ArticleNPJ Parkinson's disease2025
Systematic review of prognostic models in Parkinson's disease.
Article in NPJ Parkinson's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Developing prognostic models that predict onset and progression rates in genetic neurodegenerative diseases: perspectives of healthcare professionals in genetic counselling.Orphanet journal of rare diseases · 2026Article
- Evaluating multivariable prediction models for Parkinson's disease prognosis: a scoping review protocol.BMJ open · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting outcomes for people with Parkinson's (PwP) can enable better information provision, personalised treatments, and enhanced trial design. It is unclear what prognostic models are optimal for use. We systematically reviewed previously published prognostic models for PwP, assessed quality, and made recommendations. We searched MEDLINE and EMBASE for studies developing/validating models predicting clinical outcomes in PwP. We assessed risk of bias and applicability using the PROBAST tool. We screened 1024 references and identified 25 studies (41 prognostic models). The most common outcomes were falls (11 studies), dementia (7) and motor complications (4). Most models made short-term predictions (60% ≤2 years). All studies had concerns about bias, e.g., inadequate population details (n = 16), suboptimal methods for missing data (n = 21), and no external validation (n = 22). 13 models had sufficient information to be used in practice. Further development and validation of prognostic models is needed which follows existing guidelines to reduce risk of bias.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.