Therapeutic trial design for frontotemporal dementia and related disorders
Bibliographic record
Abstract
The frontotemporal dementia (FTD) spectrum is a heterogeneous group of neurodegenerative syndromes with overlapping clinical, molecular and pathological features, all of which challenge the design of clinical trials in these conditions. To date, no pharmacological interventions have been proven effective in significantly modifying the course of these disorders. This study critically reviews the construct and methodology of previously published randomised controlled trials (RCTs) in FTD spectrum disorders in order to identify limitations and potential reasons for negative results. Moreover, recommendations based on the identified gaps are elaborated in order to guide future clinical trial design. A systematic literature review was carried out and presented in conformity with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. A total of 23 RCTs in cohorts with diagnoses of behavioural and language variants of FTD, corticobasal syndrome and progressive supranuclear palsy syndrome were identified out of the 943 citations retrieved and were included in the qualitative review. Most studies identified were early-phase clinical trials that were small in size, short in duration and frequently underpowered. Diagnoses of populations enrolled in clinical trials were based on clinical presentation and rarely included precision-medicine tools, such as genetic and molecular testing. Uniformity and standardisation of research outcomes in the FTD spectrum are essential. Several elements should be carefully considered and planned in future clinical trials. We anticipate that precision-medicine approaches will be crucial to adequately address heterogeneity in the FTD spectrum research.
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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 | 0.062 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".