Paraneoplastic neurological syndromes: a practical approach to diagnosis and management
Bibliographic record
Abstract
Paraneoplastic neurological syndromes (PNS) are the immune-mediated effects of a remote cancer and are characterised by an autoantibody response against antigens expressed by the tumour. Classically, well-characterised 'onconeuronal' antibodies target intracellular antigens and hence cannot access their antigens across intact cell membranes. The pathogenic mediators are likely to be neuronal-specific T cells. There is a variable response to immunotherapies and the clinical syndrome helps to direct the search for a specific set of tumours. By contrast, many newly emerging autoantibodies with oncological associations target cell surface epitopes and can exert direct pathogenic effects on both the central and peripheral nervous systems. Patients with these cell-surface directed autoantibodies often clearly respond to immunotherapies. Overall, the clinical, serological and oncological features in an individual patient help to determine the clinical relevance of the syndrome and hence guide its management. We summarise current knowledge and a practical approach to the investigation, diagnosis, treatment and outcomes of patients with suspected PNS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".