Incidence and clinical features of Langerhans cell histiocytosis in the UK and Ireland
Bibliographic record
Abstract
OBJECTIVES: There are few published studies on the epidemiology of Langerhans cell histiocytosis (LCH). We undertook a survey to ascertain all newly diagnosed cases aged 0-16 years in the UK and Republic of Ireland. DESIGN: Three methods of ascertainment were used: the British Paediatric Surveillance Unit (BPSU) system, a survey by Newcastle University, and the Children's Cancer and Leukaemia Group (CCLG) registry. Deaths data were obtained from the UK Office for National Statistics and the Central Statistics Office in Ireland. Clinicians who reported cases were sent a questionnaire to obtain demographic and clinical details. RESULTS: Over the 2-year period, 94 cases were identified. The age-standardised incidence rate of LCH in children aged 0-14 years was 4.1 per million per year. The sex ratio (M:F) was 1.5:1 and the median age at diagnosis was 5.9 years. Single system disease (predominantly bony involvement) accounted for 73% of cases and 27% had multisystem disease of whom 7% had involvement of "risk organs" (liver, lung, spleen and bone marrow). Three children died, two of whom were diagnosed after death. CONCLUSIONS: This is the first study of LCH to use an active surveillance method with additional sources of ascertainment. Our incidence is comparable with those in other national reports, although it is likely to be an underestimate as each method may have missed some cases, either diagnosed or undiagnosed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".