Demographic and Neuropsychiatric Factors Associated With Off-label Medication Use in Frontotemporal Dementia and Alzheimer’s Disease
Bibliographic record
Abstract
OBJECTIVES: Off-label medication use for treating cognitive impairments and neuropsychiatric symptoms occurs in frontotemporal dementia (FTD) and Alzheimer disease (AD). We compared the use of cognitive and psychiatric medications in FTD and AD and evaluated the relationship between neuropsychiatric symptoms and medication use. METHODS: Cognitive and psychiatric medication use, demographic variables, and Neuropsychiatric Inventory (NPI) subscale symptoms were obtained from the National Alzheimer's Coordinating Center Uniform Data Set (n=3958, 8.1% FTD). Bivariate statistics and logistic regressions were calculated to evaluate which demographic or NPI subscale symptoms predicted medication use. RESULTS: Although cognitive medication was used more commonly in AD (78%), it was also commonly used off-label in FTD (56%). Psychiatric medications were in greater use in FTD than in AD (68% vs. 45%, respectively, P<0.001). In FTD, cognitive medication use was associated with elevated NPI elation scores and psychiatric medication use was associated with history of prior psychiatric disease. In AD, demographic variables (white, longer disease duration, higher education, more severe disease, or being male) were most predictive of cognitive medication use, whereas having psychiatric disease, being white, having longer disease duration, being younger, greater disease severity, and being disinhibited or anxious were associated with psychiatric medication use. Off-label antipsychotics were used by 4.7% of patients with AD and 10% of patients with FTD. CONCLUSIONS: Our results revealed significant off-label medication use in both FTD and AD. A notable finding from this study was the lack of consistent relationships between medication use and neuropsychiatric symptoms across the 2 illnesses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".