Describing phenotypic subtypes of GBM in DWI imaging in relation to its genotypic subtypes
Bibliographic record
Abstract
Glioblastoma (GBM) is the most lethal primary brain tumour of the central nervous system, and has an unpredictable response to treatment with wide range of survival. There have been many attempts to identify factors that influence survival. We investigated the possible association between diffusion MRI, molecular signature, and survival of patients with GBM. This is a retrospective study conducted in Winnipeg (Health Sciences Center) for patients with GBMs from January 2015 to January 2018. In 93 patients, correlating normalized apparent diffusion coefficient (nADC) to time to death in days showed a Spearman’s rho correlation value of 0.244, indicating a weakly positive linear correlation. IDH mutation status in relation to nADC was found to be significant (mean difference of 0.38 and p-value of 0.015). The log-rank (Mantel–Cox) of nADC with cut-off point of 1.1725 was found to be significant (p-value of 0.046). The median survival was 11.5 months for nADC>1.1725 .vs 7.5 months for nADC<1.1725. The Cox regression multivariate analysis that included nADC (cut-off pint of 1.1725), age, nADC, IDH-mutation status, and extent of resection showed that age (p-value of 0.016) and nADC (p-value of 0.039) are statistically significant. Individuals with nADC <1.1725 were associated with an increased mortality hazard of 69% compared to individuals with nADC >1.1725 after adjusting for covariates of age, gender, and IDH mutation status. Individuals <70-year-old had a reduced mortality hazard of 47% compared to individuals >70-year-old old after adjusting for covariates of nADC, IDH mutation status, and extent of resection. In conclusion, nADC might have some value in identifying GBM patients with worse survival via IDH-mutation status.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".