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. 2018 Apr;38(1_suppl):32S-43S.
doi: 10.1177/0272989X17743236.

Estimating Breast Cancer Survival by Molecular Subtype in the Absence of Screening and Adjuvant Treatment

Diego F Munoz  1 , Sylvia K Plevritis  1
Affiliations

Estimating Breast Cancer Survival by Molecular Subtype in the Absence of Screening and Adjuvant Treatment

Diego F Munoz et al. Med Decis Making. 2018 Apr.

Abstract

Background: As molecular subtyping of breast cancer influences clinical management, the evaluation of screening and adjuvant treatment interventions at the population level needs to account for molecular subtyping. Performing such analyses are challenging because molecular subtype-specific, long-term outcomes are not readily accessible; these markers were not historically recorded in tumor registries. We present a modeling approach to estimate historical survival outcomes by estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status.

Method: Our approach leverages a simulation model of breast cancer outcomes and integrates data from two sources: the Surveillance Epidemiology and End Results (SEER) databases and the Breast Cancer Surveillance Consortium (BCSC). We not only produce ER- and HER2-specific estimates of breast cancer survival in the absence of screening and adjuvant treatment but we also estimate mean tumor volume doubling time (TVDT) and mean mammographic detection threshold by ER/HER2-status.

Results: In general, we found that tumors with ER-negative and HER2-positive status are associated with more aggressive growth, have lower TVDTs, are harder to detect by mammography, and have worse survival outcomes in the absence of screening and adjuvant treatment. Our estimates have been used as inputs into model-based analyses that evaluate the effects of screening and adjuvant treatment interventions on population outcomes by ER and HER2 status developed by the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Working Group. In addition, our estimates enable a re-assessment of historical trends in breast cancer incidence and mortality in terms of contemporary molecular tumor characteristics.

Conclusion: Our approach can be generalized beyond breast cancer and to more complex molecular profiles.

Keywords: CISNET; breast cancer simulation model; breast cancer survival; estrogen receptor (ER) status; human epidermal growth factor 2 (HER2) status; screening mammography.

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Figures

Figure 1
Figure 1
Timeline showing when screening mammography and different types of treatment became widespread in the general population compared to data available in the Surveillance Epidemiology and End Results (SEER) registry and incidence records with screening histories provided by the Breast Cancer Surveillance Consortium (BCSC). * Estrogen-receptor (ER) status and human epidermal growth factor 2 (HER2) status were available in the Breast Cancer Surveillance Consortium (BCSC) data for women diagnosed between 1996–2010 and 1999–2010, respectively.
Figure 2
Figure 2
Estimated survival curves by estrogen-receptor (ER) status, stage (local and regional), and tumor size (<=2cm, 2–5cm, >=5cm) in the absence of screening and adjuvant treatment.
Figure 3
Figure 3
Estimated annual mortality hazards by joint estrogen-receptor and human epidermal growth factor 2 (HER2) status, stage (local and regional), and tumor size (<=2cm, 2–5cm, >=5cm) in the absence of screening and adjuvant treatment.
See this image and copyright information in PMC

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