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Record W4390200877 · doi:10.1002/alz.076579

A longitudinal analysis of the frontotemporal dementia rating scale as a sensitive measure of disease trajectory

2023· article· en· W4390200877 on OpenAlexaff
Eve Ferry‐Bolder, Arabella Bouzigues, Phoebe H. Foster, Georgia Peakman, Caroline Greaves, Rhian S. Convery, John C. van Swieten, Lize C. Jiskoot, Harro Seelaar, Fermín Moreno, Raquel Sánchez‐Valle, Robert Laforce, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Barbara Borroni, Elizabeth Finger, Matthis Synofzik, Daniela Galimberti, Rik Vandenberghe, Alexandre de Mendonça, Christopher Butler, Alexander Gerhard, Simon Ducharme, Isabelle Le Ber, Pietro Tiraboschi, Isabel Santana, Florence Pasquier, Johannes Levin, Markus Otto, Sandro Sorbi, Jonathan D. Rohrer, Lucy L. Russell

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill UniversityWestern UniversityMontreal Neurological Institute and HospitalUniversity of TorontoOccupational Cancer Research CentreHealth Sciences CentreSunnybrook Health Science CentreUniversité Laval
Fundersnot available
KeywordsFrontotemporal dementiaFrontotemporal lobar degenerationClinical Dementia RatingAsymptomaticC9orf72Internal medicineMedicineDementiaRating scaleCohortDiseasePsychologyOncologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Background Previous research in genetic frontotemporal dementia (FTD) has suggested that the FTD Rating Scale (FRS) may be a more sensitive measure of disease severity than the Clinical Dementia Rating scale plus National Alzheimer’s Coordinating Centre Frontotemporal Lobar Degeneration score (CDR+NACC FTLD). This study aims to assess the potential of longitudinal measurement of the FRS to track disease trajectory, using data from the Genetic FTD Initiative (GENFI). Method 119 mutation negative controls and 270 mutation carriers (52 MAPT, 107 GRN, 111 C9orf72) from the GENFI cohort completed the FRS at their baseline and follow‐up visits. Participants were grouped by disease severity according to their CDR+NACC FTLD global score at the baseline visit, which generated five mutation groups: asymptomatic (0), prodromal (0.5), mild (1), moderate (2), and severe (3), plus the control group. Annualised FRS change scores were generated for each participant (mean interval between visits = 1.3 years, standard deviation = 0.6). For each of the genetic groups, correlations with annualised change score for the MMSE and the CDR+NACC FTLD SOB were performed. Result As disease becomes more severe, the annualised change in FRS was larger, peaking at the moderate stage: asymptomatic 0.6 (8.0), prodromal ‐5.1, (23.2), mild ‐7.2 (24.8), moderate ‐7.8 (11.6), severe ‐1.8 (8.2). The moderate group was significantly different from controls (p = 0.018) and the asymptomatic group (p = 0.030). The annualised change in FRS negatively correlated with the annualised change in CDR+NACC FTLD Sum of Boxes (Rho = ‐0.4, p<0.001) and positively correlated with the annualised change in MMSE (Rho = 0.3, p = 0.001) in GRN MCs but not in MAPT or C9orf72. Conclusion The FRS shows promise as a sensitive clinical outcome measure, but only at certain stages of the disease. More sophisticated modelling utilising the wider GENFI cohort will help to establish the real potential for use in clinical settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.048
GPT teacher head0.311
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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