Discordance and Concordance Between Cerebrospinal and [ <sup>18</sup> F]FDG-PET Biomarkers in Assessing Atypical and Early-Onset AD Dementia Cases
Bibliographic record
Abstract
Background and Objectives To assess the concordance and discordance between the core Alzheimer disease (AD) CSF biomarkers and [18F]fluorodeoxyglucose (FDG)-PET patterns evaluated clinically in memory clinic patients who meet appropriate use criteria for AD biomarker investigations. Methods We retrospectively assessed participants with atypical and/or early-onset dementia evaluated at a tertiary care memory clinic. All individuals underwent CSF evaluations for Aβ42, phosphorylated tau (P-tau181) and total tau, and brain [18F]FDG-PET. [18F]FDG-PET data were visually interpreted by 2 nuclear medicine experts as being consistent with AD or non-AD. CSF biomarker results were similarly grouped into AD biomarker positive/negative. Contingency tables and Kappa coefficients were used to establish the level of agreement and disagreement between CSF and [18F]FDG-PET results in all individuals. Results One hundred thirty-six individuals had both [18F]FDG-PET and lumbar puncture performed as part of the early-onset and/or atypical dementia assessments. [18F]FDG-PET showed a pattern suggestive of AD in 43% of patients, while CSF biomarkers showed results consistent with AD in 57% of participants. In patients who met criteria for AD biomarker investigations, we found that [18F]FDG-PET was discordant with CSF AD biomarkers in nearly 20% of cases; 12% of individuals with [18F]FDG-PET scans consistent with AD had AD-negative CSF results; and 7% of individuals with [18F]FDG-PET scans not consistent with AD had AD-positive CSF results, potentially suggesting atypical AD variants or less advanced neurodegeneration. [18F]FDG-PET discriminated patients with an AD-positive CSF profile from patients with an AD-negative profile with a sensitivity and specificity higher than 80% (sensitivity: 81%, 95% CI = 71–88%, SP: 81%, 95% CI = 68–89%). Furthermore, [18F]FDG-PET had a positive predictive value of 87% (95% CI = 78–93%) and a negative predictive value of 72% (95% CI = 60–82%). Discussion CSF and [18F]FDG-PET disagreed in nearly 20% of the cases studied in this clinical series. While CSF Aβ42 and P-tau181 biomarkers are specific for AD, the topographical information from [18F]FDG-PET may provide complementary information.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".