemotherapy for the Treatment of Metastatic Myxofibrosarcoma Refractory to Doxorubicin: A Case Series
Bibliographic record
Abstract
BACKGROUND: Myxofibrosarcoma is a type of soft-tissue sarcoma that is associated with high rates of local recurrence and distant metastases. The first-line treatment for metastatic soft-tissue sarcoma has conventionally been doxorubicin-based. Recent evidence suggests that myxofibrosarcoma may be molecularly similar to undifferentiated pleomorphic sarcoma (UPS), which is particularly sensitive to gemcitabine-based therapy. The goal of this study was to evaluate the activity of gemcitabine-containing regimens for the treatment of metastatic myxofibrosarcoma refractory to doxorubicin. MATERIAL AND METHODS: We retrospectively evaluated seven consecutive cases of metastatic myxofibrosarcoma at our institution treated with gemcitabine-based therapy in the second-line setting, after progression on doxorubicin. Baseline clinical and baseline characteristics were collected. Primary endpoints were objective response rate (ORR), progression-free survival (PFS) and overall survival (OS). RESULTS: After progression on first-line doxorubicin, a partial, or complete radiological response was observed in four of seven patients who received gemcitabine-based chemotherapy. With a median follow-up of 14 months, median progression-free and overall survival were 8.5 months and 11.4 months, respectively. CONCLUSIONS: Gemcitabine-based chemotherapy was associated with encouraging response rates in this cohort, similar to those seen in UPS. Both entities could be studied together for novel gemcitabine-based regimens.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".