A Prediction Model of Colorectal Cancer based on the FOBT results

Back ground
Most of CRC prediction model based on f-Hb were developed in symptomatic patients rather than in asymptomatic patients in CRC screening. Statistical models for the prediction might be more precise when making allowance for time-varying property of f-Hb. By using population-based screening data, we aimed to develop a predictive model in association with time-dependent repeated f-Hb.
Material and Methods
9,731 individuals with advanced CRC found in a cohort of 920,946  individuals, aged between 50 and 69 who had been participate in FIT screening with complete f‐Hb information since 2004. Three statistical models including logistic regression model, Cox proportional hazards model, dynamic logistic regression model  were used to develop CRC prediction model. The accuracy of predicting incident CRC was assessed by using receiver operating characteristics (ROC) curve analysis.
Results
By combing baseline f-Hb with age and sex, the AUC was 0.75 (95%CI 0.71-0.76) using time-independent model. The time-dependent AUC by age, sex, and time-varying f-Hb with 2 years, 4 years, and 6 years were 0.912 (95%CI: 0.91-0.913), 0.879 (95%CI: 0.823-0.934), and 0.838 (95%CI: 0.794-0.884), respectively. The AUC of the ROC curve with multi-state Markov approach considering dynamic f-Hb changes was 0.880 (95% CI: 0.873-0.886).
Conclusions
Our results not only demonstrate a dose-response relationship between time-varying f-Hb and incident CRC but also show a dose-response relationship played in both of initiator and promoter of CRC when using the novel dynamic logistic regression model.