P08.05 Cognitive impairment in patients with newly-diagnosed high-grade gliomas
Bibliographic record
Abstract
Abstract BACKGROUND Cognitive dysfunction is frequent in patients with primary brain tumor, impairing attention, memory and executive function. It compromises functional independence, decision making capacity and psycho-social well-being. Cognitive functioning is highly correlated to disease progression and quality of survival, thus cognitive follow-up is essential in the management of the disease. Cognitive screening tools are often used, since a comprehensive battery may be time consuming and challenging for patients. The objective of this study was to identify a pattern of cognitive dysfunction in patients with newly-diagnosed high-grade gliomas and evaluate the sensitivity and specificity of the MoCA (Montreal Cognitive Assessment) as a cognitive screening tool in the clinical practice. MATERIAL AND METHODS We compared performances in tests of memory, action speed, visuospatial ability and executive function of 156 patients with newly-diagnosed WHO Grade III and IV gliomas, after surgery and prior to radiochemotherapy, to those of a group of healthy controls (n=1003). Relatives assessed behavior through a questionnaire of behavioral dysexecutive syndrome. A stepwise logistic regression was performed to select cognitive domains better discriminating patients from healthy controls and we tested the sensitivity and specificity of the MOCA using ROC curve analysis. RESULTS The stepwise logistic regression analysis identified the 3 following factors better discriminating patients from controls: TMT-B completion time (OR: 0.673; 95% CI: 0.511–0.886; p=0.0005), a verbal memory index (OR:0.507; 95% CI: 0.358–0.718; p=0.0001) and a behavioral dysexecutive score (OR:0.616; 95% CI: 0.468–0.812, p=0.001). Prevalence of cognitive-behavioral impairment was of 35.94%; 95% CI: 28.3 - 43.5. The ROC curve analysis for the assessment of the MoCA sensitivity and specificity in detecting impairment yielded 0.795 (95%CI: 0.714–0.875) for the MoCA raw score, and 0.804 (95%CI: 0.727 - 0.881) for the adjusted z score. The optimal discrimination was obtained for a raw score ≤ 25 (sensitivity of 0.526; specificity of 0.832). For the adjusted score, optimal discrimination value was observed with a -0.603 z score (sensitivity of 0.716; specificity of 0.768). CONCLUSION Cognitive impairment and behavioral dysexecutive syndrome is frequent in patients with newly-diagnosed high-grade glioma. The MoCA lacks sensitivity in screening cognitive impairment to discriminate patients from healthy controls in this setting, and a comprehensive neuropsychological assessment is still recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".