Real-world experience of tyrosine kinase inhibitors in patients (pt) with recurrent bone tumours (BT): A CanSaRCC study.
Bibliographic record
Abstract
11530 Background: Survival after relapse in osteosarcoma (OST), Ewing Sarcoma (ES) and chondrosarcoma (CS) remains dismal. Recent reports suggest a role of tyrosine kinase inhibitors (TKI) including regorafenib (R) and cabozantinib (C). We conducted a retrospective multi-centre pan-Canadian study to assess real-word outcomes with these novel treatments in recurrent BT. Methods: After ethics approval, data from pts treated in 7 different institutions was extracted from the CanSaRCC (Canadian Sarcoma Research and Clinical Collaboration) Database. Pt characteristics, treatment and outcomes were analyzed. Response was assessed per RECIST 1.1. PFS, OS were estimated using Kaplan-Meier. TTP was defined as time from TKI start to progression. Results: From June 2018-Dec 2021, 44 pts received R or C and best response by histology are listed in Table, with an overall clinical benefit rate of 63.6%. Median time to best response was 2.3 mo (range 1 – 17). 15 pts (34.1%) required dose reduction; most common reasons were hand-foot syndrome (13.6%), mucositis (9.1%) and hypertension (9.1%). At median FU of 6.4 mo (range 1.6 – 29), 25 pts (56.8%) died, 19 (43.2%) were alive with disease (AWD). Median PFS was 4.1 mo (95%CI 2.9 – 5.7), for OST was 5.0 (N = 25, 95%CI 2.6 – 10.6), for ES was 4.1 (N = 10, 95%CI 2-5.9), and for CS 4.0 (N = 9, 1 Progressed). Median OS was 10.5 mo (95%CI 7 – 14). By univariate analysis, age, line of therapy, gender, location of primary, or R vs. C did not correlate with PFS. Conclusions: Consistent with previous published studies, our pan-country real-world analysis shows that TKI have meaningful activity in the setting of recurrent BT with acceptable toxicities. Inclusion in earlier lines of treatment and/or maintenance therapy could be questions for future research. [Table: see text]
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".