EPID-09. PROGNOSTIC FACTORS IN ADULT PATIENTS WITH PRIMARY INTRACRANIAL EPENDYMOMAS: A POPULATION-BASED STUDY
Bibliographic record
Abstract
Abstract BACKGROUND Outcomes for patients with intracranial ependymoma remain poor in the current era of cancer treatment. This study aims to investigate the prognostic value of demographic and clinical variables to predict survival using the largest current database of patients with intracranial ependymoma. METHODS The Surveillance, Epidemiology and End Results (SEER) registry was queried for prognostic factors and survival outcomes of adult (≥18 years) patients diagnosed with intracranial ependymoma from 2004–2016. Survival was estimated using Kaplan Meier curves. Cox proportional hazards modeling was used to identify correlates of survival. RESULTS We identified a cohort of 229 primary intracranial ependymoma patients. The cohort showed a slight male predominance (52%) and had a mean age of 43 ± 17 years. 107 patients (47%) had WHO grade II tumors and 122 patients (53%) had WHO grade III tumors. One year survival was 85% for the entire cohort. Increasing age at diagnosis (HR: 1.05, 95% CI: 1.03–1.07) and WHO grade III tumor (HR: 4.20, 95% CI: 2.02–8.75) were independently associated with mortality after adjusting for age, sex, tumor location, extent of surgery, use of radiation therapy, and use of chemotherapy. Use of radiation therapy was associated with better one-year survival in cases of gross total resection (GTR) and subtotal resection (STR). Use of chemotherapy was not associated with mortality in the adjusted analysis (HR: 2.16, 95% CI: 0.96–4.84). CONCLUSION Our results suggest that age at diagnosis and tumor grade are independent factors associated with mortality in adult patients with intracranial ependymoma. Furthermore, use of chemotherapy was not shown to decrease mortality. These findings help guide future prognostic model making and therapeutic strategies designed by health care professionals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".