TY - JOUR
T1 - Mammographic sensitivity as a function of tumor size
T2 - A novel estimation based on population-based screening data
AU - Wang, Jing
AU - Gottschal, Pam
AU - Ding, Lilu
AU - Veldhuizen, Daniëlle W.A.van
AU - Lu, Wenli
AU - Houssami, Nehmat
AU - Greuter, Marcel J.W.
AU - de Bock, Geertruida H.
N1 - Publisher Copyright:
© 2020 The Authors
PY - 2021/2
Y1 - 2021/2
N2 - 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.
AB - 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.
KW - Breast Neoplasms
KW - Mammography
KW - Mass screening
KW - Sensitivity
KW - Tumor growth
UR - http://www.scopus.com/inward/record.url?scp=85097882586&partnerID=8YFLogxK
U2 - 10.1016/j.breast.2020.12.003
DO - 10.1016/j.breast.2020.12.003
M3 - Article
C2 - 33348148
AN - SCOPUS:85097882586
SN - 0960-9776
VL - 55
SP - 69
EP - 74
JO - Breast
JF - Breast
ER -
