Literature DB >> 27548583

Tailoring Breast Cancer Screening Intervals by Breast Density and Risk for Women Aged 50 Years or Older: Collaborative Modeling of Screening Outcomes.

Amy Trentham-Dietz1, Karla Kerlikowske1, Natasha K Stout1, Diana L Miglioretti1, Clyde B Schechter1, Mehmet Ali Ergun1, Jeroen J van den Broek1, Oguzhan Alagoz1, Brian L Sprague1, Nicolien T van Ravesteyn1, Aimee M Near1, Ronald E Gangnon1, John M Hampton1, Young Chandler1, Harry J de Koning1, Jeanne S Mandelblatt1, Anna N A Tosteson1.   

Abstract

Background: Biennial screening is generally recommended for average-risk women aged 50 to 74 years, but tailored screening may provide greater benefits. Objective: To estimate outcomes for various screening intervals after age 50 years based on breast density and risk for breast cancer. Design: Collaborative simulation modeling using national incidence, breast density, and screening performance data. Setting: United States. Patients: Women aged 50 years or older with various combinations of breast density and relative risk (RR) of 1.0, 1.3, 2.0, or 4.0. Intervention: Annual, biennial, or triennial digital mammography screening from ages 50 to 74 years (vs. no screening) and ages 65 to 74 years (vs. biennial digital mammography from ages 50 to 64 years). Measurements: Lifetime breast cancer deaths, life expectancy and quality-adjusted life-years (QALYs), false-positive mammograms, benign biopsy results, overdiagnosis, cost-effectiveness, and ratio of false-positive results to breast cancer deaths averted.
Results: Screening benefits and overdiagnosis increase with breast density and RR. False-positive mammograms and benign results on biopsy decrease with increasing risk. Among women with fatty breasts or scattered fibroglandular density and an RR of 1.0 or 1.3, breast cancer deaths averted were similar for triennial versus biennial screening for both age groups (50 to 74 years, median of 3.4 to 5.1 vs. 4.1 to 6.5 deaths averted; 65 to 74 years, median of 1.5 to 2.1 vs. 1.8 to 2.6 deaths averted). Breast cancer deaths averted increased with annual versus biennial screening for women aged 50 to 74 years at all levels of breast density and an RR of 4.0, and those aged 65 to 74 years with heterogeneously or extremely dense breasts and an RR of 4.0. However, harms were almost 2-fold higher. Triennial screening for the average-risk subgroup and annual screening for the highest-risk subgroup cost less than $100 000 per QALY gained. Limitation: Models did not consider women younger than 50 years, those with an RR less than 1, or other imaging methods.
Conclusion: Average-risk women with low breast density undergoing triennial screening and higher-risk women with high breast density receiving annual screening will maintain a similar or better balance of benefits and harms than average-risk women receiving biennial screening. Primary Funding Source: National Cancer Institute.

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Year:  2016        PMID: 27548583      PMCID: PMC5125086          DOI: 10.7326/M16-0476

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  50 in total

1.  Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies.

Authors:  Jeanne S Mandelblatt; Natasha K Stout; Clyde B Schechter; Jeroen J van den Broek; Diana L Miglioretti; Martin Krapcho; Amy Trentham-Dietz; Diego Munoz; Sandra J Lee; Donald A Berry; Nicolien T van Ravesteyn; Oguzhan Alagoz; Karla Kerlikowske; Anna N A Tosteson; Aimee M Near; Amanda Hoeffken; Yaojen Chang; Eveline A Heijnsdijk; Gary Chisholm; Xuelin Huang; Hui Huang; Mehmet Ali Ergun; Ronald Gangnon; Brian L Sprague; Sylvia Plevritis; Eric Feuer; Harry J de Koning; Kathleen A Cronin
Journal:  Ann Intern Med       Date:  2016-01-12       Impact factor: 25.391

2.  Alcohol consumption and ethyl carbamate.

Authors: 
Journal:  IARC Monogr Eval Carcinog Risks Hum       Date:  2010

3.  Personalizing mammography by breast density and other risk factors for breast cancer: analysis of health benefits and cost-effectiveness.

Authors:  John T Schousboe; Karla Kerlikowske; Andrew Loh; Steven R Cummings
Journal:  Ann Intern Med       Date:  2011-07-05       Impact factor: 25.391

4.  The SPECTRUM population model of the impact of screening and treatment on U.S. breast cancer trends from 1975 to 2000: principles and practice of the model methods.

Authors:  Jeanne Mandelblatt; Clyde B Schechter; William Lawrence; Bin Yi; Jennifer Cullen
Journal:  J Natl Cancer Inst Monogr       Date:  2006

5.  Tipping the balance of benefits and harms to favor screening mammography starting at age 40 years: a comparative modeling study of risk.

Authors:  Nicolien T van Ravesteyn; Diana L Miglioretti; Natasha K Stout; Sandra J Lee; Clyde B Schechter; Diana S M Buist; Hui Huang; Eveline A M Heijnsdijk; Amy Trentham-Dietz; Oguzhan Alagoz; Aimee M Near; Karla Kerlikowske; Heidi D Nelson; Jeanne S Mandelblatt; Harry J de Koning
Journal:  Ann Intern Med       Date:  2012-05-01       Impact factor: 25.391

6.  Prevalence of mammographically dense breasts in the United States.

Authors:  Brian L Sprague; Ronald E Gangnon; Veronica Burt; Amy Trentham-Dietz; John M Hampton; Robert D Wellman; Karla Kerlikowske; Diana L Miglioretti
Journal:  J Natl Cancer Inst       Date:  2014-09-12       Impact factor: 13.506

Review 7.  Benefits and Harms of Breast Cancer Screening: A Systematic Review.

Authors:  Evan R Myers; Patricia Moorman; Jennifer M Gierisch; Laura J Havrilesky; Lars J Grimm; Sujata Ghate; Brittany Davidson; Ranee Chatterjee Mongtomery; Matthew J Crowley; Douglas C McCrory; Amy Kendrick; Gillian D Sanders
Journal:  JAMA       Date:  2015-10-20       Impact factor: 56.272

8.  Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomised trials.

Authors:  R Peto; C Davies; J Godwin; R Gray; H C Pan; M Clarke; D Cutter; S Darby; P McGale; C Taylor; Y C Wang; J Bergh; A Di Leo; K Albain; S Swain; M Piccart; K Pritchard
Journal:  Lancet       Date:  2011-12-05       Impact factor: 79.321

9.  Prediction of breast cancer risk based on profiling with common genetic variants.

Authors:  Nasim Mavaddat; Paul D P Pharoah; Kyriaki Michailidou; Jonathan Tyrer; Mark N Brook; Manjeet K Bolla; Qin Wang; Joe Dennis; Alison M Dunning; Mitul Shah; Robert Luben; Judith Brown; Stig E Bojesen; Børge G Nordestgaard; Sune F Nielsen; Henrik Flyger; Kamila Czene; Hatef Darabi; Mikael Eriksson; Julian Peto; Isabel Dos-Santos-Silva; Frank Dudbridge; Nichola Johnson; Marjanka K Schmidt; Annegien Broeks; Senno Verhoef; Emiel J Rutgers; Anthony Swerdlow; Alan Ashworth; Nick Orr; Minouk J Schoemaker; Jonine Figueroa; Stephen J Chanock; Louise Brinton; Jolanta Lissowska; Fergus J Couch; Janet E Olson; Celine Vachon; Vernon S Pankratz; Diether Lambrechts; Hans Wildiers; Chantal Van Ongeval; Erik van Limbergen; Vessela Kristensen; Grethe Grenaker Alnæs; Silje Nord; Anne-Lise Borresen-Dale; Heli Nevanlinna; Taru A Muranen; Kristiina Aittomäki; Carl Blomqvist; Jenny Chang-Claude; Anja Rudolph; Petra Seibold; Dieter Flesch-Janys; Peter A Fasching; Lothar Haeberle; Arif B Ekici; Matthias W Beckmann; Barbara Burwinkel; Frederik Marme; Andreas Schneeweiss; Christof Sohn; Amy Trentham-Dietz; Polly Newcomb; Linda Titus; Kathleen M Egan; David J Hunter; Sara Lindstrom; Rulla M Tamimi; Peter Kraft; Nazneen Rahman; Clare Turnbull; Anthony Renwick; Sheila Seal; Jingmei Li; Jianjun Liu; Keith Humphreys; Javier Benitez; M Pilar Zamora; Jose Ignacio Arias Perez; Primitiva Menéndez; Anna Jakubowska; Jan Lubinski; Katarzyna Jaworska-Bieniek; Katarzyna Durda; Natalia V Bogdanova; Natalia N Antonenkova; Thilo Dörk; Hoda Anton-Culver; Susan L Neuhausen; Argyrios Ziogas; Leslie Bernstein; Peter Devilee; Robert A E M Tollenaar; Caroline Seynaeve; Christi J van Asperen; Angela Cox; Simon S Cross; Malcolm W R Reed; Elza Khusnutdinova; Marina Bermisheva; Darya Prokofyeva; Zalina Takhirova; Alfons Meindl; Rita K Schmutzler; Christian Sutter; Rongxi Yang; Peter Schürmann; Michael Bremer; Hans Christiansen; Tjoung-Won Park-Simon; Peter Hillemanns; Pascal Guénel; Thérèse Truong; Florence Menegaux; Marie Sanchez; Paolo Radice; Paolo Peterlongo; Siranoush Manoukian; Valeria Pensotti; John L Hopper; Helen Tsimiklis; Carmel Apicella; Melissa C Southey; Hiltrud Brauch; Thomas Brüning; Yon-Dschun Ko; Alice J Sigurdson; Michele M Doody; Ute Hamann; Diana Torres; Hans-Ulrich Ulmer; Asta Försti; Elinor J Sawyer; Ian Tomlinson; Michael J Kerin; Nicola Miller; Irene L Andrulis; Julia A Knight; Gord Glendon; Anna Marie Mulligan; Georgia Chenevix-Trench; Rosemary Balleine; Graham G Giles; Roger L Milne; Catriona McLean; Annika Lindblom; Sara Margolin; Christopher A Haiman; Brian E Henderson; Fredrick Schumacher; Loic Le Marchand; Ursula Eilber; Shan Wang-Gohrke; Maartje J Hooning; Antoinette Hollestelle; Ans M W van den Ouweland; Linetta B Koppert; Jane Carpenter; Christine Clarke; Rodney Scott; Arto Mannermaa; Vesa Kataja; Veli-Matti Kosma; Jaana M Hartikainen; Hermann Brenner; Volker Arndt; Christa Stegmaier; Aida Karina Dieffenbach; Robert Winqvist; Katri Pylkäs; Arja Jukkola-Vuorinen; Mervi Grip; Kenneth Offit; Joseph Vijai; Mark Robson; Rohini Rau-Murthy; Miriam Dwek; Ruth Swann; Katherine Annie Perkins; Mark S Goldberg; France Labrèche; Martine Dumont; Diana M Eccles; William J Tapper; Sajjad Rafiq; Esther M John; Alice S Whittemore; Susan Slager; Drakoulis Yannoukakos; Amanda E Toland; Song Yao; Wei Zheng; Sandra L Halverson; Anna González-Neira; Guillermo Pita; M Rosario Alonso; Nuria Álvarez; Daniel Herrero; Daniel C Tessier; Daniel Vincent; Francois Bacot; Craig Luccarini; Caroline Baynes; Shahana Ahmed; Mel Maranian; Catherine S Healey; Jacques Simard; Per Hall; Douglas F Easton; Montserrat Garcia-Closas
Journal:  J Natl Cancer Inst       Date:  2015-04-08       Impact factor: 13.506

10.  Cost-effectiveness and harm-benefit analyses of risk-based screening strategies for breast cancer.

Authors:  Ester Vilaprinyo; Carles Forné; Misericordia Carles; Maria Sala; Roger Pla; Xavier Castells; Laia Domingo; Montserrat Rue
Journal:  PLoS One       Date:  2014-02-03       Impact factor: 3.240

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  46 in total

1.  Breast Cancer Incidence by Stage Before and After Change in Screening Guidelines.

Authors:  Fangjian Guo; Yong-Fang Kuo; Abbey B Berenson
Journal:  Am J Prev Med       Date:  2019-01       Impact factor: 5.043

2.  Comparative effectiveness of incorporating a hypothetical DCIS prognostic marker into breast cancer screening.

Authors:  Amy Trentham-Dietz; Mehmet Ali Ergun; Oguzhan Alagoz; Natasha K Stout; Ronald E Gangnon; John M Hampton; Kim Dittus; Ted A James; Pamela M Vacek; Sally D Herschorn; Elizabeth S Burnside; Anna N A Tosteson; Donald L Weaver; Brian L Sprague
Journal:  Breast Cancer Res Treat       Date:  2017-11-28       Impact factor: 4.872

3.  "You probably can't feel as safe as normal women": Hispanic women's reactions to breast density notification.

Authors:  Alsacia L Pacsi-Sepulveda; Rachel C Shelton; Carmen B Rodriguez; Arielle T Coq; Parisa Tehranifar
Journal:  Cancer       Date:  2019-02-15       Impact factor: 6.860

4.  Discussions of Dense Breasts, Breast Cancer Risk, and Screening Choices in 2019.

Authors:  Karla Kerlikowske; Diana L Miglioretti; Celine M Vachon
Journal:  JAMA       Date:  2019-07-02       Impact factor: 56.272

5.  How Do Women View Risk-Based Mammography Screening? A Qualitative Study.

Authors:  Xiaofei He; Karen E Schifferdecker; Elissa M Ozanne; Anna N A Tosteson; Steven Woloshin; Lisa M Schwartz
Journal:  J Gen Intern Med       Date:  2018-07-31       Impact factor: 5.128

6.  Age-based versus Risk-based Mammography Screening in Women 40-49 Years Old: A Cross-sectional Study.

Authors:  Elizabeth S Burnside; Amy Trentham-Dietz; Christina M Shafer; John M Hampton; Oguz Alagoz; Jennifer R Cox; Eric Mischo; Sarina B Schrager; Lee G Wilke
Journal:  Radiology       Date:  2019-06-11       Impact factor: 11.105

7.  Breast Cancer Risk Model Requirements for Counseling, Prevention, and Screening.

Authors:  Mitchell H Gail; Ruth M Pfeiffer
Journal:  J Natl Cancer Inst       Date:  2018-09-01       Impact factor: 13.506

8.  Incorporating Baseline Breast Density When Screening Women at Average Risk for Breast Cancer : A Cost-Effectiveness Analysis.

Authors:  Ya-Chen Tina Shih; Wenli Dong; Ying Xu; Ruth Etzioni; Yu Shen
Journal:  Ann Intern Med       Date:  2021-02-09       Impact factor: 25.391

9.  Simulating the Impact of Risk-Based Screening and Treatment on Breast Cancer Outcomes with MISCAN-Fadia.

Authors:  Jeroen J van den Broek; Nicolien T van Ravesteyn; Eveline A Heijnsdijk; Harry J de Koning
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

10.  Comparing CISNET Breast Cancer Models Using the Maximum Clinical Incidence Reduction Methodology.

Authors:  Jeroen J van den Broek; Nicolien T van Ravesteyn; Jeanne S Mandelblatt; Mucahit Cevik; Clyde B Schechter; Sandra J Lee; Hui Huang; Yisheng Li; Diego F Munoz; Sylvia K Plevritis; Harry J de Koning; Natasha K Stout; Marjolein van Ballegooijen
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

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