Mammographic sensitivity as a function of tumor size: A novel estimation based on population-based screening data. (February 2021)

• Record Type: Journal Article
• Authors: Wang, Jing; Gottschal, Pam; Ding, Lilu; Veldhuizen, DaniëlleW.A van; Lu, Wenli; Houssami, Nehmat; Greuter, Marcel J.W.; de Bock, Geertruida H.
• Is Part Of: Breast. Volume 55(2021)
• Page Start: 69
• Page End: 74
• Publication Date: 2021-02
• Subjects: Breast Neoplasms -- Mass screening -- Mammography -- Sensitivity -- Tumor growth; FN false negative -- TP true positive -- TVDT tumor volume doubling time; Breast -- Diseases -- Periodicals; Breast -- Tumors -- Periodicals; Breast -- Periodicals; Electronic journals; Periodicals; 616
• DOI: 10.1016/j.breast.2020.12.003
• Languages: English
• ISSNs: 0960-9776

Abstract

Abstract: Background: Instead of a single value for mammographic sensitivity, a sensitivity function based on tumor size more realistically reflects mammography's detection capability. Because previous models may have overestimated size-specific sensitivity, we aimed to provide a novel approach to improve sensitivity estimation as a function of tumor size. Methods: Using aggregated data on interval and screen-detected cancers, observed tumor sizes were back-calculated to the time of screening using an exponential tumor growth model and a follow-up time of 4 years. From the observed number of detected cancers and an estimation of the number of false-negative cancers, a model for the sensitivity as a function of tumor size was determined. A univariate sensitivity analysis was conducted by varying follow-up time and tumor volume doubling time (TVDT). A systematic review was conducted for external validation of the sensitivity model. Results: Aggregated data of 22, 915 screen-detected and 10, 670 interval breast cancers from the Dutch screening program were used. The model showed that sensitivity increased from 0 to 85% for tumor sizes from 2 to 20 mm. When TVDT was set at the upper and lower limits of the confidence interval, sensitivity for a 20-mm tumor was 74% and 93%, respectively. The estimated sensitivity gave comparable estimates to those from two of three studies identified by our systematic review. Conclusion: Derived from aggregated breast screening outcomes data, our model's estimation of sensitivity as a function of tumor size may provide a better representation of data observed in screening programs than other models. Highlights: Mammographic sensitivity is a key indicator of screening effectiveness. Previous model using logistic function might overestimate size-specific sensitivity. Our model showed that sensitivity increased from 0 to 85% for tumor sizes from 2 to 20 mm. Our model may provide a better representation of data observed in screening programs.