Craniofacial surgery for malignant skull base tumors
Bibliographic record
Abstract
BACKGROUND: Malignant tumors of the skull base are rare. Therefore, no single center treats enough patients to accumulate significant numbers for meaningful analysis of outcomes after craniofacial surgery (CFS). The current report was based on a large cohort that was analyzed retrospectively by an International Collaborative Study Group. METHODS: One thousand three hundred seven patients who underwent CFS in 17 institutions were analyzable for outcome. The median age was 54 years (range, 1-98 years). Definitive treatment prior to CFS had been administered in 59% of patients and included radiotherapy in 367 patients (28%), chemotherapy in 151 patients (12%), and surgery in 523 patients (40%). The majority of tumors (87%) involved the anterior cranial fossa. Squamous cell carcinoma (29%) and adenocarcinoma (16%) were the most common histologic types. The margins of surgical resection were reported close/positive in 412 patients (32%). Adjuvant postoperative radiotherapy was received by 510 patients (39%), and chemotherapy was received by 57 patients (4%). RESULTS: Postoperative complications were reported in 433 patients (33%), with local wound complications the most common (18%). The postoperative mortality rate was 4%. With a median follow-up of 25 months, the 5-year overall, disease-specific, and recurrence-free survival rates were 54%, 60%, and 53%, respectively. The histology of the primary tumor, its intracranial extent, and the status of surgical margins were independent predictors of overall, disease-specific, and recurrence-free survival on multivariate analysis. CONCLUSIONS: CFS is a safe and effective treatment option for patients with malignant tumors of the skull base. The histology of the primary tumor, its intracranial extent, and the status of surgical margins are independent determinants of outcome.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".