Risk Factors for Cognitive Impairment in High-Grade Glioma Patients Treated with Postoperative Radiochemotherapy
Bibliographic record
Abstract
PURPOSE: Fractionated radiotherapy as well as concomitant and adjuvant chemotherapy such as temozolomide for postoperative high-grade glioma (HGG) patients improves progression-free survival and overall survival. Multiple factors such as chemotherapy, radiotherapy, tumor grade, residual tumor volume, and genetic modifications might play a role in the formation of cognitive impairment. The risk factors of cognitive impairment in postoperative patients with HGG receiving radiotherapy and chemotherapy remains a concern in this population. The purpose of this study was to identify risk factors for cognitive impairment in patients of postoperative HGG. MATERIALS AND METHODS: A total of 229 patients with HGG who underwent surgery were analyzed. Cognitive impairment was defined as a decrease of Cognitive Assessment Montreal (MoCA)'s score in at least two cognitive domains or any MoCA's score of less than 26 points at the time of study compared with baseline level. Multiple potential risk factors including methylated status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter, glioma World Health Organization (WHO) grade, residual tumor volume, education, and sex were analyzed. Cox univariate and multivariate regression analysis was used to detect the significant risk factors for cognitive impairment. RESULTS: At the end of follow-up among the 229 patients, 147 patients (67%) developed cognitive impairment. 82 patients (36%) remained in normal cognitive condition. In multivariate analysis, unmethylated MGMT promoter (hazard ratio [HR], 1.679; 95% confidence interval [CI], 1.212 to 2.326; p=0.002), glioblastoma (HR, 1.550; 95% CI, 1.117 to 2.149; p=0.009), and residual tumor volume > 5.58 cm3 (HR, 1.454; 95% CI, 1.047 to 2.020; p=0.026) were independent risk factors for cognitive impairment. CONCLUSION: Methylated status of the MGMT promoter, glioma WHO grade, and residual tumor volume might be risk factors for the cognitive impairment in postoperative patients with HGG.
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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 | 0.001 |
| 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) | 0.001 | 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".