Assessing behavioral syndromes in patients with brain tumors using the frontal systems behavior scale (FrSBe)
Bibliographic record
Abstract
Abstract Background Personality changes following brain tumors may be due to disruption of frontal-subcortical networks. The relation between personality changes and tumor parameters such as volumes of the surgical cavity, residual tumor, or nonspecific white matter abnormalities is unknown. In this study we examined the relation between these tumor parameters and abnormal behaviors typically associated with frontal lobe dysfunction. Methods Thirty-one patients with intracranial tumors who completed the Frontal Systems Behavior Scale (FrSBe) during clinical neuropsychological assessment and had a solitary, well-delimited brain lesion on MRI within 3 months of that assessment were included. Tumor parameters were manually segmented using OsiriX. Nonparametric statistics were used to determine the relationship between tumor parameters and frontal behavioral dysfunction as measured by FrSBe scores. Results Patients reported significantly more behavior problems after tumor diagnosis. Tumor cavity volume was correlated with self-reported Executive Dysfunction (rho = 0.450, P = .047), and there was a trend in the relationship with self-reported Apathy (rho = 0.438, P = .053). Nonspecific white matter abnormality volume was also correlated with self-reported Apathy (rho = 0.810, P = .01). There were no correlations between FrSBe scores and residual tumor volume or summed volumes of tumor-related parameters. Conclusion Our results suggest that tumor parameters have differential effects on behaviors associated with frontal-subcortical networks and corroborate the high frequency of behavioral dysfunction in brain tumor patients. Examination of these relationships in a prospective trial is warranted to establish incidence, prevalence, risk factors, and consequences of behavioral disturbances in brain tumor patients.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 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".