Literature DB >> 33552842

Factors to Consider in Developing Breast Cancer Risk Models to Implement into Clinical Care.

Diana S M Buist1.   

Abstract

PURPOSE OF THE REVIEW: This article outlines considerations for individuals interested in developing and implementing breast cancer risk models and has relevance for individuals developing risk-models with the goal of implementing them into health systems. RECENT
FINDINGS: There has been increased focus on developing risk models for clinical use-often with less attention model implementation. Epidemiologists developing risk-models must think through model outcomes including stakeholder needs, time horizons, terminology and reference groups and clarity on what actionable steps are for health systems, providers and patients following its implementation.
SUMMARY: Model performance needs to be evaluated relative to complexity of the model to be implemented-not just from the risk-prediction perspective, but also from the burden on patients, providers and systems for the amount and frequency of required data collection and with clear actionable steps to be taken with the information collected.

Entities:  

Keywords:  Implementation science; breast cancer screening; risk-based screening

Year:  2020        PMID: 33552842      PMCID: PMC7863773          DOI: 10.1007/s40471-020-00230-9

Source DB:  PubMed          Journal:  Curr Epidemiol Rep


  19 in total

Review 1.  Harms of Breast Cancer Screening: Systematic Review to Update the 2009 U.S. Preventive Services Task Force Recommendation.

Authors:  Heidi D Nelson; Miranda Pappas; Amy Cantor; Jessica Griffin; Monica Daeges; Linda Humphrey
Journal:  Ann Intern Med       Date:  2016-01-12       Impact factor: 25.391

2.  The contributions of breast density and common genetic variation to breast cancer risk.

Authors:  Celine M Vachon; V Shane Pankratz; Christopher G Scott; Lothar Haeberle; Elad Ziv; Matthew R Jensen; Kathleen R Brandt; Dana H Whaley; Janet E Olson; Katharina Heusinger; Carolin C Hack; Sebastian M Jud; Matthias W Beckmann; Ruediger Schulz-Wendtland; Jeffrey A Tice; Aaron D Norman; Julie M Cunningham; Kristen S Purrington; Douglas F Easton; Thomas A Sellers; Karla Kerlikowske; Peter A Fasching; Fergus J Couch
Journal:  J Natl Cancer Inst       Date:  2015-03-04       Impact factor: 13.506

3.  The Barrier to Informed Choice in Cancer Screening: Statistical Illiteracy in Physicians and Patients.

Authors:  Odette Wegwarth; Gerd Gigerenzer
Journal:  Recent Results Cancer Res       Date:  2018

4.  Projecting individualized probabilities of developing breast cancer for white females who are being examined annually.

Authors:  M H Gail; L A Brinton; D P Byar; D K Corle; S B Green; C Schairer; J J Mulvihill
Journal:  J Natl Cancer Inst       Date:  1989-12-20       Impact factor: 13.506

5.  Breast cancer risk prediction using a clinical risk model and polygenic risk score.

Authors:  Yiwey Shieh; Donglei Hu; Lin Ma; Scott Huntsman; Charlotte C Gard; Jessica W T Leung; Jeffrey A Tice; Celine M Vachon; Steven R Cummings; Karla Kerlikowske; Elad Ziv
Journal:  Breast Cancer Res Treat       Date:  2016-08-26       Impact factor: 4.872

6.  Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer.

Authors:  Jeffrey A Tice; Diana L Miglioretti; Chin-Shang Li; Celine M Vachon; Charlotte C Gard; Karla Kerlikowske
Journal:  J Clin Oncol       Date:  2015-08-17       Impact factor: 44.544

Review 7.  Screening for breast cancer: an update for the U.S. Preventive Services Task Force.

Authors:  Heidi D Nelson; Kari Tyne; Arpana Naik; Christina Bougatsos; Benjamin K Chan; Linda Humphrey
Journal:  Ann Intern Med       Date:  2009-11-17       Impact factor: 25.391

8.  Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model.

Authors:  Jeffrey A Tice; Steven R Cummings; Rebecca Smith-Bindman; Laura Ichikawa; William E Barlow; Karla Kerlikowske
Journal:  Ann Intern Med       Date:  2008-03-04       Impact factor: 25.391

9.  Knowledge and Perception of Breast Density, Screening Mammography, and Supplemental Screening: in Search of "Informed".

Authors:  Karen E Schifferdecker; Anna N A Tosteson; Celia Kaplan; Karla Kerlikowske; Diana S M Buist; Louise M Henderson; Dianne Johnson; Jill Jaworski; Gloria Jackson-Nefertiti; Kelly Ehrlich; Mary W Marsh; Lisa Vu; Tracy Onega; Karen J Wernli
Journal:  J Gen Intern Med       Date:  2019-12-02       Impact factor: 5.128

10.  The Impact of a Risk-Based Breast Cancer Screening Decision Aid on Initiation of Mammography Among Younger Women: Report of a Randomized Trial.

Authors:  Marilyn M Schapira; Rebecca A Hubbard; Holli H Seitz; Emily F Conant; Mitchell Schnall; Joseph N Cappella; Tory Harrington; Carrie Inge; Katrina Armstrong
Journal:  MDM Policy Pract       Date:  2019-01-17
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  1 in total

1.  Effect of Psychological Intervention-Assisted Comfort Nursing Based on PERMA Model on Stress and Psychological Changes of Patients after Breast Cancer Surgery.

Authors:  Bin Chen; Ting Luo; Qiong Cai; Feng Pan; DongQin Liang; YuJie Hu
Journal:  Comput Math Methods Med       Date:  2022-06-07       Impact factor: 2.809

  1 in total

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