Mammographic sensitivity as a function of tumor size: A novel estimation based on population-based screening data

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.

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“…This implied that the results could not be generalized to the broader denser breast tissue. The pattern was similar to conventional mammograms interpreted by radiologists, where performance tended to decrease in denser breast tissue and increase in larger lesion size [38,39].…”

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“…Mammographic density in particular plays an important role in both risk and screening sensitivity and more complex modeling with respect to this covariate might be useful. Alternatives to the logistic function used for the screening sensitivity could also be explored 52 …”

“…Alternatives to the logistic function used for the screening sensitivity could also be explored. 52 In this study we have treated each risk factor as a time-constant variable. With some additional work, our model could be made to handle piece-wise constant risk factors in the onset submodel.…”

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“…Data from Vermont in the US and Norway yielded sensitivities of 88.2% and 90.7%, respectively ( 10 ). According to a study from the Netherlands, the sensitivity of mammography was 85% in individuals with 20 mm-sized breast tumors and was even lower in individuals with smaller breast tumors ( 11 ). Inadequate sensitivity can lead to a considerable number of missed diagnoses.…”