International Agency for Research on Cancer (IARC). Estimated age-standardized incidence and mortality rates (World) in 2020, World, females, ages 20-84 (excl. NMSC). 2020. https://gco.iarc.fr/today/online-analysis-multi-bars?v=2020&mode=cancer&mode_population=countries&population=900&populations=900&key=asr&sex=2&cancer=39&type=0&statistic=5&prevalence=0&population_group=0&ages_group%5B%5D=4&ages_group%5B%5D=16&nb_items=10&group_cancer=0&include_nmsc=0&include_nmsc_other=1&type_multiple=%257B%2522inc%2522%253Atrue%252C%2522mort%2522%253Atrue%252C%2522prev%2522%253Afalse%257D&orientation=horizontal&type_sort=0&type_nb_items=%257B%2522top%2522%253Atrue%252C%2522bottom%2522%253Afalse%257D. Accessed February 1, 2023.

Breast Cancer Screening. IARC handbook of cancer prevention. Vol. 15. Lyon, France: International Agency for Research on Cancer; 2016.

Dibden A, Offman J, Duffy SW, Gabe R. Worldwide review and meta-analysis of cohort studies measuring the effect of mammography screening programmes on incidence-based breast cancer mortality. Cancers. 2020;12:976.

Article  PubMed  PubMed Central  Google Scholar 

Badve SS, Beitsch PD, Bose S, Byrd D, Chen VW, Connolly JL, et al. Part XI, breast. In: Amin MB, et al., editors. AJCC Cancer Staging Manual, 8th edn. New York, USA: Springer International Publishing; 2017. p 587–636.

Tabar L, Duffy SW, Vitak B, Chen H-H, Prevost TC. The natural history of breast carcinoma. Cancer. 1999;86:449–62.

Article  CAS  PubMed  Google Scholar 

Johansson ALV, Trewin CB, Fredriksson I, Reinertsen KV, Russnes H, Ursin G. In modern times, how important are breast cancer stage, grade and receptor subtype for survival: a population-based cohort study. Breast Cancer Res. 2021;23:17.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Broeders M, Moss S, Nystrom L, Njor S, Jonsson H, Paap E, et al. The impact of mammographic screening on breast cancer mortality in Europe: a review of observational studies. J Med Screen. 2012;19:14–25.

Article  PubMed  Google Scholar 

Duffy SW, Tabar L, Yen AM, Dean PB, Smith RA, Jonsson H, et al. Beneficial effect of consecutive screening mammography examinations on mortality from breast cancer: a prospective study. Radiology. 2021;299:541–7.

Article  PubMed  Google Scholar 

Shen Y, Yang Y, Inoue LY, Munsell MF, Miller AB, Berry DA. Role of detection method in predicting breast cancer survival: analysis of randomized screening trials. J Natl Cancer Inst. 2005;97:1195–203.

Article  PubMed  Google Scholar 

Fortin J, Leblanc M, Elgbeili G, Cordova MJ, Marin MF, Brunet A. The mental health impacts of receiving a breast cancer diagnosis: a meta-analysis. Br J Cancer. 2021;125:1582–92.

Article  PubMed  PubMed Central  Google Scholar 

Cancer Registry of Norway. Kvalitetsmanualen i Mammografiprogrammet [Quality manual for BreastScreen Norway]. Oslo, Norway: Cancer Registry of Norway; 2003.

European Commission Initiative on Breast Cancer. European guidelines on breast cancer screening and diagnosis. 2022. https://healthcare-quality.jrc.ec.europa.eu/ecibc/european-breast-cancer-guidelines. Accessed November 8, 2022.

Lauby-Secretan B, Scoccianti C, Loomis D, Benbrahim-Tallaa L, Bouvard V, Bianchini F, et al. Breast-cancer screening–viewpoint of the IARC Working Group. N. Engl J Med. 2015;372:2353–8.

Article  CAS  PubMed  Google Scholar 

Hofvind S, Tsuruda K, Mangerud G, Ertzaas AK, Holen Å, Pedersen K, et al. The Norwegian Breast Cancer Screening Program, 1996-2016: celebrating 20 years of organised screening in Norway. Oslo, Norway: Cancer Registry of Norway; 2017.

Skaane P, Skjennald A. Screen-film mammography versus full-field digital mammography with soft-copy reading: randomized trial in a population-based screening program—the Oslo II Study. Radiology. 2004;232:197–204.

Article  PubMed  Google Scholar 

Larsen IK, Smastuen M, Johannesen TB, Langmark F, Parkin DM, Bray F, et al. Data quality at the Cancer Registry of Norway: an overview of comparability, completeness, validity and timeliness. Eur J Cancer. 2009;45:1218–31.

Article  PubMed  Google Scholar 

Lydersen S, Fagerland MW, Laake P. Categorical data and contingency tables. In: Veierød MB, Lydersen S, Laake P, editors. Medical statistics in clinical and epidemiological research, 1st edn. Oslo, Norway: Gylendal Norsk Forlag; 2012. p 48–89.

LeBlanc M, Crowley J. Relative risk trees for censored survival data. Biometrics. 1992;48:411–25.

Article  CAS  PubMed  Google Scholar 

Therneau T, Atkinson E. An introduction to recursive partitioning using the RPART Routines. 2022. https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf.

Zhang H, Singer BH. Recursive partitioning and applications. 2nd edn. New York NY, USA: Springer; 2010.

R Core Team. R: a language and environment for statistical computing v. 4.1.3. Vienna, Austria: R Foundation for Statistical Computing; 2022.

Therneau T, Atkinson B. rpart: Recursive partitioning and regression trees. R package version 4.1.19 (2022). https://cran.r-project.org/package=rpart.

Milborrow S. rpart.plot: Plot ‘rpart’ models: an enhanced version of ‘plot.rpart’. R package version 3.1.1 (2022). https://cran.r-project.org/package=rpart.plot.

Coviello V, Boggess M. Cumulative incidence estimation in the presence of competing risks. Stata J. 2004;4:103–12.

Article  Google Scholar 

Haybittle JL, Blamey RW, Elston CW, Johnson J, Doyle PJ, Campbell FC, et al. A prognostic index in primary breast cancer. Br J Cancer. 1982;45:361–6.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hastie T, Tibshirani R, Friedman J. Chapter 9: additive models, trees, and related methods. In: Hastie T, Tibshirani R, Friedman J. The elements of statistical learning, 2nd edn. New York, NY, USA: Springer; 2009. p 295–336.

Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol. 2013;24:2206–23.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Debien V, De Caluwe A, Wang X, Piccart-Gebhart M, Tuohy VK, Romano E, et al. Immunotherapy in breast cancer: an overview of current strategies and perspectives. NPJ Breast Cancer. 2023;9:7.

Article  PubMed  PubMed Central  Google Scholar 

Larønningen S, Ferlay J, Beydogan H, Bray F, Engholm G, Ervik M, et al. NORDCAN: period, age-specific rate per 100 000, mortality, females, age [40-74] (Norway, Breast). Association of the Nordic Cancer Registries, Cancer Registry of Norway. 2023. https://nordcan.iarc.fr/en/dataviz/cohorts?cancers=180&sexes=2&populations=578&age_start=8&years_available=1943_2020&types=1&cohort=period (Data version 9.2 - June 23, 2022). Accessed August 26, 2023.

Andersen PK, Geskus RB, de Witte T, Putter H. Competing risks in epidemiology: possibilities and pitfalls. Int J Epidemiol. 2012;41:861–70.

Article  PubMed  PubMed Central  Google Scholar 

Satagopan JM, Ben-Porat L, Berwick M, Robson M, Kutler D, Auerbach AD. A note on competing risks in survival data analysis. Br J Cancer. 2004;91:1229–35.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Austin PC, Lee DS, Fine JP. Introduction to the analysis of survival data in the presence of competing risks. Circulation. 2016;133:601–9.

Article  PubMed  PubMed Central  Google Scholar 

Gooley TA, Leisenring W, Crowley J, Storer BE. Estimation of failure probabilities in the presence of competing risks: new representations of old estimators. Stat Med. 1999;18:695–706.

Article  CAS  PubMed  Google Scholar