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Re: analysis of dioxin cancer threshold.


Mackie et al. (2003) present an exploratory Monte Carlo meta-regression of selected cohort mortality and exposure data for three dioxin-exposed cohorts [National Institute for Occupational Safety and Health National Institute for Occupational Safety and Health,
n.pr an institute of the Centers for Disease Control and Prevention that is responsible for assuring safe and healthful working conditions and for developing standards of safety and health.
 (NIOSH NIOSH National Institute for Occupational Safety & Health, see there

NIOSH Recommendations for Safety & Health Standards

Agent  NIOSH REL*/OSHA PEL  Health effects
), Ranch Hand, and Seveso] as a critique of our earlier publication of a similar analysis (Kirman et al. 2000). Although we appreciate that our preliminary examinations of the cohort mortality dose-response data have been followed by more detailed analyses of these data (e.g., Crump et al. 2003), we disagree with a number of Mackie et al.'s procedures, assertions, and conclusions.

Mackie et al. (2003) assert that no weighting of the individual cohort data points is necessary and that a linear regression Linear regression

A statistical technique for fitting a straight line to a set of data points.
 of the unweighted dose-response data is appropriate. We disagree. The data used in the regression analysis In statistics, a mathematical method of modeling the relationships among three or more variables. It is used to predict the value of one variable given the values of the others. For example, a model might estimate sales based on age and gender.  include observations obtained for groups ranging from 19 individuals (Ranch Hand Group R4) to 15,000 individuals (Seveso Zone R females). In an unweighted regression, dose-response information from these two groups is weighted equally, which is clearly inappropriate. Weighting by sample size, while relatively simplistic sim·plism  
n.
The tendency to oversimplify an issue or a problem by ignoring complexities or complications.



[French simplisme, from simple, simple, from Old French; see simple
, eliminates the sensitivity of the regression results to either study size or data-grouping decisions of the study authors. For example, the unweighted fits by Mackie et al. would have been quite different if the results for women in Seveso Zone R had been reported for 789 groups of 19 individuals rather than one group of 15,000. The data are probably best analyzed using a Poisson regression. Estimators produced by maximizing the likelihood function in a Poisson regression are generally preferred over those produced by least squares based on their statistical properties, and the data are automatically weighted based on the expected number of deaths (highly correlated with population size). The results of a Poisson regression would be expected to be nearly identical to those obtained using a population-weighted least-squares regression (ongoing work confirms this).

The broad conclusion of Mackie et al. (2003) that the data provide no evidence of a threshold is based on analysis of only three of the five cohorts with available dose-response data. Further, the data used in their analysis do not reflect the most current mortality information available for two of the three included cohorts [NIOSH cohort, updated by Steenland et al. (2001); Seveso cohort, updated by Bertazzi et al. (2001)]. Mackie et al.'s conclusion of no evidence of a threshold seems unreasonable on the basis of this incomplete analysis. Crump et al. (2003) noted that the dose-response data from the manufacturing cohorts do not show any positive trend until groups with estimated doses well above current background exposures are included. Data from the Seveso cohort are consistent with this observation.

Finally, data from the occupational cohorts indicate an underlying elevation in cancer mortality independent of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) exposure [standard mortality ratio between 115 and 120 at zero dioxin exposure (Crump et al. 2003; Starr 2001)], consistent with possible confounding confounding

when the effects of two, or more, processes on results cannot be separated, the results are said to be confounded, a cause of bias in disease studies.


confounding factor
 by exposure to other chemicals in the workplace, elevated smoking rates, or other factors. In contrast, the data from the Seveso and Ranch Hand populations, with more appropriate control populations, do not show this underlying elevation at zero exposure. Combining these two groups of populations into a single meta-regression may result in spurious effects on the apparent shape of the dose-response curve dose-response curve A graphic representation of the effects that varous doses of an agent–eg, ionizing radiation or a chemotherapeutic agent, have on a given parameter–eg, cell viability, mutation frequency, DNA damage, tumor growth or metastasis or  unless this elevation is accounted for.

In this respect, we agree with Mackie et al. (2003) that the epidemiologic data must be analyzed carefully using appropriate statistical and commonsense approaches, and with an awareness of the strengths and weaknesses of the underlying data. However, we think additional work remains to be done to fully appreciate the implications of the available epidemiologic data for the cancer dose-response of TCDD in humans.

REFERENCES

Bertazzi PA, Consonni D, Bachetti S, Rubagotti M, Baccarelli A, Zocchetti C, et al. 2001. Health effects of dioxin exposure: a 20-year mortality study. Am J Epidemiol 153(11):1031-1044.

Crump KS, Canady R, Kogevinas M. 2003. Meta-analysis of dioxin cancer dose response for three occupational cohorts. Environ Health Perspect 111:681-687. doi:10.1289/ ehp.5831 [Online 30 October 2002].

Kirman CR, Aylward LL, Karch NJ, Paustenbach DJ, Finley BL, Hays SM. 2000. Is dioxin a threshold carcinogen carcinogen: see cancer.
carcinogen

Agent that can cause cancer. Exposure to one or more carcinogens, including certain chemicals, radiation, and certain viruses, can initiate cancer under conditions not completely understood.
? A quantitative analysis Quantitative Analysis

A security analysis that uses financial information derived from company annual reports and income statements to evaluate an investment decision.

Notes:
 of the epidemiological data using internal dose and Monte Carlo methods Monte Carlo method

Statistical method of approximating the solution of complex physical or mathematical systems. The method was adopted and improved by John von Neumann and Stanislaw Ulam for simulations of the atomic bomb during the Manhattan Project.
. Organohalogen Compounds 48:219-222.

Mackie D, Liu J, Loh YS, Thomas V. 2003. No evidence of dioxin cancer threshold. Environ Health Perspect 111:1145-1147. doi:10.1289/ehp.5730 [Online 25 November 2002].

Starr TB. 2001. Significant shortcomings A shortcoming is a character flaw.

Shortcomings may also be:
  • Shortcomings (SATC episode), an episode of the television series Sex and the City
 of the U.S. Environmental Protection Agency's latest draft risk characterization for dioxin-like compounds. Toxicol Sci 64(1):7-13.

Steenland K, Deddens J, Piacitelli L. 2001. Risk assessment for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) based on an epidemiologic study epidemiologic study A study that compares 2 groups of people who are alike except for one factor, such as exposure to a chemical or the presence of a health effect; the investigators try to determine if any factor is associated with the health effect . Am J Epidemiol 154(5):451-458.

Editor's note: In accordance with journal policy, Mackie et al. were asked whether they wanted to respond to this letter. They chose not to do so.

The authors declare they have no conflict of interest.

Lesa Aylward

Exponent

Alexandria, Virginia

Chris Rirman

The Sapphire Group

Cleveland, Ohio

Daniel Cher

Exponent

Menlo Park, California Menlo Park is a city in San Mateo County, California in the United States of America. It is located at latitude 37°29' North, longitude 122°9' East. Menlo Park had 30,785 inhabitants as of the 2000 U.S. Census.  

Sean Hays

Exponent

Boulder, Colorado

E-mail: shays Shays   , Daniel 1747?-1825.

American Revolutionary soldier and insurrectionist who with a band of armed men raided a government arsenal in Springfield, Massachusetts, to protest the state legislature's indifference to the economic plight of farmers
@exponent.com
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Title Annotation:Correspondence
Author:Hays, Sean
Publication:Environmental Health Perspectives
Date:Aug 1, 2003
Words:853
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