NCOG-17. COGNITION AND BRAIN STEREOTACTIC RADIOTHERAPY: A PILOT TRIAL
Bibliographic record
Abstract
To evaluate a computerised cognitive test for the detection of information processing speed impairment in patients with radiation therapy for brain metastases named Interhemispheric transfer time test (IHTTT). Medical inclusion criteria: patients≥18 years, with 1 to 4 brain metastases treated by stereotactic radiotherapy (SRT) with dose schedule: 33 Gy in 3 fractions, with a solid tumour, ≥70 Karnofsky Performance Status, with Mini-Mental State Evaluation (MMSE) ≥ 24, without medical history of stroke brain injury. 29 patients were recruited to our Center from June 2014 to April 2015. All recruited patients were administered a MMSE, the Frontal Assessment Battery at Bedside (FAB), a IHTTT and a quality of life questionnaire before SRT, and at one month, six months and one year follow up. The primary endpoint was Interhemispheric Transfer Time (IHTT). Secondary endpoints included IHTI (Interhemispheric Transfer Index), MMSE score, FAB score and quality of life. Our results suggest that IHTT and IHTI could detect a significant evolution of cognitive function over time (IHTT=720.3 ms ±26.5 at baseline, 728.0 ± 19.8 at one month follow up, 735.5 ± 36.1 at 6 month, 790.5 ± 109.1 at one year follow up, p=0.04, IHTI=13.1 ± 31.4, 11.5 ± 24.3, 50.6 ± 57.9, 82.2 ± 63.5, p=0.01). There is no significant evolution over time for MMSE and FAB score. This confirms their low sensitivity and specificity for detecting cognitive impairment. No significant evolution over time for quality of life questionnaire. IHTTT could be an interesting cognitive test to include in patients’ evaluation with brain metastases irradiated by SRT.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".