Is Postoperative Radiotherapy Needed in the Management of Adult Craniopharyngiomas?
Bibliographic record
Abstract
ABSTRACT: Background: The optimal treatment of adult craniopharyngioma (CP) remains controversial. Although benign, these tumors tend to recur locally. The choice between gross total resection (GTR) versus subtotal resection (STR) with adjuvant or delayed radiotherapy (RT) is debated. The objective of this study is to review our experience with adult CPs over a 20-year period and identify an optimal management strategy. Methods: From 1999 to 2020, we reviewed all patients diagnosed with CP at our institution. We collected data regarding tumor characteristics, treatments, and toxicity. Disease progression was defined as growth on imaging. Descriptive statistics were used to assess patient characteristics. The Kaplan Meier method was used to assess progression-free survival (PFS) and corresponding 95% confidence intervals (CI) from the time since treatment initiation. Results: Twenty-four patients with a median age of 50 were included in this study. The median follow-up was 85 months. Seven patients had initial GTR, 10 STR, and 7 STR + RT. The overall 5-year PFS was 56% (95% CI: 38–83%): 100% in the STR + RT group, 69% in the GTR group, and 18% in the STR group (p = 0.01). Of the 17 patients initially treated with surgery alone, 3 with GTR and 6 with STR required salvage RT at a median of 46 months, with no further progression after salvage RT. Conclusions: Our study underscores the importance of RT for local control and suggests that STR + RT should be considered a viable option in the management of these tumors as it may be associated with improved PFS compared to surgery alone.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".