The effectiveness of adjuvant radiotherapy after thymoma resection: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Our systematic review and meta-analysis aimed to investigate the impact of postoperative radiotherapy(PORT) on patient outcomes following thymoma resection. METHODS: A comprehensive search of PubMed, EMbase, The Cochrane Library, Web of Science, Wanfang, Wipo, and China Knowledge Network databases was systematically conducted. Relevant literature comparing the therapeutic efficacy and effectiveness of thymectomy and thymectomy+ PORT in patients with thymoma published until August 2024 was gathered. The retrospective studies included in this analysis were evaluated using the Newcastle-Ottawa Scale (NOS), while meta-analysis of the literature was performed using Review Manager 5.4 software. RESULTS: A total of 23 retrospective studies, encompassing 13,742 patients, were included in the analysis. Among them, 6,980 patients belonged to the surgery-only group (3,321 male patients and 3,659 female patients), with an average age of 54.08 years. The surgery + PORT group consisted of 6,762 patients (3,385 male patients and 3,377 female patients) with an average age of 53.76 years. All included studies had a NOS score of ≥7.The meta-analysis results revealed that, in comparison to the surgery group, the surgery + PORT group exhibited higher rates of overall survival at 1 year, 3 years, 5 years, and 10 years. Additionally, the surgery + PORT group demonstrated superior disease-free survival (DFS)rates at 1 year and 5 years as well as disease-specific survival (DSS) rates at 3 years, 5 years, and 10 years. However, no significant differences were observed between the two groups in terms of DFS at 3 years or DSS at 1 year. CONCLUSIONS: Available retrospective evidence indicates an association between PORT and improved survival after thymoma resection, though prospective validation is warranted.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".