Consensus Report of the 2015 Weinman International Conference on Mesothelioma
Bibliographic record
Abstract
On November 9 and 10, 2015, the International Conference on Mesothelioma in Populations Exposed to Naturally Occurring Asbestiform Fibers was held at the University of Hawaii Cancer Center in Honolulu, Hawaii. The meeting was cosponsored by the International Association for the Study of Lung Cancer, and the agenda was designed with significant input from staff at the U.S. National Cancer Institute and National Institute of Environmental Health Sciences. A multidisciplinary group of participants presented updates reflecting a range of disciplinary perspectives, including mineralogy, geology, epidemiology, toxicology, biochemistry, molecular biology, genetics, public health, and clinical oncology. The group identified knowledge gaps that are barriers to preventing and treating malignant mesothelioma (MM) and the required next steps to address barriers. This manuscript reports the group's efforts and focus on strategies to limit risk to the population and reduce the incidence of MM. Four main topics were explored: genetic risk, environmental exposure, biomarkers, and clinical interventions. Genetics plays a critical role in MM when the disease occurs in carriers of germline BRCA1 associated protein 1 mutations. Moreover, it appears likely that, in addition to BRCA1 associated protein 1, other yet unknown genetic variants may also influence the individual risk for development of MM, especially after exposure to asbestos and related mineral fibers. MM is an almost entirely preventable malignancy as it is most often caused by exposure to commercial asbestos or mineral fibers with asbestos-like health effects, such as erionite. In the past in North America and in Europe, the most prominent source of exposure was related to occupation. Present regulations have reduced occupational exposure in these countries; however, some people continue to be exposed to previously installed asbestos in older construction and other settings. Moreover, an increasing number of people are being exposed in rural areas that contain noncommercial asbestos, erionite, and other mineral fibers in soil or rock (termed naturally occurring asbestos [NOA]) and are being developed. Public health authorities, scientists, residents, and other affected groups must work together in the areas where exposure to asbestos, including NOA, has been documented in the environment to mitigate or reduce this exposure. Although a blood biomarker validated to be effective for use in screening and identifying MM at an early stage in asbestos/NOA-exposed populations is not currently available, novel biomarkers presented at the meeting, such as high mobility group box 1 and fibulin-3, are promising. There was general agreement that current treatment for MM, which is based on surgery and standard chemotherapy, has a modest effect on the overall survival (OS), which remains dismal. Additionally, although much needed novel therapeutic approaches for MM are being developed and explored in clinical trials, there is a critical need to invest in prevention research, in which there is a great opportunity to reduce the incidence and mortality from MM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.046 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".