The Effect of Hippocampal Avoidance Whole Brain Radiotherapy on the Preservation of Long-Term Neurocognitive Function in Non-Small Cell Lung Cancer Patients With Brain Metastasis
Bibliographic record
Abstract
Whole-brain radiotherapy (WBRT) is the mainstay of therapy in treating cancer patients with brain metastases, but unfortunately, it might also lead to decline in neurocognitive function. This study aims to investigate the preservation of long-term neurocognitive function in patients after hippocampal avoidance whole-brain radiotherapy (HA-WBRT). Retrospectively, 47 patients diagnosed with brain metastases of non-small cell lung cancer (NSCLC) between 2015-01-01 and 2017-12-31 at the Department of Oncology, XXX Hospital were selected and divided into 2 groups. Group A (n = 27) received HA-WBRT, whereas group B (n = 20) received WBRT. Neurocognitive function was analyzed at baseline and at 3, 6, 9, 12 and 24 months after radiotherapy, using Mine-Mental State Examination (MMSE) scales and Montreal Cognitive Assessment (MoCA) scales. The OS, PFS and tumor recurrence sites were also analyzed. When evaluated at 12 and 24 months after radiotherapy, the cognitive function scores of the hippocampal avoidance group were significantly higher than those of the non-hippocampal avoidance group ( P < 0.001). In terms of patient survival, there was no significant difference in OS ( P = 0.2) and PFS (P = 0.18) between these 2 groups. Fourteen patients in group A and 12 patients in group B had brain tumor recurrence after radiation, only one patient in group A occurred within 5 mm from the edge of the hippocampus ( P > 0.05). In conclusion, HA-WBRT might have a protective effect on long-term neurocognitive function and did not affect patient survival.
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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) | 0.000 | 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 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".