Does Myasthenia Gravis Affect Long-Term Survival in Thymic Carcinomas? An ESTS Database Analysis
Bibliographic record
Abstract
Background: Thymic carcinoma is a rare and highly malignant tumor with a dismal prognosis, which occasionally coexists with myasthenia gravis (MG). This study aims to investigate the MG incidence on a surgical cohort of patients with thymic carcinoma and to explore its influence on long-term survival. Methods: the prospectively collected data from the ESTS database on thymic epithelial tumors were reviewed. Clinical, pathological, and survival information on thymic carcinoma were analyzed. Results: the analysis was conducted on 203 patients, with an equal gender distribution (96 males and 107 females). MG was detected in 22 (10.8%) patients, more frequently elderly (>60 years, p = 0.048) and male (p = 0.003). Induction therapy was performed in 22 (10.8%) cases. After surgery, 120 (59.1%) patients had a Masaoka stage II−III while complete resection (R0) was achieved in 158 (77.8%). Adjuvant therapy was performed in 68 cases. Mean follow-up was 60 (SD = 14) months. The 3-year, 5-year and 10-year survival rates were 79%, 75% and 63%, respectively. MG did not seem to influence long-term survival (5-year survival in non-MG−TCs 78% vs. 50% in MG−TCs, p = ns) as age < 60 years, female gender, early Masaoka stage, and postoperative radiotherapy did, conversely. Conclusions: myasthenia occurred in about 10% of thymic carcinomas and it did not seem to affect significantly the long-term prognosis in surgically treated thymic carcinoma-patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".