Saf Health Work.  2010 Dec;1(2):140-148.

Decision Tree of Occupational Lung Cancer Using Classification and Regression Analysis

• Kim TW
• Koh DH
• Park CY

Abstract

OBJECTIVES
Determining the work-relatedness of lung cancer developed through occupational exposures is very difficult. Aims of the present study are to develop a decision tree of occupational lung cancer.
METHODS
153 cases of lung cancer surveyed by the Occupational Safety and Health Research Institute (OSHRI) from 1992-2007 were included. The target variable was whether the case was approved as work-related lung cancer, and independent variables were age, sex, pack-years of smoking, histological type, type of industry, latency, working period and exposure material in the workplace. The Classification and Regression Test (CART) model was used in searching for predictors of occupational lung cancer.
RESULTS
In the CART model, the best predictor was exposure to known lung carcinogens. The second best predictor was 8.6 years or higher latency and the third best predictor was smoking history of less than 11.25 pack-years. The CART model must be used sparingly in deciding the work-relatedness of lung cancer because it is not absolute.
CONCLUSION
We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

Keyword

Occupational lung cancer; Decision tree; Latency; Smoking; CART

MeSH Terms

Academies and Institutes
Carcinogens
Decision Trees
Lung
Lung Neoplasms
Occupational Diseases
Occupational Exposure
Occupational Health
Regression Analysis*
Smoke
Smoking
Carcinogens
Smoke