Impact of asbestos exposure on survival and treatment of patients with malignant mesothelioma.
Bibliographic record
Abstract
e17507 Background: Malignant mesothelioma is a rare pleural cancer heavily correlated to asbestos exposure. However, the number of mesotheliomas without any known exposure to asbestos is surely increasing. The impact of asbestos exposure on patient survival and response to standard treatment is unknown. We retrospectively analyzed 49 consecutive patients diagnosed with malignant mesothelioma using an unselected SARDO database at Notre-Dame Hospital from 2006 to 2009. Methods: Patients were sorted into 2 groups based on reported asbestos exposure status, mostly on patient’s working exposure. Demographic and treatment data were collected and analyzed with Kaplan-Meier survival plots and log-rank tests. Results: The median survival was 22.6 months for the entire 49 patients, overall survival at 1 year 86.4% and at 2 years 47.3%. Median survival of exposed patients (n = 20) was 22.6 months and that of non-exposed patients (n = 29) was 59.5 months. However, survival was not significantly different between the 2 groups (p = 0.450), despite there was no treatment difference in between 2 cohorts. Most patients were men (n = 42) and women (n=7) generally belonged to the non-exposed group. 3 patients had surgical treatment (pleurectomy with either pneumonectomy or lobectomy), but their survival was not statistically superior (p = 0.091) despite a clear trend. Patients younger than 65 years did not have better survival. Conclusions: Although asbestos exposure clearly increases the risk of mesothelioma, it does not seem to have an impact on the overall survival of patients with malignant mesothelioma neither on the efficiency of their treatment. However, a reliable serum biomarker of asbestos exposure would probably be necessary to make sure patients with no working exposure have really no exposure in other circumstances to asbestos.
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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 | 0.002 |
| 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) | 0.001 | 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".