01:49pm Thursday 17 August 2017

New model estimates smoking's legal attribution to lung cancer cases

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The model is based on the dose-response relationship between smoking and lung cancer, and the smoking pattern among lung cancer patients. Researchers measured the extent of smoking through a pack-years measure, which integrates the amount smoked per day and the number of years that the person smoked. The model was developed in response to a request from lawyers of a class action suit in Quebec against the tobacco industry on behalf of patients with lung cancer that was allegedly caused by smoking.

The researchers estimated that the amount of smoking required to satisfy the legal criterion of “more likely than not” is between 3 and 12 pack-years, depending on the modelling assumptions. Based on smoking patterns among lung cancer cases in Quebec, they further estimated that more than 90 percent of the cases satisfied even the most conservative of these thresholds and could be legally attributed to smoking.

 

“In Quebec, where there were about 6,200 newly diagnosed cases of lung cancer per year from 1995 to 2006, this translates to a total of about 5,700 cases per year that would satisfy the criterion of probability of causation greater than 0.50,” the researchers explain.

 

Source: American Journal of Public Health

 

Reference

 

Jack Siemiatycki, Igor Karp, Marie-Pierre Sylvestre, and Javier Pintos.  (2014). Estimating the Proportion of Cases of Lung Cancer Legally Attributable to Smoking: A Novel Approach for Class Actions Against the Tobacco Industry. American Journal of Public Health. e-View Ahead of Print.

 

Media contacts: Kimberly Short, American Journal of Public Health, 202-777-2511, Kimberly.Short@apha.org.

 

Jack Siemiatycki, University of Montreal, Canada, j.siemiatycki@umontreal.ca

 

Contact at the University of Montreal’s Office of Public Relations and Communications:

William Raillant-Clark
International Press Attaché
University of Montreal (officially Université de Montréal)
Tel: 514-343-7593


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