P.104 Glioblastomas located in the right hemisphere are associated with worse quality of life
Bibliographic record
Abstract
Background: Because glioblastoma is currently incurable, the goal of therapy is the optimization of the patient’s quality of life (QOL). Tumor location is critical in screening surgical candidates, yet the impact of tumor location on QOL has never been demonstrated. By using a novel computer-driven algorithm, we set out to investigate the impact of tumor location on QOL. Methods: The tumors of fourty consecutive glioblastoma patients were segmented and the Euclidian distance between 90 brain regions and each tumor’s margin was calculated and correlated to the patients’ self-reported QOL as measured by the SNAS questionnaire. Results: QOL was statistically associated with proximity to three areas: the right para-hypocampal gyrus, the right posterior cingulate cortex and the right postcentral gyrus. We postulate that the adverse relation between proximity to these areas and QOL results from disruption in large-scale networks involved in high-order functions such as visuospatial memory. While harder to detect with a bedside clinical examination, such deficits are likely more impactful on QOL than those related to the motor cortex or Broca’s area. Conclusions: Tumor proximity to right parietooccipital region are associated with decreased QOL. This should be considered in the management strategies of glioma patients.
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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 | 0.000 | 0.000 |
| 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) | 0.008 | 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".