C.04 A systematic review and meta-analysis of 7551 patients with post-operative radiation for the management of functioning and non-functioning pituitary adenomas
Bibliographic record
Abstract
Background: Although surgery is the mainstay of treatment for most pituitary adenomas, post-operative radiotherapy has been shown to be of benefit in improving tumor control and recurrence-free survival. To understand potential side effects of radiotherapy we performed a systematic review and meta-analysis to determine the efficacy and safety of post-operative radiotherapy for pituitary adenoma. Methods: A systematic review was performed according to the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. We searched PubMed, MEDLINE and Cochrane databases with no language or publication date restrictions. Outcomes included 5- and 10-year progression-free survival and adverse events rates. Results: A total of 48 studies from 1986-2016 met the inclusion criteria, with 7551 cumulative patients. The cumulative 5- and 10-year s progression-free survival rates were 90.8% (95% CI 86-94%) and 88.6% (95% CI 81-93%), respectively. The overall adverse events rate was 8% (95% CI 5-12%). All outcomes were associated with significant heterogeneity (I2 ≥ 70%). No differences in survival rates or adverse events in relation to study date, tumor pathology, radiosurgery system used or dose of radiation. Conclusions: Post-operative radiotherapy for pituitary adenomas is effective and safe. Because of the significant heterogeneity and lack of matched controls in the literature, optimum timing and dosage are still unclear. Further prospective studies are needed.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.035 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".