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Screening status, tumour subtype, and breast cancer survival: a national population-based analysis

  • Epidemiology
  • Published:
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Abstract

Purpose

We examined whether demographic and tumour characteristics (including subtype) were different for women with breast cancer diagnosed via mammography screening compared with women with interval breast cancers, lapsed attenders of the screening programme and non-participants of the screening programme. In addition, we explored whether there were survival differences between the groups, taking into account lead time bias.

Methods

We used linked data from National Cancer Registry Ireland and the national breast screening programme BreastCheck. Multinomial logistic regression was used to test the association of covariates with screening status. For survival analysis, we corrected the survival time for screen-detected cases for lead time bias, examined Kaplan–Meier curves and then used Cox regression to investigate differences in survival by screening status.

Results

Subtype (HER2 over-expressing, triple negative), stage (III/IV), grade (poor), having co-morbidities, area of deprivation, smoking status and age were associated with having interval cancer or being a non-participant of the screening programme in the multivariable model. After correcting for lead time bias, and adjusting for variables associated with screening status, there was no evidence that risk of breast-cancer death for women with screen-detected cancer was different from women with interval cancer (HR = 0.76, 95% CI 0.56–1.03), non-participants (HR = 1.07, 95% CI 0.84–1.37) and lapsed attenders (HR = 0.97, 95% CI 0.65–1.45).

Conclusions

Screening status was strongly associated with subtype and this association persisted after adjustment for covariates including tumour stage and grade. After correcting for lead-time bias and adjusting for stage, subtype, grade and socio-demographic variables, no significant survival difference was demonstrated for women with screen-detected cancer in the 5-year period post-diagnosis. Since we are adjusting for stage, subtype and other variables, the lack of difference between these groups would be expected but has not been demonstrated in studies which do not correct for lead time bias.

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Acknowledgements

We thank the tumour registration officers and other staff of the National Cancer Registry for their work in collecting and quality-assuring the data used in this analysis. We would like to thank Tracy Kelleher (NCRI) for matching the data.

Funding

The authors received no specific funding for this work.

Author information

Authors and Affiliations

  1. National Cancer Registry Ireland, Cork, T12 CDF7, Ireland

    Katie M. O’Brien

  2. Department of Mathematics, Cork Institute of Technology, Cork, T12 P928, Ireland

    Katie M. O’Brien

  3. National Screening Service, King’s Inns House, 200 Parnell Street, Dublin 1, Ireland

    Therese Mooney & Patricia Fitzpatrick

  4. School of Public Health, Physiotherapy & Sports Science, University College Dublin, Dublin 4, Ireland

    Patricia Fitzpatrick

  5. Institute of Health & Society, Newcastle University, Richardson Road, Newcastle upon Tyne, NE2 4AX, UK

    Linda Sharp

Authors
  1. Katie M. O’Brien
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  2. Therese Mooney
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  4. Linda Sharp
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Corresponding author

Correspondence to Katie M. O’Brien.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

The NCRI has permission under the Health (Provision of Information) Act 1997 to collect and hold data on all persons diagnosed with cancer in Ireland without requiring individual consent. The use of that data for research is covered by the Statutory Instrument which established the Registry Board in 1991. All datasets were anonymised prior to analysis.

Informed consent

At the time of screening, consent for data being shared with the National Cancer Registry was obtained by BreastCheck.

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O’Brien, K.M., Mooney, T., Fitzpatrick, P. et al. Screening status, tumour subtype, and breast cancer survival: a national population-based analysis. Breast Cancer Res Treat 172, 133–142 (2018). https://doi.org/10.1007/s10549-018-4877-9

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  • DOI: https://doi.org/10.1007/s10549-018-4877-9

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