Primary cardiac sarcomas: A multi‐national retrospective review
Bibliographic record
Abstract
BACKGROUND: Primary cardiac sarcoma (PCS) is a rare but often fatal disease. The current study aimed to analyze the impact of baseline demographics, local and systemic therapies in a contemporary cohort. METHODS: Clinical records of PCS across six institutions in three continents were reviewed. Kaplan-Meier method was used to estimate survival. Cox proportional hazard model was used to determine variables impacting progression-free survival (PFS) or overall survival (OS). RESULTS: Sixty-one patients with PCS (1996-2016) were identified. The median age at diagnosis was 46 (range 18-79); 36% (n = 22) presented with metastatic disease. The most common histology was angiosarcoma (n = 24, 39%). A total of 46 patients received surgery (75%) but only 5 (8%) patients achieved R0 resection. Multi-modality treatment to the primary tumor was given to 28 patients (46%; localized disease 23/39 (59%); metastatic disease 5/22 (23%)). The median OS for the entire cohort was 17.5 months (95% CI 9.5-20.6), with seven (11%) patients surviving longer than 36 months. On multi-variate analysis, age <65 (P = 0.01) was the only significant favorable prognostic factor. For first-line palliative chemotherapy, the median PFS was 4.4 months (95% CI 2.9-7.7 months). The best response for first-line chemotherapy was 32% (CR = 1, PR = 9). No significant improvement in OS was identified in patients presenting throughout the 20-year period of this review. CONCLUSION: Younger age at diagnosis was associated with improved outcome although the prognosis of PCS remains poor. Given the lack of improvement in survival, further dedicated research is required.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".