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. 2011 Dec;35(6):545-50.
doi: 10.1016/j.canep.2011.02.008. Epub 2011 Apr 5.

The role of mammography screening attendance and detection mode in predicting breast cancer survival-is there added prognostic value?

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The role of mammography screening attendance and detection mode in predicting breast cancer survival-is there added prognostic value?

Cornelis Biesheuvel et al. Cancer Epidemiol. 2011 Dec.

Abstract

Introduction: The aim of this study was to examine whether screening exposure status, defined as detection mode (screening, interval or symptomatic) combined with breast cancer screening attendance prior to diagnosis, had any additional value over detection mode in predicting breast cancer survival. We also assessed the effect of hormone replacement therapy (HRT) on the association of detection mode with breast cancer survival.

Methods: We analysed and compared the associations of both screening exposure status and detection mode with 5-year breast cancer survival on a cohort of 3013 breast cancer patients, aged 50-74 years in Sweden. We used Cox proportional hazards modelling with adjustments for tumour size, grade, estrogen receptor (ER) and progesterone receptor (PR) status and lymph node involvement. We repeated the analyses after stratification for HRT use.

Results: Multivariate hazard ratios (HR) for cancers detected in patients at subsequent screens, interval cancers and symptomatic cancers in patients with and without previous screening attendance were 1.3 (95%CI 0.7-2.3), 1.8 (95%CI 1.0-3.2), 1.8 (95%CI 0.9-3.6) and 2.2 (95%CI 1.2-4.1) respectively, compared with cancers detected at the first screen. The regression model including screening exposure status had no additional prognostic value over the model including detection mode (P=0.63). HRT users showed a more favourable survival than non-users; this was not influenced by detection mode.

Conclusion: The number of routine screening examinations attended in the 5-year period prior to diagnosis had no additional prognostic value over detection mode in predicting breast cancer survival.

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