SPCR-04 EFFECTS OF BRAIN METASTASES ON NEUROCOGNITIVE FUNCTION: BASELINE RESULTS OF A LONGITUDINAL TRIAL
Bibliographic record
Abstract
Abstract PURPOSE Neurocognitive dysfunction is common in patients with advanced metastatic cancer. The contribution of brain metastases (BrMets) to neurocognitive outcomes is uncertain. We examined the impact of BrMets on cognitive outcomes before CNS-directed treatment and compared findings to patients with advanced metastatic cancer without BrMets. Here we present results from an ongoing prospective, longitudinal study. METHODS English-speaking adults followed at the brain metastases and lung cancer clinics underwent neurocognitive testing using a standardized battery (prior to cranial radiotherapy, if applicable), with follow-up assessments 3, 6, 9, 12, 18, and 24 months later. We calculated z-scores and impairment rates for composite neurocognitive function and memory, attention/working memory, processing speed and executive function domains. Impairment was defined according to International Cancer and Cognition Task Force criteria. RESULTS 78 patients with BrMets (50% female; mean age (SD):61(11) years) and 28 patients with metastatic non-small cell lung cancer (mNSCLC) with no known BrMets (71% female; age 67(9) years) were included. Baseline neurocognitive composite scores were impaired in both groups (BrMets: 61.5%; nonBrMets: 60.7%). Impairment rates varied between groups and across domains (BrMets vs nonBrMets: memory: 35.9%vs25.0%; attention/working memory: 35.8%vs21.4%; processing speed: 10.3%vs7.1%; executive function: 44.0%vs35.7%). Subgroup comparisons between BrMets patients with mNSCLC (N=29) and mNSCLC patients without BrMets, none of whom had targetable mutations, revealed no differences in impairment rates, but BrMets patients had slower processing speed than nonBrMets patients (mean(SD): -0.6(1.4) vs -0.1(1.9); Wilcoxon signed-rank test, p = 0.043). CONCLUSION Neurocognitive impairment in patients with advanced cancers is common. Our preliminary findings demonstrate no clear difference in cognitive outcomes between patients with BrMets and those with advanced metastatic disease not involving the brain. Our work examining how neurocognitive outcomes evolve over time in patients with and without BrMets, and demographic, disease, and treatment variables associated with those outcomes, is ongoing.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".