Brain Metastases from Adult Sarcoma: Prognostic Factors and Impact of Treatment. A Retrospective Analysis from the French Sarcoma Group (GSF/GETO)
Bibliographic record
Abstract
BACKGROUND: Brain metastases (BM) from adult soft tissue or bone sarcomas are rare, and sparse data exist on their prognostic factors and management. SUBJECTS, MATERIALS AND METHODS: A retrospective study was conducted in 15 centers of the French Sarcoma Group, plus one Canadian and one Swiss center, to report on clinical, histological, and treatment characteristics and to identify predictive factors of outcome. RESULTS: Between 1992 and 2012, 246 patients with a median age of 50 years (range: 16-86) were managed for BM. BM included 221 cerebral and cerebellar metastases and 40 cases of meningeal sarcomatosis. The most frequent histopathological subtype was leiomyosarcoma (18.7%). Histological grade was high in 118 (48%) cases. Surgery of BM was carried out for 38 (15.5%) patients. Radiotherapy and chemotherapy were administered in 168 (68.3%) and 91 (37.0%) patients, respectively. Irrespective of treatment modality, BM were controlled in 113 patients (45.9%), including 31 partial responses (12.6%) and 18 complete responses (7.3%). The median overall survival from diagnosis of brain metastasis was 2.7 months (range: 0-133). In the multivariate analysis, the following parameters influenced overall survival: chemotherapy (hazard ratio [HR] = 0.38; 95% confidence interval [CI]: 0.26-0.48), surgery (HR = 0.40; 95% CI: 0.22-0.72), stereotactic radiotherapy (HR = 0.41; 95% CI: 0.19-0.90), whole-brain radiotherapy (HR = 0.51; 95% CI: 0.35-0.76), and grade (HR = 0.65; 95% CI: 0.43-0.98). CONCLUSION: BM of sarcomas are rare and associated with a dismal outcome. Multidisciplinary management with chemotherapy, radiation therapy, and surgery is associated with a better survival. IMPLICATIONS FOR PRACTICE: The incidence of brain and meningeal metastasis in bone and soft tissue sarcomas is estimated between 1% and 8%. Published data are derived from small retrospective case series, often in the pediatric population. A prognostic index is important to guide both clinical decision-making and outcomes research, but one such is lacking for adult sarcoma patients with brain metastases. The current study describes brain metastasis in a large cohort of sarcoma patients. This study, conducted within the French Sarcoma Group, describes the natural history of sarcoma brain metastasis and enables the proposal of strategic recommendations for subsequent clinical trials and for the management of such patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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".