QLIF-29. FUNCTIONAL AND EMPLOYMENT OUTCOMES IN IDH MUTANT GLIOBLASTOMA
Bibliographic record
Abstract
A diagnosis of Glioblastoma is associated with poor outcomes with respect to functional and employment status in the period following surgery, radiation and chemotherapy. Genomic characterization of glioblastoma has demonstrated that patients harboring an IDH mutation have longer survival. This study aims to determine if patients with IDH mutant glioblastoma have improved oncologic, functional, and employment outcomes. Patient data was obtained from a single surgeon series between the years 2013 and 2017. Of 230 patients diagnosed with WHO grade 4 glioblastoma 11 harbored mutation of IDH1. Records obtained included age at diagnosis, Karnofsky Performance Status (KPS), return to work date, stability of imaging at the 16 month interval, and overall length of survival. The median age for this cohort was 39.2 years. Average KPS following initial resection and diagnosis was 78.8. Return to work was seen in 64% of patients and the average return to work date was 17 months post diagnosis. Of the 11 patients, 2 were deceased from unrelated causes. After accounting for the two unrelated deaths, 77% of patients returned to work in some capacity. Average overall survival (OS) was difficult to determine as only one patient has died as a result of tumor progression (survival length for this patient was 52 months). Imaging stability was seen in 100% of patients at the 16 month interval. In comparison to historical data for glioblastoma, in our series, glioblastoma patients with IDH mutation have increased return to employment, higher functional status post treatment, and extended stability of disease. These results suggest that care management and rehabilitation goals for patients with IDH mutant glioblastoma should reflect their improved functional outcomes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".