Mammographic sensitivity as a function of tumor size: A novel estimation based on population-based screening data |
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Affiliation: | 1. University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands;2. Department of Epidemiology and Health Statistics, School of Public Health, Tianjin Medical University, Tianjin, China;3. Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Australia;4. University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, the Netherlands;5. Robotics and Mechatronics (RaM) Group, Faculty of Electrical Engineering Mathematics and Computer Science, Technical Medical Centre, University of Twente, Enschede, the Netherlands |
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Abstract: | BackgroundInstead 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.MethodsUsing 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.ResultsAggregated 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.ConclusionDerived 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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Keywords: | Breast Neoplasms Mass screening Mammography Sensitivity Tumor growth FN" },{" #name" :" keyword" ," $" :{" id" :" kwrd0040" }," $$" :[{" #name" :" text" ," _" :" false negative TP" },{" #name" :" keyword" ," $" :{" id" :" kwrd0050" }," $$" :[{" #name" :" text" ," _" :" true positive TVDT" },{" #name" :" keyword" ," $" :{" id" :" kwrd0060" }," $$" :[{" #name" :" text" ," _" :" tumor volume doubling time |
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