Differentiating Sporadic behavioural variant Frontotemporal Dementia from late‐onset Primary Psychiatric Disorders: the DIPPA‐FTD study
Bibliographic record
Abstract
BACKGROUND: Sporadic bvFTD is often misdiagnosed as a primary psychiatric disorder (PPD) due to overlapping clinical features and lack of reliable biomarkers. The multi-centre study DIPPA-FTD aims to develop diagnostic- and prognostic-algorithms that can distinguish sporadic bvFTD from late-onset PPD. The aim of the retrospective DIPPA-FTD study was to identify the strongest clinical discriminators. METHOD: DIPPA-FTD has compiled a retrospective database with 508 sporadic bvFTD and 152 late-onset PPD cases from five cohorts, making it the largest sporadic FTD cohort to date. Logistic regression models and ROC curve analysis were applied to determine discriminative value per clinical marker in separate subsets; (i) neuropsychological features, (ii) visual brain atrophy rating scales and (iii) serum NfL+GFAP. A global (backward stepwise) logistic regression was also conducted in the most optimal subset that had all markers per modality available. All models were adjusted for age, sex and education when indicated. RESULT: For marker (i) (bvFTD n = 217, PPD n = 75) higher scores of letter fluency (OR:1.47, p<0.001), global cognitive screening (OR:1.72, p = 0.01) and lower attention scores (OR:0.77, p = 0.05) were significantly associated with increased likelihood of PPD and reached an AUC of 0.77. Marker (ii) visual atrophy rating composite score (bvFTD n = 211, PPD n = 112) reached diagnostic accuracy of 79% and fronto-insula was the most useful discriminator (AUC 0.80). Analysis of marker (iii) NfL+GFAP (bvFTD n = 275, PPD n = 82) showed that NfL and GFAP levels were significantly higher in bvFTD. Combination of NfL+GFAP yielded highest AUC value (0.88). The combined dataset with all markers variables available (bvFTD n = 120, PPD n = 40) reached an AUC of 0.89. Higher NfL (OR:1.09, p<0.01), more atrophy in fronto-insula (OR:2.38, p = 0.02) and enlarged mean ventricular space (OR:3.84, p = 0.05) were significant predictors for sporadic bvFTD. CONCLUSION: Global cognition, letter fluency and attention scores, fronto-insula brain atrophy and NfL+GFAP have a significant role in discriminating sporadic bvFTD from PPD. Combination of markers can increase diagnostic accuracy in clinical setting. Promising markers identified in this retrospective study will be validated in the prospective DIPPA-FTD study and integrated in a data-driven approach to develop diagnostic and prognostic tools, enabling early-stage diagnosis sporadic bvFTD which is required for trial enrolment.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".