Bibliographic record
Abstract
Abstract Background The Frontotemporal dementia Prevention Initiative (FPI) is a collaborative group made up of familial FTD (fFTD) research groups across the world. This includes the Genetic FTD Initiative (GENFI) in Europe and Canada, ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) in the USA, the Multi‐partner consortium to expand dementia research in Latin America (ReDLat), the Dominantly Inherited Non‐Alzheimer’s Dementias (DINAD) in Australia, and The New Zealand Genetic FTD Study (FTDGeNZ). Initial efforts have been focused on individuals from families who are known to carry mutations in the C9orf72, GRN and MAPT genes. Methods To advance therapeutic trials for fFTD, data has been shared within the FPI across the different cohort studies to understand the stratification and disease progression of mutation carriers. As well as the development of a large network of ‘trial‐ready’ participants for upcoming trials, with further extension of this network to Asia, the FPI also aims to develop a set of principles for fFTD trials that will guide data and sample sharing. Results An initial FPI project has shown the range of ages at symptom onset (AAO), death and duration in fFTD, with relatively poor correlation of individual AAO with both parental and family AAO, particularly in those with C9orf72 and GRN mutations. Further work has shown the ability of blood neurofilament light chain protein levels to predict subsequent disease progression. Lastly, a combination of clinical, cognitive, imaging and fluid biomarker data has allowed the development of disease progression models that will be useful in future clinical trial design. Conclusions The FPI is the first initiative to bring together the academic fFTD community to contribute to a global effort to find therapeutics for this devastating disease. Future work aims to extend the network and continue to establish our partnerships with our families, patient advocacy groups, and industry partners.
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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 | 0.027 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.072 | 0.009 |
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".