MODELLING THE OCCURRENCE OF INVASIVE BREAST CANCER IN WOMEN AGED 50-59 AND SIMULATING THE STUDY AND CONTROL GROUPS OF WOMEN IN THE CANADIAN NATIONAL BREAST SCREENING STUDY-2

Purpose: Breast cancer is one of the most frequent types of cancer in Canada. We built an accurate model of the progression of breast cancer that includes predisposition factors and examine the effectiveness of different screening strategies. This tool is essential to evaluating different approaches to reduce the incidence of breast cancer and its associated mortality. 

Method:  We start by modelling the natural progression of breast cancer using a Markov process. A patient follows from healthy state to preclinical state and finally to a clinical state, if the cancer is not detected by screening. We incorporate the effects of covariates on transition rates using proportional hazards model. Patients are women aged 50-59 from the Canadian National Breast Screening Study-2 (CNBSS). We include prevalent cancers, which are cancers detected at the initial screen of the CNBSS screening program by means of different modalities. We estimate the screening sensitivities at the initial and subsequent screens for both study and control groups of the CNBSS. We then develop a simulation model to predict the expected number of prevalent, screen-detected and clinical cancers for this age group, and validate the progression model and screening sensitivities.

Result:   We compare the effectiveness of mammography (MA) and physical breast examination (PEX) for the study group to that of solely PEX for the control group. The values of the program sensitivity at initial and subsequent screens are given in table 1. Our analysis shows that age of entry and family history are the two main risks factors for cancer progression for the age group 50-59. We estimate that only 83.5% of reported cancer cases would have developed within the follow-up period of five years of the CNBSS if those women had been screened only through PEX. We evaluate overdiagnosis due to the addition of MA screening at 21.8%.

Conclusion: The values we estimated and validated for both control and study groups for transition rate, risk factors, effect of screening modalities and programs and proportion of overdiagnosis will help policy-makers by giving them the tools to improve the QALY and cost of their screening strategies.

Table 1: Estimated values of the program sensitivity 

	Control group (PEX only)	Study group (MA & PEX)
Sensitivity at initial screen	69%	95%
Sensitivity at subsequent screens	39%	82%