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Record W4206005779 · doi:10.1002/mds.28909

Age‐Adjusted Serum Neurofilament Predicts Cognitive Decline in Parkinson's Disease (<scp>MARK‐PD</scp>)

2022· letter· en· W4206005779 on OpenAlexaboutno aff
Carsten Buhmann, Susanne Lezius, Monika Pötter‐Nerger, Christian Gerloff, Jens Kühle, Chi‐un Choe

Bibliographic record

VenueMovement Disorders · 2022
Typeletter
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersElse Kröner-Fresenius-Stiftung
KeywordsCognitive declineMontreal Cognitive AssessmentInternal medicineDementiaCohortParkinson's diseasePopulationPsychologyMedicineReceiver operating characteristicRating scaleDiseaseGerontologyDevelopmental psychology

Abstract

fetched live from OpenAlex

We read with great interest the study by Aamodt and colleagues reporting that plasma neurofilament light (NfL) chain levels are associated with UPDRS III (Unified Parkinson's Disease Rating Scale, Part III) score but not the Mattis Dementia Rating Scale (DRS-2), whereas plasma NfL predicted cognitive decline (DRS-2 change) but not motor worsening (UPDRS III ≥5 points).1 Interestingly, these findings are in line with our results that serum NfL was associated with UPDRS III but not Montreal Cognitive Assessment (MoCA) score, whereas serum NfL predicted cognitive decline (decrease in MoCA score >2 points) but not motor worsening (increase in UPDRS III >4 points) in the Biomarkers in Parkinson's Disease (MARK-PD) study.2 Numerous studies have shown that blood NfL predicts cognitive decline in patients with Parkinson's disease, but cutoff values determined by receiver operating characteristic (ROC) analysis revealed very different results.1-3 Given that serum NfL levels increase by 3.35% per year in PD patients and double in individuals above 70 years compared with those below 50 years in the normal population, age is the most important covariate of NfL variability.4, 5 Consequently, we hypothesize that age-adjusted NfL percentiles might reveal more consistent results among cohort studies compared with absolute NfL values for the prediction of disease progression in PD patients. Therefore, we evaluated if the plasma NfL cutoff value of 14.6 pg/mL determined by Aamodt and colleagues also predicts cognitive decline in the Mark-PD study.6 Furthermore, we analyzed if age-adjusted serum NfL above the 95th percentile predicts cognitive decline in MARK-PD. In MARK-PD, serum NfL and cognitive outcome (initial and follow-up MoCA scores) were available for 106 patients with PD (age: 64.6 ± 8.8 years, men: 60.4%, disease duration: 12 [7.5, 15.5] years, follow-up: 512 [365, 680] days). During follow-up, we registered 21 patients with cognitive decline (decrease in MoCA score >2 points). In a Kaplan–Meier analysis, we observed no association between serum NfL levels and faster cognitive decline using a cutoff value of 14.6 pgl/mL (log-rank test: P = 0.322) (Fig. 1A). However, patients with NfL levels above the age-adjusted 95th percentile revealed a significantly faster cognitive decline (P = 0.026) than those below (Fig. 1B). This difference remained significant after further adjustment for age, sex, disease duration, and initial MoCA score (P = 0.017) (Fig. 1C). In summary, both studies using different cognitive scales (ie, DRS-2 and MoCA) show that increased NfL levels predict cognitive decline in PD patients. We suggest that NfL levels above the age-adjusted 95th percentile are independently associated with cognitive decline. We propose that age-adjusted NfL cutoffs might reveal more consistent results across different cohort studies and therefore facilitate the establishment of NfL as a clinically useful blood-based biomarker in patients with PD. The data that support the findings of this study are available from the corresponding author upon reasonable request.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.348
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations16
Published2022
Admission routes1
Has abstractyes

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