TY - JOUR
T1 - Imputation of individual cancer cases to occupational causes
AU - Vandentorren, Stéphanie
AU - Salmi, L. Rachid
AU - Mathoulin-Pélissier, Simone
AU - Baldi, Isabelle
AU - Brochard, Patrick
AU - Ameille, Jacques
AU - Bégaud, Bernard
AU - Bergeret, Alain
AU - Boffeta, Paolo
AU - Choudat, Dominique
AU - Conso, Françoise
AU - Dalphin, Jean Charles
AU - Devuyst, Paul
AU - Guillemin, Michel
AU - Imbernon, Ellen
AU - Lagier, Georges
AU - Lane, David
AU - Letourneux, Marc
AU - Masse, Roland
AU - Minaro, Laurent
AU - Pairon, Jean Claude
AU - Rossignol, Michel
AU - Serres, Gérald
AU - Taytard, André
PY - 2006/2
Y1 - 2006/2
N2 - Objectives: Many potential occupational causes of cancer have been documented. Imputation of an individual cancer to occupational or other causes is, however, difficult. A method based on the Bayes theorem is proposed for assessing causal relationships at the individual level. Methods: Causality assessment, dealing with four types of persons defined by exposure and the occurrence of cancer, was linked with imputation, only dealing with persons who have cancer and were exposed. Imputation was then formulated using the Bayes theorem, relating epidemiologic information regarding causes, a patient's exposure history, and the posterior odds that the cancer was caused by a suspected occupational exposure. Data needed to apply a Bayesian method were defined in terms of relative risks, proportion of people exposed in populations, and the frequency of a positive relevant characteristic for persons without cancer. A relevant characteristic was defined using a formal consensus between experts. The method was then illustrated with cases of mesothelioma and lung cancer in possible relation to asbestos. Results: Experts defined the relevant characteristics as being qualific ation of occupational exposure, intensity of exposure, latency, disease characteristics, and presence of causal agent in the body. Application to mesothelioma and lung cancer cases illustrated the potential usefulness of the method. Conclusions: The importance of occupational exposure in the formulation of imputation underscores the need for available and reliable data sources on occupational exposures. The proposed method could become a powerful tool for the expert assessment of causes of cancer cases, provided data become available in individual files and the literature.
AB - Objectives: Many potential occupational causes of cancer have been documented. Imputation of an individual cancer to occupational or other causes is, however, difficult. A method based on the Bayes theorem is proposed for assessing causal relationships at the individual level. Methods: Causality assessment, dealing with four types of persons defined by exposure and the occurrence of cancer, was linked with imputation, only dealing with persons who have cancer and were exposed. Imputation was then formulated using the Bayes theorem, relating epidemiologic information regarding causes, a patient's exposure history, and the posterior odds that the cancer was caused by a suspected occupational exposure. Data needed to apply a Bayesian method were defined in terms of relative risks, proportion of people exposed in populations, and the frequency of a positive relevant characteristic for persons without cancer. A relevant characteristic was defined using a formal consensus between experts. The method was then illustrated with cases of mesothelioma and lung cancer in possible relation to asbestos. Results: Experts defined the relevant characteristics as being qualific ation of occupational exposure, intensity of exposure, latency, disease characteristics, and presence of causal agent in the body. Application to mesothelioma and lung cancer cases illustrated the potential usefulness of the method. Conclusions: The importance of occupational exposure in the formulation of imputation underscores the need for available and reliable data sources on occupational exposures. The proposed method could become a powerful tool for the expert assessment of causes of cancer cases, provided data become available in individual files and the literature.
KW - Bayes theorem
KW - Causality
KW - Epidemiologic methods
KW - Occupational cancer
UR - https://www.scopus.com/pages/publications/33644834728
U2 - 10.5271/sjweh.974
DO - 10.5271/sjweh.974
M3 - Article
C2 - 16539170
AN - SCOPUS:33644834728
SN - 0355-3140
VL - 32
SP - 32
EP - 40
JO - Scandinavian Journal of Work, Environment and Health
JF - Scandinavian Journal of Work, Environment and Health
IS - 1
ER -