Changing Clinical and Laboratory Characteristics of Progressive Multifocal Leukoencephalopathy: A Retrospective National Cohort Study
Bibliographic record
Abstract
BACKGROUND: Progressive multifocal leukoencephalopathy (PML) is a severe demyelinating disease caused by JC polyomavirus (JCV), affecting immunocompromised individuals. We describe PML demographic, clinical, radiological, and laboratory characteristics and survival over time and according to underlying condition in a large retrospective patient cohort. METHODS: This is a retrospective cohort including Italian PML patients observed between 1987 and 2024, with known year of diagnosis and underlying disease. RESULTS: We included 456 cases with either a definite (n = 376, 82.4%) or clinico-radiological (n = 80, 17.6%) PML diagnosis. The relative frequency of human immunodeficiency virus (HIV)-associated cases decreased through four time periods (1987-1996; 1997-2004; 2005-2012; 2013-2024) from 99% to 43%, in parallel with increasing age (P < .0001), proportion of women (P < .001) and CD4+ counts (P < .001) but not cerebrospinal fluid (CSF) or plasma JCV-DNA levels at diagnosis. One-year survival probability increased from 23.8% in 1987-1996 to 59.2% in 2013-2024, with highest values in natalizumab-treated multiple sclerosis (93.8%), followed by combination antiretroviral treatment (cART)-treated HIV infection (55%), hematological malignancies (50.8%), primary immunodeficiencies (41.3%), and cART-untreated HIV infection (11.9%). At multivariate analysis excluding cART-untreated people with HIV, JCV-DNA levels in both CSF and plasma were independently associated with an increased mortality risk of 2.9% and 7.2%, respectively, for each Log increase in JCV-DNA. CONCLUSIONS: This observational study showed a changing epidemiological context over 37 years. Although survival improved over time, it remained poor even in the last decade, with a one-year survival probability of 59.2%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".