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

Autor: Danielle W. A van Veldhuizen, Marcel J. W. Greuter, Pam Gottschal, Nehmat Houssami, Wenli Lu, Jing Wang, Geertruida H. de Bock, Lilu Ding
Přispěvatelé: ​Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE)
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: The Breast, 55, 69-74. Churchill Livingstone
The Breast
The Breast : Official Journal of the European Society of Mastology
Breast, Vol 55, Iss, Pp 69-74 (2021)
ISSN: 0960-9776
Popis: 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.
Databáze: OpenAIRE
Externí odkaz: