arising from L. Jackson et al. eClinicalMedicine https://doi.org/10.1016/j.eclinm.2023.102159 (2023)
Average cancer risks for BRCA1/BRCA2 and Lynch Syndrome pathogenic-variant carriers are above established thresholds of clinical intervention for patient benefit, even in those without a cancer family-history. A recent analysis based on UK-Biobank data suggesting that risk in carriers is primarily conferred by cancer family-history has multiple interpretation and methodological flaws.
BRCA1, BRCA2, and mismatch repair (Lynch Syndrome) cancer susceptibility genes (CSGs) fall under Tier-1 genomic applications (as defined by the Centres for Disease Control, Office of Public Health Genomics) which have significant potential for positive impact on public health based on available evidence-based guidelines and recommendations [1,2,3]. Testing for these CSGs has been evaluated to have clinical utility by NICE and other professional bodies, where subsequent interventions including for early detection (screening) and prevention or risk reduction recommended in published guidelines, could significantly reduce morbidity and mortality [3,4,5,6]. Previous consortia-based studies analysed data from diverse settings to estimate cancer risks for pathogenic variant (PV) carriers of these CSGs. These demonstrated modification of cancer risks by family history (FH), but the average risks for those without cancer FH were still above established intervention thresholds [7,8,9].
A recent report from Jackson et al. [10] estimated breast and colorectal cancer risks for PV carriers in BRCA1/BRCA2 and Lynch-Syndrome genes, using data from the UK-Biobank cohort. This cohort is relatively old at entry, with recruitment ages of 40-to-69 years, and healthy. Their main finding that the cancer risks are modified by cancer family-history (FH), is in agreement with the previous reports [8]. However, their analysis contains multiple statistical methodological issues, and their interpretation of their estimates raises several concerns. Additionally, some of the comparisons in the article and communications are incorrect [11]. Anecdotally, this has led to concern amongst stakeholders including healthcare professionals who counsel on cancer risk management and patients.
From a methodological perspective their Kaplan-Meier and Cox regression analyses considered retrospective and prospective data from UK-Biobank, treating the cohort as if they were enroled at birth. This is not true and this approach leads to high risk of bias due to beginning follow-up prior to when participants joined the cohort. For example, individuals who had cancer before entry, or were undergoing current cancer treatment, are under-represented in comparison to the general population. In fact, individuals who had cancer and died before the study’s commencement may not be included in the analysis. These factors make the study at risk of producing lower than expected estimates of risk, particularly at ages younger than 40, which cannot reliably estimated. A further limitation is the assumption of a constant relative-hazard for PV carriers across all age-groups. Given the older age of the UK-Biobank cohort (mean age = 56 years), the relative hazard estimates are likely heavily dominated by effects in older age-groups, overlooking well-established findings that BRCA1/BRCA2 BC relative-risks decrease with age [8].
UK-Biobank is a highly selected cohort with a strong healthy volunteer effect. For example, at age 70–74 y rates of all-cause mortality were 46–56% lower and total cancer incidence 12–18% lower than the general population [12]. Therefore, estimates may further be susceptible to selection biases.
When drawing wider conclusions about the results it is important to make right comparisons from an analysis. “The authors’ interpretation of the 20-year risk between 40–60 as cumulative-risks to a specific age and their comparisons to “lifetime-risks” in figure-2 and the discussion in their manuscript [10], along-with the press release, are misleading. They overlook the well-established high BC incidence in BRCA1/BRCA2-carriers under 40-years [8, 9], and use inconsistent age-intervals for their comparisons. Clearly by definition their estimates will be lower than lifetime risk. It is incorrect to compare risk-estimates for the 40–60 year interval to established intervention thresholds based on lifetime-risks and to intimate that BRCA1/BRCA2 PV-carriers do not meet NICE guideline high-risk threshold without FH.
Their conclusion that “much of the risk conferred by a rare PV associated with HBOC ……. is conferred by a FDR family-history of disease” is not supported by their results. For example, their estimated relative-hazard estimate of 7.2 among BRCA1-carriers without FH translates to an approximate 60% BC-risk by age 80 y, assuming the latest UK-population BC incidences [13]. This is well above the NICE and other well-established thresholds for clinical intervention [3] and similar to previous risk estimates by FH [8].
Their unaddressed methodological issues are compounded by the interpretation of their results based on a small number of PV carriers. Ignoring larger datasets (with many more PV carriers) that have considered the issue regarding FH and provide reliable analysis in their interpretation is imprudent [8].
References
CDC. Tier 1 Genomics applications and their importance to public Health. 2014 10/10/2023. Available from: https://www.cdc.gov/genomics/implementation/toolkit/tier1.htm.
Crosbie EJ, Ryan NAJ, Arends MJ, Bosse T, Burn J, Cornes JM, et al. The Manchester International Consensus Group recommendations for the management of gynecological cancers in Lynch syndrome. Genet Med. 2019;21:2390–400.
NICE. Familial breast cancer: classification, care and managing breast cancer and related risks in people with a family history of breast cancer. 2017 16/3/2019. [https://www.nice.org.uk/guidance/cg164]. Available from: https://www.nice.org.uk/guidance/cg164.
Hanson H, Kulkarni A, Loong L, Kavanaugh G, Torr B, Allen S, et al. UK consensus recommendations for clinical management of cancer risk for women with germline pathogenic variants in cancer predisposition genes: RAD51C, RAD51D, BRIP1 and PALB2. J Med Genet 2023;60:417–29.
Manchanda R, Gaba F, Talaulikar V, Pundir J, Gessler S, Davies M, et al. Risk-reducing salpingo-oophorectomy and the use of hormone replacement therapy below the age of natural menopause: scientific impact paper no. 66 october 2021: scientific impact paper No. 66. BJOG. 2022;129:e16–34.
NICE. Ovarian cancer: identifying and managing familial and genetic risk. Draft for consultation, September 2023 2023. Available from: https://www.nice.org.uk/guidance/indevelopment/gid-ng10225.
Dominguez-Valentin M, Sampson JR, Seppala TT, Ten Broeke SW, Plazzer JP, Nakken S, et al. Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the prospective lynch syndrome database. Genet Med. 2020;22:15–25.
Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017;317:2402–16.
Breast Cancer Association C, Dorling L, Carvalho S, Allen J, Gonzalez-Neira A, Luccarini C, et al. Breast cancer risk genes—association analysis in more than 113,000 women. N Engl J Med. 2021;384:428–39.
Jackson L, Weedon MN, Green HD, Mallabar-Rimmer B, Harrison JW, Wood AR, et al. Influence of family history on penetrance of hereditary cancers in a population setting. eClinicalMedicine. 2023;64:102159.
Knapton S. Angelina Jolie breast cancer gene screening could be ‘leading women to have needless mastectomies’. The Telegraph. 2023. https://www.telegraph.co.uk/news/2023/09/15/angelina-jolie-breast-cancer-gene-screening-mastectomies/.
Fry A, Littlejohns TJ, Sudlow C, Doherty N, Adamska L, Sprosen T, et al. Comparison of sociodemographic and health-related characteristics of UK biobank participants with those of the general population. Am J Epidemiol. 2017;186:1026–34.
CRUK. Breast cancer incidence (invasive) statistics. 2021 22.09.2023. Available from: https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer/incidence-invasive#heading-One.
Carver T, Hartley S, Lee A, Cunningham AP, Archer S, Babb de Villiers C, et al. CanRisk Tool-A web interface for the prediction of breast and ovarian cancer risk and the likelihood of carrying genetic pathogenic variants. Cancer Epidemiol Biomarkers Prev. 2021;30:469–73.
Author information
Authors and Affiliations
Contributions
All authors contributed equally to the drafting of the manuscript, critical review and approval of final version.
Corresponding author
Ethics declarations
Competing interests
RM reports receiving grants from Yorkshire Cancer Research, GSK, NHS Innovation Accelerator (NIA), and Barts Charity into genetic testing, screening and prevention research; and honoraria for advisory board membership from Astrazeneca/MSD/GSK/EGL. RM is Topic Advisor for the NICE Guideline—Ovarian cancer: identifying and managing familial and genetic risk. ACA is listed as a creator of the BOADICEA model which has been licensed by Cambridge Enterprise. DGE received consulting fees from Astrazeneca and Everything Genetics Ltd. AB declares grants from Cancer Research UK, Breast Cancer Now and royalties arising from use of the Tyrer-Cuzick (IBIS) breast cancer risk evaluation tool.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Manchanda, R., Evans, D.G., Antoniou, A.C. et al. Penetrance estimates of hereditary cancers in a population setting using UK Biobank data. BJC Rep 2, 24 (2024). https://doi.org/10.1038/s44276-023-00021-x
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1038/s44276-023-00021-x