Pleural Mesothelioma Surveillance: Validity of Cases from a Tumour Registry
Bibliographic record
Abstract
BACKGROUND: Pleural mesothelioma is a rare tumour associated with exposure to asbestos fibres. Fewer than than one-quarter of cases registered in the Quebec Tumour Registry (QTR) have been compensated as work-related. While establishing a surveillance system, this led to questioning as to whether there has been over-registration of cases that are not authentic pleural mesotheliomas in the QTR. OBJECTIVE: To assess whether registered cases of pleural mesothelioma could be confirmed. METHODS: A medical chart review was designed to assess the proportion of mesothelioma cases newly registered in the QTR in 2001⁄2002 that could be confirmed. For each registered case, clinical, medical imaging and pathology information were sought and, occasionally, additional immunohistochemistry staining was obtained. Three specialists - a chest physician, a radiologist and a pathologist - reviewed the available information and material, coding each mesothelioma case as to degree of certainty of the mesothelioma diagnosis. RESULTS: The QTR reported 190 incident cases of mesothelioma (81% males) for the period. The specialists classified 81% of charts as 'certain⁄probable' or 'possible' mesotheliomas, 8% as 'unlikely to be a mesothelioma' and 11% as 'not a mesothelioma'. After excluding chart summaries of unsatisfactory quality, 87% to 88% of the charts were classified as 'certain⁄probable' or 'possible' mesotheliomas, and 9% to 11% were still considered 'not a mesothelioma'. CONCLUSION: Tumour registry data are a valid source of information for mesothelioma surveillance. While there is some over-registration of mesothelioma cases in the QTR, a significant majority of registered cases appeared to be authentic. Over-registration cannot explain the greater proportion of cases that were not compensated.
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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 | 0.018 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".