The real evidence for polymyalgia rheumatica as a paraneoplastic syndrome
Bibliographic record
Abstract
The aim of this study was to systematically consider the evidence for polymyalgia rheumatica (PMR) as a paraneoplastic disease. A systematic review of Medline and Embase was conducted from their inception to February 2017. Risk of bias was assessed using the Newcastle-Ottawa tool. Data were extracted regarding the PMR-cancer association, the types of cancer associated with PMR and the presentation of PMR patients subsequently diagnosed with cancer. Twenty-three full text articles were reviewed from the 1174 unique references identified in the search. Nine articles were included in the final review. There was some evidence of an association between PMR and cancer in the short-term (first 6 to 12 months after diagnosis), but no evidence of an association after this time. Limited evidence suggests that lymphoma, prostate and haematological cancers may be those cancers more commonly diagnosed in those with PMR. There was little evidence to suggest what presenting features may be associated with the development of cancer. There is little evidence of PMR as a true paraneoplastic disease. However, there is reason to be cautious when making the diagnosis of PMR. Clinicians should be aware of this potential association both prior to making a diagnosis and throughout the course of the condition.
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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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".