Skip to main content
Top
Published in: Breast Cancer Research 1/2019

Open Access 01-12-2019 | Breast Cancer | Research article

Prediction and clinical utility of a contralateral breast cancer risk model

Authors: Daniele Giardiello, Ewout W. Steyerberg, Michael Hauptmann, Muriel A. Adank, Delal Akdeniz, Carl Blomqvist, Stig E. Bojesen, Manjeet K. Bolla, Mariël Brinkhuis, Jenny Chang-Claude, Kamila Czene, Peter Devilee, Alison M. Dunning, Douglas F. Easton, Diana M. Eccles, Peter A. Fasching, Jonine Figueroa, Henrik Flyger, Montserrat García-Closas, Lothar Haeberle, Christopher A. Haiman, Per Hall, Ute Hamann, John L. Hopper, Agnes Jager, Anna Jakubowska, Audrey Jung, Renske Keeman, Iris Kramer, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Jan Lubiński, Mehdi Manoochehri, Luigi Mariani, Heli Nevanlinna, Hester S. A. Oldenburg, Saskia Pelders, Paul D. P. Pharoah, Mitul Shah, Sabine Siesling, Vincent T. H. B. M. Smit, Melissa C. Southey, William J. Tapper, Rob A. E. M. Tollenaar, Alexandra J. van den Broek, Carolien H. M. van Deurzen, Flora E. van Leeuwen, Chantal van Ongeval, Laura J. Van’t Veer, Qin Wang, Camilla Wendt, Pieter J. Westenend, Maartje J. Hooning, Marjanka K. Schmidt

Published in: Breast Cancer Research | Issue 1/2019

Login to get access

Abstract

Background

Breast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making.

Methods

We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8 years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10 years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility.

Results

In the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5 years, 0.52–0.74; at 10 years, 0.53–0.72). Calibration-in-the-large was -0.13 (95% PI: -1.62–1.37), and the calibration slope was 0.90 (95% PI: 0.73–1.08). The AUC of Predict-1B at 10 years was 0.59 (95% PI: 0.52–0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4–10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.

Conclusions

We developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.
Appendix
Available only for authorised users
Literature
1.
go back to reference Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.PubMedCrossRef Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.PubMedCrossRef
3.
go back to reference Schaapveld M, Visser O, Louwman WJ, Willemse PH, de Vries EG, van der Graaf WT, Otter R, Coebergh JW, van Leeuwen FE. The impact of adjuvant therapy on contralateral breast cancer risk and the prognostic significance of contralateral breast cancer: a population based study in the Netherlands. Breast Cancer Res Treat. 2008;110(1):189–97.PubMedCrossRef Schaapveld M, Visser O, Louwman WJ, Willemse PH, de Vries EG, van der Graaf WT, Otter R, Coebergh JW, van Leeuwen FE. The impact of adjuvant therapy on contralateral breast cancer risk and the prognostic significance of contralateral breast cancer: a population based study in the Netherlands. Breast Cancer Res Treat. 2008;110(1):189–97.PubMedCrossRef
4.
go back to reference Brenner DJ. Contralateral second breast cancers: prediction and prevention. J Natl Cancer Inst. 2010;102(7):444–5.PubMedCrossRef Brenner DJ. Contralateral second breast cancers: prediction and prevention. J Natl Cancer Inst. 2010;102(7):444–5.PubMedCrossRef
5.
go back to reference van den Broek AJ, van ‘t Veer LJ, Hooning MJ, Cornelissen S, Broeks A, Rutgers EJ, Smit VT, Cornelisse CJ, van Beek M, Janssen-Heijnen ML, et al. Impact of age at primary breast cancer on contralateral breast cancer risk in BRCA1/2 mutation carriers. J Clin Oncol. 2016;34(5):409–18.PubMedCrossRef van den Broek AJ, van ‘t Veer LJ, Hooning MJ, Cornelissen S, Broeks A, Rutgers EJ, Smit VT, Cornelisse CJ, van Beek M, Janssen-Heijnen ML, et al. Impact of age at primary breast cancer on contralateral breast cancer risk in BRCA1/2 mutation carriers. J Clin Oncol. 2016;34(5):409–18.PubMedCrossRef
6.
go back to reference Malone KE, Begg CB, Haile RW, Borg A, Concannon P, Tellhed L, Xue S, Teraoka S, Bernstein L, Capanu M, et al. Population-based study of the risk of second primary contralateral breast cancer associated with carrying a mutation in BRCA1 or BRCA2. J Clin Oncol. 2010;28(14):2404–10.PubMedPubMedCentralCrossRef Malone KE, Begg CB, Haile RW, Borg A, Concannon P, Tellhed L, Xue S, Teraoka S, Bernstein L, Capanu M, et al. Population-based study of the risk of second primary contralateral breast cancer associated with carrying a mutation in BRCA1 or BRCA2. J Clin Oncol. 2010;28(14):2404–10.PubMedPubMedCentralCrossRef
7.
go back to reference Evans DG, Ingham SL, Baildam A, Ross GL, Lalloo F, Buchan I, Howell A. Contralateral mastectomy improves survival in women with BRCA1/2-associated breast cancer. Breast Cancer Res Treat. 2013;140(1):135–42.PubMedCrossRef Evans DG, Ingham SL, Baildam A, Ross GL, Lalloo F, Buchan I, Howell A. Contralateral mastectomy improves survival in women with BRCA1/2-associated breast cancer. Breast Cancer Res Treat. 2013;140(1):135–42.PubMedCrossRef
8.
go back to reference Graeser MK, Engel C, Rhiem K, Gadzicki D, Bick U, Kast K, Froster UG, Schlehe B, Bechtold A, Arnold N, et al. Contralateral breast cancer risk in BRCA1 and BRCA2 mutation carriers. J Clin Oncol. 2009;27(35):5887–92.PubMedCrossRef Graeser MK, Engel C, Rhiem K, Gadzicki D, Bick U, Kast K, Froster UG, Schlehe B, Bechtold A, Arnold N, et al. Contralateral breast cancer risk in BRCA1 and BRCA2 mutation carriers. J Clin Oncol. 2009;27(35):5887–92.PubMedCrossRef
9.
go back to reference Weischer M, Nordestgaard BG, Pharoah P, Bolla MK, Nevanlinna H, Van't Veer LJ, Garcia-Closas M, Hopper JL, Hall P, Andrulis IL, et al. CHEK2*1100delC heterozygosity in women with breast cancer associated with early death, breast cancer-specific death, and increased risk of a second breast cancer. J Clin Oncol. 2012;30(35):4308–16.PubMedPubMedCentralCrossRef Weischer M, Nordestgaard BG, Pharoah P, Bolla MK, Nevanlinna H, Van't Veer LJ, Garcia-Closas M, Hopper JL, Hall P, Andrulis IL, et al. CHEK2*1100delC heterozygosity in women with breast cancer associated with early death, breast cancer-specific death, and increased risk of a second breast cancer. J Clin Oncol. 2012;30(35):4308–16.PubMedPubMedCentralCrossRef
10.
go back to reference Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, Jervis S, van Leeuwen FE, Milne RL, Andrieu N, et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017;317(23):2402–16.CrossRefPubMed Kuchenbaecker KB, Hopper JL, Barnes DR, Phillips KA, Mooij TM, Roos-Blom MJ, Jervis S, van Leeuwen FE, Milne RL, Andrieu N, et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017;317(23):2402–16.CrossRefPubMed
11.
go back to reference Domchek SM. Risk-reducing mastectomy in BRCA1 and BRCA2 mutation carriers: a complex discussion. JAMA. 2019;321(1):27.PubMedCrossRef Domchek SM. Risk-reducing mastectomy in BRCA1 and BRCA2 mutation carriers: a complex discussion. JAMA. 2019;321(1):27.PubMedCrossRef
12.
go back to reference Chen Y, Thompson W, Semenciw R, Mao Y. Epidemiology of contralateral breast cancer. Cancer Epidemiol Biomark Prev. 1999;8(10):855–61. Chen Y, Thompson W, Semenciw R, Mao Y. Epidemiology of contralateral breast cancer. Cancer Epidemiol Biomark Prev. 1999;8(10):855–61.
13.
go back to reference Kramer I, Schaapveld M, Oldenburg HSA, Sonke GS, McCool D, van Leeuwen FE, Van de Vijver KK, Russell NS, Linn SC, Siesling S, et al. The influence of adjuvant systemic regimens on contralateral breast cancer risk and receptor subtype. J Natl Cancer Inst. 2019;111(7):709–18. Kramer I, Schaapveld M, Oldenburg HSA, Sonke GS, McCool D, van Leeuwen FE, Van de Vijver KK, Russell NS, Linn SC, Siesling S, et al. The influence of adjuvant systemic regimens on contralateral breast cancer risk and receptor subtype. J Natl Cancer Inst. 2019;111(7):709–18.
14.
go back to reference Portschy PR, Abbott AM, Burke EE, Nzara R, Marmor S, Kuntz KM, Tuttle TM. Perceptions of contralateral breast cancer risk: a prospective, longitudinal study. Ann Surg Oncol. 2015;22(12):3846–52.PubMedCrossRef Portschy PR, Abbott AM, Burke EE, Nzara R, Marmor S, Kuntz KM, Tuttle TM. Perceptions of contralateral breast cancer risk: a prospective, longitudinal study. Ann Surg Oncol. 2015;22(12):3846–52.PubMedCrossRef
15.
go back to reference Murphy JA, Milner TD, O'Donoghue JM. Contralateral risk-reducing mastectomy in sporadic breast cancer. Lancet Oncol. 2013;14(7):e262–9.PubMedCrossRef Murphy JA, Milner TD, O'Donoghue JM. Contralateral risk-reducing mastectomy in sporadic breast cancer. Lancet Oncol. 2013;14(7):e262–9.PubMedCrossRef
16.
go back to reference Chowdhury M, Euhus D, Onega T, Biswas S, Choudhary PK. A model for individualized risk prediction of contralateral breast cancer. Breast Cancer Res Treat. 2017;161(1):153–60.PubMedCrossRef Chowdhury M, Euhus D, Onega T, Biswas S, Choudhary PK. A model for individualized risk prediction of contralateral breast cancer. Breast Cancer Res Treat. 2017;161(1):153–60.PubMedCrossRef
18.
go back to reference Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ. 2016;352:i6.PubMedPubMedCentralCrossRef Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ. 2016;352:i6.PubMedPubMedCentralCrossRef
19.
go back to reference Michailidou K, Lindstrom S, Dennis J, Beesley J, Hui S, Kar S, Lemacon A, Soucy P, Glubb D, Rostamianfar A, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551(7678):92–4.PubMedPubMedCentralCrossRef Michailidou K, Lindstrom S, Dennis J, Beesley J, Hui S, Kar S, Lemacon A, Soucy P, Glubb D, Rostamianfar A, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551(7678):92–4.PubMedPubMedCentralCrossRef
20.
go back to reference Schmidt MK, Tollenaar RA, de Kemp SR, Broeks A, Cornelisse CJ, Smit VT, Peterse JL, van Leeuwen FE, Van't Veer LJ. Breast cancer survival and tumor characteristics in premenopausal women carrying the CHEK2*1100delC germline mutation. J Clin Oncol. 2007;25(1):64–9.PubMedCrossRef Schmidt MK, Tollenaar RA, de Kemp SR, Broeks A, Cornelisse CJ, Smit VT, Peterse JL, van Leeuwen FE, Van't Veer LJ. Breast cancer survival and tumor characteristics in premenopausal women carrying the CHEK2*1100delC germline mutation. J Clin Oncol. 2007;25(1):64–9.PubMedCrossRef
22.
go back to reference Font-Gonzalez A, Liu L, Voogd AC, Schmidt MK, Roukema JA, Coebergh JW, de Vries E, Soerjomataram I. Inferior survival for young patients with contralateral compared to unilateral breast cancer: a nationwide population-based study in the Netherlands. Breast Cancer Res Treat. 2013;139(3):811–9.PubMedCrossRef Font-Gonzalez A, Liu L, Voogd AC, Schmidt MK, Roukema JA, Coebergh JW, de Vries E, Soerjomataram I. Inferior survival for young patients with contralateral compared to unilateral breast cancer: a nationwide population-based study in the Netherlands. Breast Cancer Res Treat. 2013;139(3):811–9.PubMedCrossRef
24.
go back to reference Foundation Federation of Dutch Medical Scientific Societies: Human tissue and medical research: code of conduct for responsible use. 2011. Foundation Federation of Dutch Medical Scientific Societies: Human tissue and medical research: code of conduct for responsible use. 2011.
25.
go back to reference Vichapat V, Garmo H, Holmqvist M, Liljegren G, Warnberg F, Lambe M, Fornander T, Adolfsson J, Luchtenborg M, Holmberg L. Tumor stage affects risk and prognosis of contralateral breast cancer: results from a large Swedish-population-based study. J Clin Oncol. 2012;30(28):3478–85.PubMedCrossRef Vichapat V, Garmo H, Holmqvist M, Liljegren G, Warnberg F, Lambe M, Fornander T, Adolfsson J, Luchtenborg M, Holmberg L. Tumor stage affects risk and prognosis of contralateral breast cancer: results from a large Swedish-population-based study. J Clin Oncol. 2012;30(28):3478–85.PubMedCrossRef
26.
go back to reference Vichapat V, Gillett C, Fentiman IS, Tutt A, Holmberg L, Luchtenborg M. Risk factors for metachronous contralateral breast cancer suggest two aetiological pathways. Eur J Cancer. 2011;47(13):1919–27.PubMedCrossRef Vichapat V, Gillett C, Fentiman IS, Tutt A, Holmberg L, Luchtenborg M. Risk factors for metachronous contralateral breast cancer suggest two aetiological pathways. Eur J Cancer. 2011;47(13):1919–27.PubMedCrossRef
27.
go back to reference Mariani L, Coradini D, Biganzoli E, Boracchi P, Marubini E, Pilotti S, Salvadori B, Silvestrini R, Veronesi U, Zucali R, et al. Prognostic factors for metachronous contralateral breast cancer: a comparison of the linear Cox regression model and its artificial neural network extension. Breast Cancer Res Treat. 1997;44(2):167–78.PubMedCrossRef Mariani L, Coradini D, Biganzoli E, Boracchi P, Marubini E, Pilotti S, Salvadori B, Silvestrini R, Veronesi U, Zucali R, et al. Prognostic factors for metachronous contralateral breast cancer: a comparison of the linear Cox regression model and its artificial neural network extension. Breast Cancer Res Treat. 1997;44(2):167–78.PubMedCrossRef
28.
go back to reference Reiner AS, Lynch CF, Sisti JS, John EM, Brooks JD, Bernstein L, Knight JA, Hsu L, Concannon P, Mellemkjaer L, et al. Hormone receptor status of a first primary breast cancer predicts contralateral breast cancer risk in the WECARE study population. Breast Cancer Res. 2017;19(1):83.PubMedPubMedCentralCrossRef Reiner AS, Lynch CF, Sisti JS, John EM, Brooks JD, Bernstein L, Knight JA, Hsu L, Concannon P, Mellemkjaer L, et al. Hormone receptor status of a first primary breast cancer predicts contralateral breast cancer risk in the WECARE study population. Breast Cancer Res. 2017;19(1):83.PubMedPubMedCentralCrossRef
29.
go back to reference Sisti JS, Bernstein JL, Lynch CF, Reiner AS, Mellemkjaer L, Brooks JD, Knight JA, Bernstein L, Malone KE, Woods M, et al. Reproductive factors, tumor estrogen receptor status and contralateral breast cancer risk: results from the WECARE study. Springerplus. 2015;4:825.PubMedPubMedCentralCrossRef Sisti JS, Bernstein JL, Lynch CF, Reiner AS, Mellemkjaer L, Brooks JD, Knight JA, Bernstein L, Malone KE, Woods M, et al. Reproductive factors, tumor estrogen receptor status and contralateral breast cancer risk: results from the WECARE study. Springerplus. 2015;4:825.PubMedPubMedCentralCrossRef
30.
go back to reference Healey EA, Cook EF, Orav EJ, Schnitt SJ, Connolly JL, Harris JR. Contralateral breast cancer: clinical characteristics and impact on prognosis. J Clin Oncol. 1993;11(8):1545–52.PubMedCrossRef Healey EA, Cook EF, Orav EJ, Schnitt SJ, Connolly JL, Harris JR. Contralateral breast cancer: clinical characteristics and impact on prognosis. J Clin Oncol. 1993;11(8):1545–52.PubMedCrossRef
31.
go back to reference Gao X, Fisher SG, Emami B. Risk of second primary cancer in the contralateral breast in women treated for early-stage breast cancer: a population-based study. Int J Radiat Oncol Biol Phys. 2003;56(4):1038–45.PubMedCrossRef Gao X, Fisher SG, Emami B. Risk of second primary cancer in the contralateral breast in women treated for early-stage breast cancer: a population-based study. Int J Radiat Oncol Biol Phys. 2003;56(4):1038–45.PubMedCrossRef
32.
go back to reference Brooks JD, John EM, Mellemkjaer L, Lynch CF, Knight JA, Malone KE, Reiner AS, Bernstein L, Liang X, Shore RE, et al. Body mass index, weight change, and risk of second primary breast cancer in the WECARE study: influence of estrogen receptor status of the first breast cancer. Cancer Med. 2016;5(11):3282–91.PubMedPubMedCentralCrossRef Brooks JD, John EM, Mellemkjaer L, Lynch CF, Knight JA, Malone KE, Reiner AS, Bernstein L, Liang X, Shore RE, et al. Body mass index, weight change, and risk of second primary breast cancer in the WECARE study: influence of estrogen receptor status of the first breast cancer. Cancer Med. 2016;5(11):3282–91.PubMedPubMedCentralCrossRef
33.
go back to reference Knight JA, Blackmore KM, Fan J, Malone KE, John EM, Lynch CF, Vachon CM, Bernstein L, Brooks JD, Reiner AS, et al. The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study. Breast Cancer Res. 2018;20(1):23.PubMedPubMedCentralCrossRef Knight JA, Blackmore KM, Fan J, Malone KE, John EM, Lynch CF, Vachon CM, Bernstein L, Brooks JD, Reiner AS, et al. The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study. Breast Cancer Res. 2018;20(1):23.PubMedPubMedCentralCrossRef
34.
go back to reference Basu NN, Barr L, Ross GL, Evans DG. Contralateral risk-reducing mastectomy: review of risk factors and risk-reducing strategies. Int J Surg Oncol. 2015;2015:901046.PubMedPubMedCentral Basu NN, Barr L, Ross GL, Evans DG. Contralateral risk-reducing mastectomy: review of risk factors and risk-reducing strategies. Int J Surg Oncol. 2015;2015:901046.PubMedPubMedCentral
35.
go back to reference Akdeniz D, Schmidt MK, Seynaeve CM, McCool D, Giardiello D, van den Broek AJ, Hauptmann M, Steyerberg EW, Hooning MJ. Risk factors for metachronous contralateral breast cancer: a systematic review and meta-analysis. Breast. 2018;44:1–14.PubMedCrossRef Akdeniz D, Schmidt MK, Seynaeve CM, McCool D, Giardiello D, van den Broek AJ, Hauptmann M, Steyerberg EW, Hooning MJ. Risk factors for metachronous contralateral breast cancer: a systematic review and meta-analysis. Breast. 2018;44:1–14.PubMedCrossRef
36.
go back to reference Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17(6):1471–4.PubMedCrossRef Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17(6):1471–4.PubMedCrossRef
38.
go back to reference van den Broek AJ, Schmidt MK, van ‘t Veer LJ, HSA O, Rutgers EJ, Russell NS, Smit V, Voogd AC, Koppert LB, Siesling S, et al. Prognostic impact of breast-conserving therapy versus mastectomy of BRCA1/2 mutation carriers compared with noncarriers in a consecutive series of young breast cancer patients. Ann Surg. 2019;270(2):364–72.PubMedCrossRef van den Broek AJ, Schmidt MK, van ‘t Veer LJ, HSA O, Rutgers EJ, Russell NS, Smit V, Voogd AC, Koppert LB, Siesling S, et al. Prognostic impact of breast-conserving therapy versus mastectomy of BRCA1/2 mutation carriers compared with noncarriers in a consecutive series of young breast cancer patients. Ann Surg. 2019;270(2):364–72.PubMedCrossRef
39.
go back to reference Resche-Rigon M, White IR, Bartlett JW, Peters SA, Thompson SG, Group P-IS. Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data. Stat Med. 2013;32(28):4890–905.PubMedCrossRef Resche-Rigon M, White IR, Bartlett JW, Peters SA, Thompson SG, Group P-IS. Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data. Stat Med. 2013;32(28):4890–905.PubMedCrossRef
40.
go back to reference Sv B. Flexible imputation of missing data. Boca Raton: CRC Press; 2012. Sv B. Flexible imputation of missing data. Boca Raton: CRC Press; 2012.
41.
go back to reference Geskus RB. Cause-specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring. Biometrics. 2011;67(1):39–49.PubMedCrossRef Geskus RB. Cause-specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring. Biometrics. 2011;67(1):39–49.PubMedCrossRef
42.
go back to reference Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94(446):496–509.CrossRef Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94(446):496–509.CrossRef
43.
go back to reference Schoenfeld DA. Sample-size formula for the proportional-hazards regression model. Biometrics. 1983;39(2):499–503.PubMedCrossRef Schoenfeld DA. Sample-size formula for the proportional-hazards regression model. Biometrics. 1983;39(2):499–503.PubMedCrossRef
44.
go back to reference Little RJA, Rubin DB. Statistical analysis with missing data. New York: Wiley; 1987. Little RJA, Rubin DB. Statistical analysis with missing data. New York: Wiley; 1987.
45.
46.
go back to reference Steyerberg EW, Harrell FE Jr. Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 2016;69:245–7.PubMedCrossRef Steyerberg EW, Harrell FE Jr. Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 2016;69:245–7.PubMedCrossRef
47.
go back to reference Austin PC, van Klaveren D, Vergouwe Y, Nieboer D, Lee DS, Steyerberg EW. Geographic and temporal validity of prediction models: different approaches were useful to examine model performance. J Clin Epidemiol. 2016;79:76–85.PubMedPubMedCentralCrossRef Austin PC, van Klaveren D, Vergouwe Y, Nieboer D, Lee DS, Steyerberg EW. Geographic and temporal validity of prediction models: different approaches were useful to examine model performance. J Clin Epidemiol. 2016;79:76–85.PubMedPubMedCentralCrossRef
48.
go back to reference Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med. 2016;35(2):214–26.PubMedCrossRef Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med. 2016;35(2):214–26.PubMedCrossRef
49.
go back to reference Steyerberg EW. Clinical prediction models: a practical approach to development, validation and updating. New York: Springer; 2010. Steyerberg EW. Clinical prediction models: a practical approach to development, validation and updating. New York: Springer; 2010.
50.
go back to reference Blanche P, Dartigues JF, Jacqmin-Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med. 2013;32(30):5381–97.PubMedCrossRef Blanche P, Dartigues JF, Jacqmin-Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med. 2013;32(30):5381–97.PubMedCrossRef
51.
go back to reference Snell KI, Hua H, Debray TP, Ensor J, Look MP, Moons KG, Riley RD. Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model. J Clin Epidemiol. 2016;69:40–50.PubMedPubMedCentralCrossRef Snell KI, Hua H, Debray TP, Ensor J, Look MP, Moons KG, Riley RD. Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model. J Clin Epidemiol. 2016;69:40–50.PubMedPubMedCentralCrossRef
52.
go back to reference Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26(6):565–74.CrossRef Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26(6):565–74.CrossRef
53.
go back to reference Kerr KF, Brown MD, Zhu K, Janes H. Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use. J Clin Oncol. 2016;34(21):2534–40.PubMedPubMedCentralCrossRef Kerr KF, Brown MD, Zhu K, Janes H. Assessing the clinical impact of risk prediction models with decision curves: guidance for correct interpretation and appropriate use. J Clin Oncol. 2016;34(21):2534–40.PubMedPubMedCentralCrossRef
54.
go back to reference Vickers AJ, Cronin AM, Elkin EB, Gonen M. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers. BMC Med Inform Decis Mak. 2008;8:53.PubMedPubMedCentralCrossRef Vickers AJ, Cronin AM, Elkin EB, Gonen M. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers. BMC Med Inform Decis Mak. 2008;8:53.PubMedPubMedCentralCrossRef
55.
go back to reference Heemskerk-Gerritsen BA, Rookus MA, Aalfs CM, Ausems MG, Collee JM, Jansen L, Kets CM, Keymeulen KB, Koppert LB, Meijers-Heijboer HE, et al. Improved overall survival after contralateral risk-reducing mastectomy in BRCA1/2 mutation carriers with a history of unilateral breast cancer: a prospective analysis. Int J Cancer. 2015;136(3):668–77.PubMed Heemskerk-Gerritsen BA, Rookus MA, Aalfs CM, Ausems MG, Collee JM, Jansen L, Kets CM, Keymeulen KB, Koppert LB, Meijers-Heijboer HE, et al. Improved overall survival after contralateral risk-reducing mastectomy in BRCA1/2 mutation carriers with a history of unilateral breast cancer: a prospective analysis. Int J Cancer. 2015;136(3):668–77.PubMed
56.
go back to reference Rockhill B, Spiegelman D, Byrne C, Hunter DJ, Colditz GA. Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst. 2001;93(5):358–66.PubMedCrossRef Rockhill B, Spiegelman D, Byrne C, Hunter DJ, Colditz GA. Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst. 2001;93(5):358–66.PubMedCrossRef
57.
go back to reference Elmore JG, Fletcher SW. The risk of cancer risk prediction: “what is my risk of getting breast cancer”? J Natl Cancer Inst. 2006;98(23):1673–5.PubMedCrossRef Elmore JG, Fletcher SW. The risk of cancer risk prediction: “what is my risk of getting breast cancer”? J Natl Cancer Inst. 2006;98(23):1673–5.PubMedCrossRef
58.
go back to reference Wishart GC, Azzato EM, Greenberg DC, Rashbass J, Kearins O, Lawrence G, Caldas C, Pharoah PD. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer. Breast Cancer Res. 2010;12(1):R1.PubMedPubMedCentralCrossRef Wishart GC, Azzato EM, Greenberg DC, Rashbass J, Kearins O, Lawrence G, Caldas C, Pharoah PD. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer. Breast Cancer Res. 2010;12(1):R1.PubMedPubMedCentralCrossRef
59.
go back to reference Goldstein LJ, Gray R, Badve S, Childs BH, Yoshizawa C, Rowley S, Shak S, Baehner FL, Ravdin PM, Davidson NE, et al. Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features. J Clin Oncol. 2008;26(25):4063–71.PubMedPubMedCentralCrossRef Goldstein LJ, Gray R, Badve S, Childs BH, Yoshizawa C, Rowley S, Shak S, Baehner FL, Ravdin PM, Davidson NE, et al. Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features. J Clin Oncol. 2008;26(25):4063–71.PubMedPubMedCentralCrossRef
60.
go back to reference van den Broek AJ, de Ruiter K, van ‘t Veer LJ, Tollenaar RA, van Leeuwen FE, Verhoef S, Schmidt MK. Evaluation of the Dutch BRCA1/2 clinical genetic center referral criteria in an unselected early breast cancer population. Eur J Hum Genet. 2015;23(5):588–95.PubMedCrossRef van den Broek AJ, de Ruiter K, van ‘t Veer LJ, Tollenaar RA, van Leeuwen FE, Verhoef S, Schmidt MK. Evaluation of the Dutch BRCA1/2 clinical genetic center referral criteria in an unselected early breast cancer population. Eur J Hum Genet. 2015;23(5):588–95.PubMedCrossRef
61.
62.
go back to reference O'Donnell M. Estimating contralateral breast cancer risk. Current Breast Cancer Rep. 2018;10(2):91–7.CrossRef O'Donnell M. Estimating contralateral breast cancer risk. Current Breast Cancer Rep. 2018;10(2):91–7.CrossRef
63.
go back to reference van Maaren MC, de Munck L, Strobbe LJA, Sonke GS, Westenend PJ, Smidt ML, Poortmans PMP, Siesling S. Ten-year recurrence rates for breast cancer subtypes in the Netherlands: a large population-based study. Int J Cancer. 2019;144(2):263–72.PubMedCrossRef van Maaren MC, de Munck L, Strobbe LJA, Sonke GS, Westenend PJ, Smidt ML, Poortmans PMP, Siesling S. Ten-year recurrence rates for breast cancer subtypes in the Netherlands: a large population-based study. Int J Cancer. 2019;144(2):263–72.PubMedCrossRef
64.
go back to reference Lu W, Schaapveld M, Jansen L, Bagherzadegan E, Sahinovic MM, Baas PC, Hanssen LM, van der Mijle HC, Brandenburg JD, Wiggers T, et al. The value of surveillance mammography of the contralateral breast in patients with a history of breast cancer. Eur J Cancer. 2009;45(17):3000–7.PubMedCrossRef Lu W, Schaapveld M, Jansen L, Bagherzadegan E, Sahinovic MM, Baas PC, Hanssen LM, van der Mijle HC, Brandenburg JD, Wiggers T, et al. The value of surveillance mammography of the contralateral breast in patients with a history of breast cancer. Eur J Cancer. 2009;45(17):3000–7.PubMedCrossRef
66.
go back to reference Langballe R, Mellemkjaer L, Malone KE, Lynch CF, John EM, Knight JA, Bernstein L, Brooks J, Andersson M, Reiner AS, et al. Systemic therapy for breast cancer and risk of subsequent contralateral breast cancer in the WECARE study. Breast Cancer Res. 2016;18(1):65.PubMedPubMedCentralCrossRef Langballe R, Mellemkjaer L, Malone KE, Lynch CF, John EM, Knight JA, Bernstein L, Brooks J, Andersson M, Reiner AS, et al. Systemic therapy for breast cancer and risk of subsequent contralateral breast cancer in the WECARE study. Breast Cancer Res. 2016;18(1):65.PubMedPubMedCentralCrossRef
68.
go back to reference Nieboer D, Vergouwe Y, Ankerst DP, Roobol MJ, Steyerberg EW. Improving prediction models with new markers: a comparison of updating strategies. BMC Med Res Methodol. 2016;16(1):128.PubMedPubMedCentralCrossRef Nieboer D, Vergouwe Y, Ankerst DP, Roobol MJ, Steyerberg EW. Improving prediction models with new markers: a comparison of updating strategies. BMC Med Res Methodol. 2016;16(1):128.PubMedPubMedCentralCrossRef
69.
go back to reference Collins GS, Altman DG. Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ. 2012;344:e4181.PubMedPubMedCentralCrossRef Collins GS, Altman DG. Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ. 2012;344:e4181.PubMedPubMedCentralCrossRef
70.
go back to reference Madley-Dowd P, Hughes R, Tilling K, Heron J. The proportion of missing data should not be used to guide decisions on multiple imputation. J Clin Epidemiol. 2019;110:63–73.PubMedPubMedCentralCrossRef Madley-Dowd P, Hughes R, Tilling K, Heron J. The proportion of missing data should not be used to guide decisions on multiple imputation. J Clin Epidemiol. 2019;110:63–73.PubMedPubMedCentralCrossRef
71.
go back to reference Childers CP, Childers KK, Maggard-Gibbons M, Macinko J. National estimates of genetic testing in women with a history of breast or ovarian cancer. J Clin Oncol. 2017;35(34):3800–6.PubMedPubMedCentralCrossRef Childers CP, Childers KK, Maggard-Gibbons M, Macinko J. National estimates of genetic testing in women with a history of breast or ovarian cancer. J Clin Oncol. 2017;35(34):3800–6.PubMedPubMedCentralCrossRef
72.
go back to reference Bonnett LJ, Snell KIE, Collins GS, Riley RD. Guide to presenting clinical prediction models for use in clinical settings. BMJ. 2019;365:l737.PubMedCrossRef Bonnett LJ, Snell KIE, Collins GS, Riley RD. Guide to presenting clinical prediction models for use in clinical settings. BMJ. 2019;365:l737.PubMedCrossRef
75.
go back to reference Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am J Hum Genet. 2019;104(1):21–34.PubMedCrossRef Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am J Hum Genet. 2019;104(1):21–34.PubMedCrossRef
Metadata
Title
Prediction and clinical utility of a contralateral breast cancer risk model
Authors
Daniele Giardiello
Ewout W. Steyerberg
Michael Hauptmann
Muriel A. Adank
Delal Akdeniz
Carl Blomqvist
Stig E. Bojesen
Manjeet K. Bolla
Mariël Brinkhuis
Jenny Chang-Claude
Kamila Czene
Peter Devilee
Alison M. Dunning
Douglas F. Easton
Diana M. Eccles
Peter A. Fasching
Jonine Figueroa
Henrik Flyger
Montserrat García-Closas
Lothar Haeberle
Christopher A. Haiman
Per Hall
Ute Hamann
John L. Hopper
Agnes Jager
Anna Jakubowska
Audrey Jung
Renske Keeman
Iris Kramer
Diether Lambrechts
Loic Le Marchand
Annika Lindblom
Jan Lubiński
Mehdi Manoochehri
Luigi Mariani
Heli Nevanlinna
Hester S. A. Oldenburg
Saskia Pelders
Paul D. P. Pharoah
Mitul Shah
Sabine Siesling
Vincent T. H. B. M. Smit
Melissa C. Southey
William J. Tapper
Rob A. E. M. Tollenaar
Alexandra J. van den Broek
Carolien H. M. van Deurzen
Flora E. van Leeuwen
Chantal van Ongeval
Laura J. Van’t Veer
Qin Wang
Camilla Wendt
Pieter J. Westenend
Maartje J. Hooning
Marjanka K. Schmidt
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2019
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-019-1221-1

Other articles of this Issue 1/2019

Breast Cancer Research 1/2019 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine