Jan Hunter, Faculty of Health Sciences, University of Hull

 

 

 

 

 

A major research study has demonstrated that breast screening in women aged 35–39  years can be effective at detecting cancers at an early stage and is therefore expected to be equally effective in reducing mortality rates (Evans et al, 2019).

Currently, as part of the UK’s NHS Breast Screening Programme, women are called for routine mammography every three years, from age 50 to 70, although in some regions – as part of a trial – the screening age range is 47–73. However, women who are at an increased risk of developing breast cancer, either due to a faulty gene and/or a familial history, can be offered screening at a younger age. The recommendations are that women with a high-to-moderate risk of breast cancer should undergo annual screening from their 40s (National Institute for Health and Care Excellence (NICE) (2017).

Although the incidence of breast cancer increases with age, a younger age at diagnosis correlates with poorer outcomes and increased mortality rates (McGuire et al, 2015). Whilst approximately only 5% of breast cancers occur in the under 40s, there is a greater risk of recurrence and death in comparison to those women diagnosed in older age (Copson et al, 2018). Women under the age of 40 years are more likely to be diagnosed with triple-negative breast cancer – the more aggressive subtype of breast cancer, with an associated lower survival rate and greater risk of recurrence (McGuire et al, 2015; Cancello et al, 2010).

There is no doubt that the introduction of cancer-specific screening programmes has been an effective way of reducing the number of deaths caused by cancer. The success of breast screening programmes has resulted in them being adopted in more than 26 countries worldwide (McGuire et al, 2015). In 2012, the Marmot Review of the UK programme, validated its achievements, concluding that deaths from breast cancer have been reduced by 20% as a result of screening.

Despite the evidence in support of screening, there are some who argue that it stretches finite resources and is not cost-effective. The majority of people who undergo screening do not have cancer and may never go on to develop it (Wardle et al, 2015). In some cases, breast screening can result in ‘false positives’, detecting an abnormality that isn’t actually there, or a tumour that may never have presented in that person’s lifetime (Pashayan et al, 2018). For every death from breast cancer that is prevented, it is estimated there will be three over-diagnosed or false-positive cases that are detected and treated (Marmot et al, 2013). Any extension of screening therefore needs to be cautious and evidence-based.

Although there will be a group of women who are over-diagnosed, Evans et al (2019) argue that this is highly unlikely to be the case in younger women. As part of their argument for extending screening to high-risk women aged 35-39, they highlight that left untreated, those with a Carcinoma In Situ (CIS) could have it transform into invasive cancer within 10 years, resulting in unnecessary deaths. Early detection through screening could allow earlier intervention, before the cancer has chance to spread to the lymph nodes and ultimately metastasize.

In order to extend screening, it is crucial that high-risk women can be identified effectively. There are several genetic tests available and algorithms to detect a woman’s risk of developing breast cancer. However, a new and comprehensive algorithm is currently running as a pilot scheme to assess its effectiveness. The CanRisk tool is an online breast cancer risk prediction tool, based on the ongoing research of Lee et al, (2016) and their breast cancer risk model – BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm). It is the first time such a tool has incorporated so many personal and genetic risk factors, including over 300 variations. It will assist healthcare practitioners in customising care and interventions based on an individual patient’s level of risk. Crucially, a more accurate indicator of overall risk will allow a more individualised approach to screening. However, this is still in its infancy and we are still some time away from genetic testing being offered to all.

There must always be a note of caution with the introduction and use of any new test. Pashayan et al (2018) have warned there is ground work to be done in terms of explaining what the findings will mean to individual – a high risk doesn’t necessarily mean a woman will develop a breast cancer, nor does being at low risk mean it will never happen. However, there is recognition that early detection is vital to improving breast cancer survival (World Health Organisation, 2019), so if a clinical tool can identify personal risk and facilitate an individualised approach to screening – even if this results in some women in their 30s being screened – then this can only be a good thing for the future of breast cancer care.

 

References

BBC News. (2019). Breast cancer risk test ‘game changer’.Available: https://www.bbc.co.uk/news/health-46875367. Last accessed 19/02/2019.

Cancello, G., et al, (2010). Prognosis and adjuvant treatment effects in selected breast cancer subtypes of very young women (< 35 years) with operable breast cancer. Annals of Oncology.  21 (10) 1974 – 1981.

Cancer Research UK (2017). Breast Cancer. [Online] https://www.cancerresearchuk.org/about-cancer/breast-cancer/screening/breast-screeningAccessed 15/02/2019.

Copson, E.R, et al (2018). Germline BRCAmutation and outcome in young-onset breast cancer (POSH): a prospective cohort study. The Lancet. 19 (2) 169 – 180. [Online] Available https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(17)30891-4/fulltextAccessed 13/02/2019.

Evans,D.G.,Thomas,S., J.Caunt,et al. (2019). Final Results of the Prospective FH02 Mammographic Surveillance Study of Women Aged 35–39 at Increased Familial Risk of Breast Cancer. EClinical Medicine.[Online] pages 1 – 8. Available https://www.thelancet.com/action/showPdf?pii=S2589-5370%2819%2930005-7

Lee, A., et al (2019). BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors. Genetics in Medicine. 0 (0), 1 – 11. [Online} Available https://www.nature.com/articles/s41436-018-0406-9.pdf

Macmillan. (2018). Risk factors for breast cancer.Available: https://www.macmillan.org.uk/information-and-support/breast-cancer/diagnosing/causes-and-risk-factors/potential-causes-of-cancer/age-lifestyle-diet-and-reducing-your-risk.html#7150.  Last accessed 19/02/2019.

McGuire, A., et al (2015). Effects of age on the detection and management of breast cancer. Cancers. 7 (2), 908 – 929.

NICE (2017). Familial breast cancer: classification, care and managing breast cancer and related risks in people with a family history of breast cancer Clinical guideline [CG164] https://www.nice.org.uk/guidance/cg164/ifp/chapter/how-breast-cancer-risk-is-described

Pashavan, N., et al, (2018). Cost-effectiveness and benefit-to-harm ratio of risk-stratified screening for breast cancer: A life-table model. JAMA Oncology.4 (11) 1504 – 1510. [Online} Available https://jamanetwork.com/journals/jamaoncology/fullarticle/2686812 Accessed 14/02/2019.

Wardle, J., et al (2015). Screening for prevention and early diagnosis of cancer. American Psychologist. 70 (2) 119 – 133. [Online] https://www.apa.org/pubs/journals/releases/amp-a0037357.pdf Accessed 14/02/2019.

World Health Organization (2019). Breast cancer: prevention and control. [Online] https://www.who.int/cancer/detection/breastcancer/en/index1.html Accessed 21/02/2019