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American Public Health Association
133rd Annual Meeting & Exposition
December 10-14, 2005
Philadelphia, PA
APHA 2005
 
5180.0: Wednesday, December 14, 2005 - 3:06 PM

Abstract #116353

Silica and Lung Cancer: A Monte Carlo Analysis

Dean Hosgood, Yale University School of Epidemiology and Public Health, Environmental Health Sciences, 60 College Street, P.O. Box 208034, New Haven, CT 06511, 203-789-2051, dean.hosgood@yale.edu, Martin Slade, Yale Occupational and Environmental Medicine Program, Yale University, 135 College St, Room 366, New Haven, CT 06510-2283, and Jonathan B. Borak, MD, DABT, School of Medicine, Yale University, 234 Church ST, Suite 1100, New Haven, CT 06510.

Controversies and disagreements have surrounded recent quantitative and weight-of-evidence risk assessments (e.g., IARC) for silica-induced carcinogenicity. IARC (1997) noted that carcinogenicity was not present in all industrial settings, while Graham et al (J Occup Environ Med 46:459-466; 2004) and Attfield and Costello (Am J Ind Med 45:129-138; 2004) reached opposite conclusions for the same worker cohort. One potential source of such disagreement is that historical exposure assessments have relied on different exposure metrics (e.g., particles counts vs. gravimetric weight) that are not linearly related and not directly interconvertible. Accordingly, it seemed possible that divergent results of risk assessments might reflect inconsistent approaches to the estimation of historical exposures. To evaluate that possibility, we used Monte Carlo analyses to estimate probability-based conversion factors in order to integrate five historical exposure assessments of Vermont granite workers. We anticipate that use of such conversion factors will allow reconciliation of silica risk assessments that otherwise seem discordant and irreconcilable.

Learning Objectives:

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.

Quantitative Methods in OSH

The 133rd Annual Meeting & Exposition (December 10-14, 2005) of APHA