Thymoma pathology and myasthenia gravis outcomes
Bibliographic record
Abstract
INTRODUCTION: There is limited evidence regarding the impact of World Health Organization (WHO) subtype of thymoma on post-thymectomy outcome of thymoma-associated myasthenia gravis (TAMG). The objective was to determine if the pathological subtypes of thymoma were associated with post-thymectomy outcomes of myasthenia gravis (MG), in patients with TAMG. METHODS: We performed a retrospective study of consecutive patients with TAMG who attended the neuromuscular clinic between January 2018 and December 2019 with a minimum follow-up of 1 y after thymectomy. Outcome measures were MG Impairment Index (MGII), single-simple question (SSQ), Myasthenia Gravis Foundation of America post-intervention status (MGFA PIS) and non-responder MG status at last assessment. RESULTS: Ninety-five patients were included; mean age at onset was 48.1 ± 12.1 y; 54(56.8%) were females. Thirteen patients developed MG post-thymectomy. The most common thymoma was WHO type B2 in 39 (41.1%). Most patients (40, 42.1%) had Masaoka stage II thymoma. There was no association of thymoma subtypes or Masaoka stage of disease with age, gender, MG phenotype, serology, post-thymectomy onset, interval from onset to thymectomy, MGII, SSQ, MGFA PIS, or non-responder status. Associations were found between positive serology and lower MGII (11.1 ± 14.2 vs 23 ± 12.9, P = .050), thymic follicular hyperplasia (TFH) and higher SSQ (89.3 ± 11.7 vs 80.1 ± 20.2, P-.043), and lack of recurrence and higher SSQ (84.1 ± 18 vs 72.5 ± 20, P = .037). DISCUSSION: The WHO pathological subtype of thymoma did not correlate with MG outcomes. However, positive acetylcholine antibody serology, presence of TFH, and non-recurrence of thymoma predict a favorable outcome.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".