association of false-positive recalls with other mammographic features (eg, microcalcifications and masses) and breast cancer risk prediction models (eg, Tyrer-Cuzick model). Furthermore, false-positive recalls should be reduced, but not at the cost of missing
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Xinhe Mao, Wei He, Keith Humphreys, Mikael Eriksson, Natalie Holowko, Fredrik Strand, Per Hall, and Kamila Czene
Arvind Bambhroliya, Mariana Chavez-MacGregor, and Abenaa M. Brewster
Service Task Force. a No particular risk prediction model is endorsed. Clinicians can use any of the following tools: NCI Breast Cancer Risk Assessment Tool ( www.cancer.gov/bcrisktool ); Breast Cancer Surveillance Consortium model ( https
Gary H. Lyman and Marek S. Poniewierski
model but assuming no G-CSF prophylaxis was administered ( Figure 3 ). The authors concluded that the individualized neutropenia risk prediction model performed well in this retrospective external cohort. In this secondary analysis, it was observed that
Martin C. Mahoney
Cancer Inst 2006 ; 98 : 1215 – 1226 . 19. Barlow WE White E Ballard-Barbash R . Prospective breast cancer risk prediction model for women undergoing screening mammography . J Natl Cancer Inst 2006 ; 98 : 1204 – 1214 . 20
Renee W. Pinsky and Mark A. Helvie
MRI sensitivity does not seem to be as affected by density as is mammography. If mammographic density is incorporated into a clinically useful risk prediction model, then more women may be considered in the high-risk group and would be eligible for
Caiqian Cropper, Ashley Woodson, Banu Arun, Carlos Barcenas, Jennifer Litton, Sarah Noblin, Diane Liu, Minjeong Park, and Molly Daniels
, this debate has included the question of how to identify patients with breast cancer who are at higher risk of having a mutation based on analysis of personal and family history of cancer. Risk prediction models such as BRCAPRO and BOADICEA 11 , 12
Douglas Arenberg and Ella A. Kazerooni
extensive-disease small cell lung cancer . J Thorac Oncol 2009 ; 4 : 741 – 745 . 9 Cassidy A Myles JP van Tongeren M . The LLP risk model: an individual risk prediction model for lung cancer . Br J Cancer 2008 ; 98 : 270 – 276 . 10
Muhamed Baljevic, Douglas W. Sborov, Ming Y. Lim, Jens Hillengass, Thomas Martin, Jorge J. Castillo, Michael B. Streiff, Shaji K. Kumar, and Natalie S. Callander
. 20 Lastly, the IMPEDE model additionally takes into consideration baseline use of ASA or anticoagulants when assessing the VTE risk. Given the advantages of the latter 2 risk prediction models, the updated NCCN Guidelines for VTE prophylaxis in NDMM
NCCN Guidelines® Insights: Lung Cancer Screening, Version 1.2022
Featured Updates to the NCCN Guidelines
Douglas E. Wood, Ella A. Kazerooni, Denise Aberle, Abigail Berman, Lisa M. Brown, Georgie A. Eapen, David S. Ettinger, J. Scott Ferguson, Lifang Hou, Dipen Kadaria, Donald Klippenstein, Rohit Kumar, Rudy P. Lackner, Lorriana E. Leard, Inga T. Lennes, Ann N.C. Leung, Peter Mazzone, Robert E. Merritt, David E. Midthun, Mark Onaitis, Sudhakar Pipavath, Christie Pratt, Varun Puri, Dan Raz, Chakravarthy Reddy, Mary E. Reid, Kim L. Sandler, Jacob Sands, Matthew B. Schabath, Jamie L. Studts, Lynn Tanoue, Betty C. Tong, William D. Travis, Benjamin Wei, Kenneth Westover, Stephen C. Yang, Beth McCullough, and Miranda Hughes
, Evaluation of USPSTF lung cancer screening guidelines among African American adult smokers . JAMA Oncol 2019 ; 5 : 1318 – 1324 . 10.1001/jamaoncol.2019.1402 31246249 55. Pasquinelli MM , Tammemägi MC , Kovitz KL , Risk prediction model
Zhong Ye, Chun Wang, Limin Guo, Juan P. Palazzo, Zhixing Han, Yinzhi Lai, Jing Jiang, James A. Posey, Atrayee Basu Mallick, Bingshan Li, Li Jiang, and Hushan Yang
. Predictors of adverse smoking outcomes in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial . J Natl Cancer Inst 2012 ; 104 : 1647 – 1659 . 22. Boursi B Mamtani R Hwang WT . A risk prediction model for sporadic CRC based on
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