Forecasting Model of Risk of Cancer in Lung Cancer Pedigree in a Case-control Study

Abstract

Background and objective Annual lung screening using spiral computed tomography (CT), has a high sensitivity of detecting early lung cancer (LC), but its high rates of false-positive often lead to unnecessary surgery. The aim of this study is to create a forecasting model of high risk individuals to lung cancer. Methods The pathologic diagnoses of LC in Guangdong Lung Cancer Institute were consecutively chosen as the probands. All the members of the first-degree relatives of probands' and their spouses' were enrolled in this study. These pedigrees consisted of 633 probands' pedigrees and 565 spouses' pedigrees. Unless otherwise stated, analyses were performed using the SPSS 17.0 statistical software package. Results Compared with the control, a family history of carcinoma in first-degree relatives was significantly associated with LC risk (OR=1.71, P<0.001), the sub-group of either one infected individual or more than two infected individuals in first-degree relatives showed significantly statistical differences (P=0.005, P=0.002). In the forecasting model, the risk compared to that in Chinese population was from 0.38 to 63.08 folds. In the population whose risk was more than 10 times to the Chinese population, the accuracy rate of prediction was 88.1%. Conclusion A family history of carcinoma in first-degree relatives was significantly associated with increased LC risk. The more infected individuals exist in first-degree relatives, the more risk was showed. In the forecasting model, smokers especially heavy ones whose risk were more than 10 times to the Chinese population should be receive annual screening. The population are positive at least any two conditions which including male, lung disease history, occupation expose and history of cancer in first-degree relative.

Keywords

• Genetic epidemiology
• Familial aggregation
• First-degree relative
• Lung neoplasms
• Inheritance