Occupational cancer: public health interventions to minimize its burden and impact on the society.
Bibliographic record
Abstract
Cancer has emerged as a major public health concern owing to its magnitude, worldwide distribution, impact on the quality of life, financial burden on the patient / family / society / health care delivery system, and associated mortality. Findings of a study have shown that approximately 19% of all types of cancers have been attributed to the environmental factor. Almost 900 potential carcinogens have been identified and evaluated for their carcinogenic potential in the workplace, a major fraction of which is preventable. A wide range of potential factors have been identified that have contributed to the rising trends of occupational cancer. In order to reduce the magnitude of occupational cancer, there is an immense need to formulate a holistic strategy which should respond to the needs of all stakeholders. To conclude, a significant rise has been observed in the incidence of occupational cancer and there is an immense need to plan and implement scientific interventions to minimize thousands of unnecessary deaths and suffering from occupational cancer. References Pruss-Ustun A, Corvalan C. Preventing disease through healthy environments: Towards an estimate of the environmental burden of disease. Geneva: WHO press; 2006. Available from:http://www.who.int/quantifying_ehimpacts/publications/preventingdiseasebegin.pdf. (accessed March 2014) International Agency for Research on Cancer [Internet]. GLOBOCAN 2012: Estimated cancer incidence, mortality and prevalence worldwide in 2012. [update 2014]. Available from: http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx/. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010; 127(12):2893-917. Christiani DC. Combating environmental causes of cancer. N Engl J Med. 2011; 364(9):791-3. Blair A, Marrett L, Beane Freeman L. Occupational cancer in developed countries. Environ Health. 2011; 10(Suppl 1):S9. Pandey KR. Occupational cancer kills more than 200,000 people a year. BMJ. 2007; 334(7600):925. Santana VS, Ribeiro FS. Occupational cancer burden in developing countries and the problem of informal workers. Environ Health. 2011; 10(Suppl 1):S10. Lee LJ, Chang YY, Liou SH, Wang JD. Estimation of benefit of prevention of occupational cancer for comparative risk assessment: methods and examples. Occup Environ Med. 2012; 69(8):582-6. Binazzi A, Scarselli A, Marinaccio A. The burden of mortality with costs in productivity loss from occupational cancer in Italy. Am J Ind Med. 2013; 56(11):1272-9. Straif K, Benbrahim-Tallaa L, Baan R, Grosse Y, Secretan B, El Ghissassi F, et al. A review of human carcinogens--part C: metals, arsenic, dusts, and fibres. Lancet Oncol. 2009; 10(5):453-4. Muirhead CR, Haylock R. Ionising radiation and occupational cancer in Britain. Br J Cancer. 2012; 107(9):1660-1. Hutchings SJ, Rushton L; British occupational cancer burden study group. Occupational cancer in Britain. Industry sector results. Br J Cancer. 2012; 107(Suppl 1):92-103. Park K. Occupational Health. In: Park K, editor. Text Book of Preventive and Social Medicine. 20th ed. Jabalpur: Banarsidas Bhanot Publishers; 2009; p.710-9. Zare Sakhvidi MJ, Mirzaei Aliabadi M, Sakhvidi FZ, Halvani G, Morowatisharifabad MA, Tezerjani HD, et al. Occupational cancer risk perception in Iranian workers. Arch Environ Occup Health. 2014; 69(3):167-71. Verger P, Pardon C, Dumesnil H, Charrier D, De Labrusse B, Lehucher-Michel MP, et al. Occupational physicians' attitudes and practices in relation to occupational cancer prevention: a qualitative study in southeastern France. Int J Occup Environ Health 2010; 16(3):320-9. Huff J. Occupational cancer and social inequities. Eur J Public Health. 2011; 21(1):129. 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Epidemiol Prev. 2009; 33(4-5 Suppl 2):85-93. Vlaanderen J, Vermeulen R, Heederik D, Kromhout H; ECNIS integrated risk assessment group, European union network of excellence. Guidelines to evaluate human observational studies for quantitative risk assessment. Environ Health Perspect. 2008; 116(12):1700-5.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".