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Refining the diagnostic accuracy of Parkinsonian disorders using metaphenomic annotation of the clinicopathological literature
Quin Massey, Leonidas Nihoyannopoulos, Peter Zeidman, Thomas T. Warner, Kailash P. Bhatia, Sonia Gandhi, Christian Lambert. npj Parkinson s Disease, 2025-11-10
Topic: Brain proteins, microglia and lab models
The diagnostic precision of Parkinsonian disorders is not accurate enough. Even in expert clinics, up to one in five diagnoses are incorrect. Gold standard diagnosis is post-mortem confirmation of the underlying proteinopathy; however, many clinicopathological studies focus on either a single disease or frame analyses in one temporal direction that may underestimate the true extent of mis- and missed diagnoses. We identified 125 published clinicopathological studies since 1992, extracted phenotype information for ~9200 post-mortem cases, curated the data in a standardised machine-readable format and used this to develop a probabilistic model to quantify diagnostic likelihood based on clinical observations. We found diagnostic accuracy was highest for multiple system atrophy (MSA, 92.8%) and lowest for dementia with Lewy bodies (DLB, 82.1%). MSA and progressive supranuclear palsy were most frequently mis-labelled as Parkinson's disease (PD) in life (7.2% and 8.3% of cases), whereas the most common PD misdiagnosis was Alzheimer's (~7% cases). We calculated likelihood ratios for a large range of clinical phenotypes and demonstrated how these can be used to help refine and improve diagnostic accuracy. This work delivers a harmonised, open-source dataset representing over 30 years of published results and represents a key foundation for flexible predictive models that leverage different sources of information to better discriminate Parkinsonian disorders during the early and prodromal phases of the illness.
Key findings
- We found diagnostic accuracy was highest for multiple system atrophy (MSA, 92.8%) and lowest for dementia with Lewy bodies (DLB, 82.1%).
- We calculated likelihood ratios for a large range of clinical phenotypes and demonstrated how these can be used to help refine and improve diagnostic accuracy.
- This work delivers a harmonised, open-source dataset representing over 30 years of published results and represents a key foundation for flexible predictive models that leverage different sources of information to better discriminate Parkinsonian disorders during the early and prodromal phases of the illness.
Why it matters
This study found that diagnostic accuracy for Parkinsonian disorders was highest for multiple system atrophy and lowest for dementia with Lewy bodies, with many cases mislabeled in life. The researchers developed a probabilistic model and likelihood ratios to help refine and improve diagnostic accuracy.
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Study details
- Effect size92.8%; 82.1%; 7.2%
- Evidence strengthLow
How this study scored 40/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (npj Parkinson s Disease) |
| Journal's citation record | 1 / 4 | Npj Parkinson s Disease: journal h-index 87 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 1.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Christian Lambert: h-index 27 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University College London: institution h-index 2,029 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41213966) |
| Free to read | 2 / 2 | Free to read |
| Total | 40 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1038/s41531-025-01157-y
- PubMed: 41213966
- Original source →
- Free full text: npj Parkinson s Disease →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Massey, Q., Nihoyannopoulos, L., Zeidman, P., Warner, T. T., Bhatia, K. P., Gandhi, S., et al. (2025). Refining the diagnostic accuracy of Parkinsonian disorders using metaphenomic annotation of the clinicopathological literature. npj Parkinson s Disease. https://doi.org/10.1038/s41531-025-01157-y
Vancouver
Massey Q, Nihoyannopoulos L, Zeidman P, Warner TT, Bhatia KP, Gandhi S, et al. Refining the diagnostic accuracy of Parkinsonian disorders using metaphenomic annotation of the clinicopathological literature. npj Parkinson s Disease. 2025. doi:10.1038/s41531-025-01157-y. PMID: 41213966.
BibTeX
@article{massey2025-41213966,
author = {Massey, Quin and Nihoyannopoulos, Leonidas and Zeidman, Peter and Warner, Thomas T. and Bhatia, Kailash P. and Gandhi, Sonia and Lambert, Christian},
title = {{Refining the diagnostic accuracy of Parkinsonian disorders using metaphenomic annotation of the clinicopathological literature}},
journal = {npj Parkinson s Disease},
year = {2025},
doi = {10.1038/s41531-025-01157-y},
pmid = {41213966},
url = {https://doi.org/10.1038/s41531-025-01157-y}
}
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