UWBCS (Wisconsin) University of Wisconsin

Purpose

The University of Wisconsin Breast Cancer Simulation (UWBCS) model simulates breast cancer in a population over time, generating cancer registry-like data sets. By manipulating parametric input assumptions about natural history, screening, and treatment, the model can be used to address a number of important policy questions related to breast cancer screening and treatment.

Overview

The UWBCS is a discrete-event microsimulation model that uses a systems engineering approach to replicate US breast cancer trends. Breast cancer incidence is a function of a woman’s birth year and age (as well as risk factors in the risk-specific version, and race in the race-specific version). Model parameters governing natural history and detection are estimated via calibration. Distinguishing features of the natural history component include a continuous-time tumor growth model following a Gompertz-type growth curve (rate differs between tumors), spread to lymph nodes, and heterogeneous tumor characteristics. Versions of the model have been developed to incorporate a variety of risk factors including breast density, body mass index, Down syndrome, family history, and survival of childhood cancer.

Our model is a discrete–event simulation with a fixed cycle time of 6 months beginning in calendar year 1950. Women in each birth cohort are individually simulated from calendar year 1950 (or the year in which they were age 20) until they die a simulated death. Breast cancer inception is a function of a woman's race, birth year, and age, and accounts for secular trends in risk. Cancers are assumed to grow according to a stochastic Gompertz-type model. Tumor spread is described by a Poisson process determined by tumor size and growth rate. Tumors are assigned a Surveillance, Epidemiology, and End Results (SEER) historical stage (in situ, localized, regional, or distant) based on tumor size and lymph node involvement at the time of diagnosis in the model. A fraction of in situ and early localized invasive cancers are assumed to be of low malignant potential and not to pose a lethal threat to women.

Breast cancer can be detected either mammographically or by routine clinical/symptom detection. Mammography sensitivity and the likelihood of clinical detection are functions of age and tumor size, as well as calendar year to account for improvements in technology and increased breast cancer awareness. Sensitivity has been calibrated to match observed estimates. Mammography utilization can follow actual age-specific US screening patterns or fixed criteria by starting/ending ages, frequency, and population participation.

Upon diagnosis, all women are assumed to receive standard treatment. Adjuvant therapy follows observed US dissemination patterns. Treatment effectiveness is a function of age, stage, estrogen receptor (ER)/human epidermal growth factor receptor 2 (HER2) status, and receipt of adjuvant treatment, and is modeled independently of the cancer detection method. An effective treatment is assumed to halt breast cancer progression.

Each woman is assigned a date of death due to non-breast cancer causes based on US birth cohort-based life tables, with breast cancer removed as a cause of death. For women who have progressed to distant-stage breast cancer, a date of death from breast cancer is assigned based on observed SEER cancer survival. The timing and cause of death are determined by the earlier of the two dates of death (breast cancer or other causes).

References

1. Alagoz O, Ergun MA, Cevik M, et al. The University of Wisconsin breast cancer epidemiology simulation model: an update. Med Decis Making. 2018 Apr;38(1_suppl):99S-111S.
2. Fryback DG, Stout NK, Rosenberg MA, Trentham-Dietz A, Kuruchittham V, Remington PL. The Wisconsin Breast Cancer Epidemiology Simulation Model. J Natl Cancer Inst Monogr 2006;(36):37-47.