Efficacy of bevacizumab and temozolomide therapy in locally advanced, recurrent, and metastatic malignant solitary fibrous tumour: A population-based analysis
Bibliographic record
Abstract
BACKGROUND: Patients with locally advanced, recurrent or metastatic solitary fibrous tumour are often treated with bevacizumab and temozolomide based on the clinical efficacy reported in a case series of 14 patients. Given the rarity of solitary fibrous tumour, large trials are not feasible. We report the efficacy of this regimen based on a population-based analysis. METHODS: This was a population-based retrospective, multi-centre analysis using patient data from a provincial cancer registry and treatment database. Cases from June 2006 through October 2016 were identified for patients receiving bevacizumab and temozolomide for locally advanced, recurrent or metastatic solitary fibrous tumour or hemangiopericytoma, which is sometimes used to describe tumours arising from the meninges. The primary outcome was overall response rate. Secondary outcomes included time to response, progression free survival and overall survival estimated using the Kaplan-Meier method. RESULTS: Fourteen patients were identified: median age 59 (range 44-70), male 78.6%. Diagnoses were solitary fibrous tumour in 10 (71.4%) and hemangiopericytoma in four (28.6%), with metastatic disease in 10 (72.7%) patients. The most common primary sites were meninges in four (28.6%) and pelvis in three (21.4%) patients. The median follow-up was 15.5 months, with median treatment of four months. Overall response rate was 21.4% (no complete response, 3 partial response), with median time to response of four months. Median progression free survival, six-month progression free survival and overall survival were 17 months, 65.0%, and 45 months, respectively. CONCLUSIONS: Efficacy of bevacizumab and temozolomide in solitary fibrous tumour appeared to be similar to that previously reported. Our findings confirmed that bevacizumab and temozolomide is an effective and tolerated treatment for this patient population.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".