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Univariate analyses of clinicopathological variables (ER, HER2, grade, age at diagnosis, and breast density) were undertaken, and those with <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.1 were included in a generalised linear model to estimate TVDT, cancer size at screening, and time of cancer visibility for \u201cnon-visible\u201d tumours.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>From 2011 to 2018, 476 ICs were diagnosed, almost half in the third year after screening with 86% grade 2 or 3. A visible abnormality at screening was identified in 281\/476 (59%) cases. Significant differences in TVDT were found with age (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.02), ER status (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.0001). Median TVDTs of grade 1, 2 and 3 cancers were 317, 288, and 195 days, respectively (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). For non-visible cancers, the median estimated size at screening was 1.7\u2009mm (IQR 1.0\u20132.5) for grade 1, 2.5\u2009mm (IQR 1.5\u20135.9) for grade 2, and 0.9\u2009mm (IQR 0.4\u20132.0) for grade 3 cancers, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001. The estimated time for cancer visibility was 489 days (IQR 229\u2013682) after screening and 645 days (IQR 527\u2013798) for cancers diagnosed in the third year after screening.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Using TVDT of retrospectively visible interval cancers, non-visible interval cancer sizes can be estimated at the time of screening. Increasing the frequency of screening from three-yearly to two-yearly invitations would reduce the number of interval cancers significantly.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Key Points<\/jats:title>\n            <jats:p>\n              <jats:bold>\n                <jats:italic>Question<\/jats:italic>\n              <\/jats:bold>\n              <jats:italic>Growth modelling of visible interval cancers (ICs) at screening helps to track the likely progression of non-visible ICs over the screening interval.<\/jats:italic>\n            <\/jats:p>\n            <jats:p>\n              <jats:bold>\n                <jats:italic>Findings<\/jats:italic>\n              <\/jats:bold>\n              <jats:italic>Tumour doubling time of visible ICs at screening is positively associated with age and ER status and inversely associated with cancer grade.<\/jats:italic>\n            <\/jats:p>\n            <jats:p>\n              <jats:bold>\n                <jats:italic>Clinical relevance<\/jats:italic>\n              <\/jats:bold>\n              <jats:italic>Interval cancer characterisation and growth modelling can be helpful to better predict the benefits of supplemental screening and the frequency of screening, given a minimum detectable size.<\/jats:italic>\n            <\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s00330-024-11342-x","type":"journal-article","created":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T17:35:38Z","timestamp":1737480938000},"page":"4001-4012","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Tumour growth rate and invasive interval cancer characteristics in a UK breast cancer screening population"],"prefix":"10.1007","volume":"35","author":[{"given":"Muzna","family":"Nanaa","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roido","family":"Manavaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thiemo J. 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Gilbert.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"The authors of this manuscript declare relationships with the following companies: F.J.G. receives research support from Hologic, GE Healthcare, Bayer, and Lunit. F.J.G., N.R.P., S.E.H., and M.N. have research collaborations with Vara, Screen-Point, Lunit, Google, Volpara, iCAD, Therapixel, CureMetrix, Sunnybrook Research Institute, and Massachusetts Institute of Technology.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No complex statistical methods were necessary for this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was not required for this study because it was covered by ethical approvals.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Ethical approval was obtained from the National Research Ethics Committee (NRES Committee London, UK; REC number: 20\/LO\/0104), Health Research Authority Research Confidentiality Advisory Group (ref no: 20\/CAG\/0009), and Public Health England (PHE) Research Advisory Committee (ref no: BSPRAC_090).","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Some study subjects or cohorts have been previously reported in: MacInnes et al [] and Hickman et al []. However, the focus of the work presented in the above publications and the submitted manuscript is different. MacInnes et al reported 60 out of 476 interval cancers included in this study, between 2008 and 2016, using interval cancers that were classified as either suspicious or with minimal signs of malignancy from five UK centres to estimate interval cancer growth rates, while our manuscript uses all interval cancers screened between 2011 and 2018 from one UK centre. Hickman et al reported 131 of the 476 interval cancers included in this study to investigate if deep learning algorithms can be used to triage screening mammograms from two sites. The current study incorporates interval cancers (n\u2009=\u2009666) over 7 years at one site to estimate tumour growth rate. Preliminary results from this research have also been presented in abstract form at the European Congress of Radiology (ECR) 2024, Vienna, Austria [Nanaa et al, oral session number: PRS 1202; poster number: C-23605].","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}