Abstract P2-09-02: ICRP analysis: Environmental influences in breast cancer
Bibliographic record
Abstract
Abstract The International Cancer Research Partnership (ICRP[1]) is an alliance of governmental and charitable organizations from the USA, Canada, Europe, Australia and Japan funding regional, national and international cancer research grants and awards. One key activity of the partnership is a database of information about member’s funded grant projects (N>60,000 grants, from 80 members, totalling over $14 billion USD). Each project is coded to a Common Scientific Outline (CSO), a classification system of broad areas of cancer research. Breast cancer is the most common cancer in women worldwide, however, only about 5-10% of breast cancer is attributable to genetic predisposition,[2] and about one third of cases are attributable to known genetic or other risk factors. In 2013, the Interagency Breast Cancer and Environmental Research Coordinating Committee (IBCERCC)[3] recommended that funding organizations plan strategically to accelerate the pace of scientific research on breast cancer and the environment. Thus, the ICRP has developed a mechanism to track activity and trends in research into environmental influences on breast cancer, to provide a baseline for future assessment of progress. Methods: ICRP-funded grants related to environmental influences on breast cancer were queried from the ICRP database. We focused on three time points: awards that were active in 2006, 2008 or 2010. The search resulted in a pool of 11983 breast cancer-relevant awards that was narrowed further to 1107 awards of relevance using a combination of keyword searches and specific Common Scientific Outline (CSO) codes.[4] Relevant awards were then coded with the assistance of keywords and manual review, to one or more, of 6 categories of environmental research: Behavior-Lifestyle, Behavior-Tobacco exposure, Chemicals-Chemical pollutants, Chemicals-Exogenous hormones, General Infection-Microorganisms and Radiation. Results: Between 2006 and 2010, the numbers of active awards declined and funding levels also fell. Most of the funded research is focused on behavioral/lifestyle factors in breast cancer (e.g., diet, alcohol intake, and shift work patterns). Further analysis of the Behavioral/Lifestyle category reveals that the major area of activity is in the role of nutrition/alcohol in cancer, closely followed by the contribution of obesity and reproductive factors (age of menarche, parity etc.). Conclusion: We were able to utilize a CSO ‘filter’ to identify trends in funded grant projects related to the environment and breast cancer. The decline in numbers and research funding between 2006 and 2010 is concerning. As breast cancer incidence continues to increase, research efforts to understand the causes of increased incidence are essential. Further research investment in these areas may be required. [1] https://www.icrpartnership.org/index.cfm [2] http://www.niehs.nih.gov/health/assets/docs_a_e/environmental_factors_and_breast_cancer_risk_508.pdf [3] https://www.niehs.nih.gov/about/assets/docs/summary_of_recs_508.pdf (Accessed 28/2/14) [4] CSO areas 2.1, 2.3, 1.2, 2.4, 6.2 (Etiology, Basic Biology of cancer initiation, and surveillance). Citation Format: Marc S Hurlbert, Senaida Poole, Kari Wojtanik, Samantha Finstad, Lynne Davies. ICRP analysis: Environmental influences in breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-09-02.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.036 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".