Familial aggregation of malignant mesothelioma in former workers and residents of Wittenoom, Western Australia
Bibliographic record
Abstract
Clustering of cases of malignant mesothelioma within families has often been observed, but disentangling genetic and exposure effects has not been done. Former workers and residents exposed to crocidolite at Wittenoom, Western Australia, where many families shared exposure to asbestos, have had high rates of mesothelioma. Our study aimed to estimate the additional risk of mesothelioma in relatives, after allowance for common exposure to crocidolite. More than 11,000 former asbestos workers and residents from Wittenoom have been followed up in cancer and death registries. Levels of exposure for all members of the Wittenoom cohorts have been estimated previously. Relationships between family members of all mesothelioma cases were established from questionnaires, birth and death certificates. Expected numbers of cases of mesothelioma were estimated by fitting a Weibull survival model to all data, based on time from first asbestos exposure, duration and intensity of exposure and age. For each family group, the earliest case was considered the index case. Predicted risk was estimated for each subject from the time of diagnosis of the index case. Familial risk ratios were estimated by dividing observed cases by the sum of risks of all same degree relatives of index cases. There were 369 family groups with at least one case of mesothelioma and a further 25 cases of mesothelioma among relatives in the same families, with 12.9 expected. The risk ratio for blood relatives was 1.9 (95% confidence interval [CI] = 1.3-2.9, p = 0.002). These findings suggest an important, but not large, genetic component in mesothelioma, similar to many other cancers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".