Frontotemporal Dementia: Recommendations for Therapeutic Studies, Designs, and Approaches
Bibliographic record
Abstract
Frontotemporal dementia (FTD) is one of three neurobehavioural syndromes produced by frontotemporal lobar degeneration. Despite the importance of FTD as a cause of dementia, especially in younger age groups, and a rationale for therapies targeting serotonergic and dopaminergic systems, there have been no large scale treatment trials in FTD. Moreover, there is no consensus on standards to facilitate comparison across therapeutic trials. This paper reviews the literature on therapeutic trials in FTD and outlines general recommendations for standards related to the development of future treatment studies in this disorder. Drugs tested in FTD include trazodone, galantamine, idazoxan, lithium plus fluoxetine, lithium plus paroxetine, SSRIs, 1-deprenyl, moclobemide, methylphenidate, piracetam, rivastigmine, donepezil, olanzapine, risperidone, amantadine, guanfacine, allopurinol, and bromocriptine. Improvement has been reported in FTD for all drugs except piracetam, guanfacine and galantamine, although there was improvement on galantamine in primary progressive aphasia. Whereas improvement has been reported for paroxetine and other SSRIs, as well as idazoxan and methylphenidate, paroxetine and idazoxan have also been reported to cause a decline in function, and a marginally significant decline has been reported for methylphenidate. In addition, patients with Pick's disease, which is part of the spectrum of frontotemporal lobar degeneration, showed improvement on calcium EDTA. Six studies are double-blind placebo-controlled trials: two reports of cases using idazoxan and group trials using trazodone, paroxetine, galantamine and methylphenidate. It is recommended that experts in FTD arrive at a consensus to define standards for all clinical trials in FTD. These should include standards for diagnostic criteria, tests of severity, experimental design, and outcome measures.
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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 | 0.484 | 0.560 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.014 | 0.020 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.017 | 0.012 |
| Research integrity | 0.035 | 0.022 |
| Insufficient payload (model declined to judge) | 0.018 | 0.018 |
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".