The natural history of ductal carcinoma in situ: development, validation, and estimated outcomes of the SimDCIS model.

Abstract

Purpose: To develop a novel simulation model for ductal carcinoma in situ (DCIS), fully validate it, and provide new estimates for DCIS in the setting of population-based biennial screening.

Methods: A micro-simulation Markov model for DCIS (SimDCIS) was developed. Input parameters were independently derived from the literature and transition parameters were age- and grade-dependent. The model was applied to the Dutch biennial screening program. SimDCIS was internally, cross, and externally validated by comparison of the model output to data from the Netherlands Cancer Registry, a modelling study on the United Kingdom Frequency Trial, and the United Kingdom screening program, respectively. Univariate and probabilistic sensitivity analyses were performed to estimate uncertainty. DCIS regression, progression to invasive breast cancer (IBC), clinical detection, and screen-detection were estimated in Dutch screening setting.

Results: SimDCIS matched observed data in internal, external, and cross-validation. The model was most sensitive to DCIS onset probability, and the maximum variation in screen-detection rate was 11%. In Dutch screening setting, DCIS regression, progression to IBC, clinical detection, and screen-detection were estimated at 8% (0-14%), 19% (16-24%), 8% (0-13%), and 61% (56-65%), respectively. Grade distribution was 20% grade 1, 38% grade 2, and 42% grade 3.

Conclusion: SimDCIS provides strong accuracy across validation methods and is particularly sensitive to DCIS onset probability. Most DCIS will be found through screening, of which less than 50% of DCIS will be grade 3, less than 1 in 10 will regress, and 1 out of 5 DCIS will progress to IBC in biennial screening setting.