d8705ad25ce9b1caea0522897f2e329d 329543.pdf 5819a54c50fddeab9aafda46a7c11acb98eaf8b1 329543.pdf 1b36ff607905d687e7706c4e82148d6fbf023aa41acfbdb9f6fadbf164cdc110 329543.pdf Title: A randomized study of 2 risk assessment models for individualized breast cancer risk estimation Subject: Doi: 10.1093/jnci/djaf067 JNCI: Journal of the National Cancer Institute, 00, 00, 2025 Publication Date: 01/04/2025 Abstract Background Estimating breast cancer risk involves quantifying genetic and non-genetic factors. This supports health interventions and risk communication to ensure adherence to screening recommendations. This study evaluated the change in risk estimation when incorporating breast density and polygenic risk score (PRS) into the baseline cancer risk assessment and compared the efficacy of 2 risk-assessment delivery models.Methods This 2-step study included 663 healthy women with a family history of breast cancer in which no pathogenic variants were identified. First, breast density and PRS were added to the baseline risk assessment for all participants. A randomized intervention study compared 2 delivery models (in-person vs pre-recorded video) for risk assessment in women at moderate or average risk. All tests were 2-sided.Results Breast density and PRS reclassified the risk group into 33% of the participants, with only 5% reclassified as high-risk. After disclosure of their estimated multifactorial risk, 65% of women aligned their risk perception with their estimated risk, compared to 47% at baseline (P < .05). No statistically significant differences were found in the primary endpoint cancer worry, mean = 10.2 (SD = 3.1) vs 10.1 (2.7), between delivery models. In-person delivery had slightly better psychological outcomes (excluding the primary outcome) and higher satisfaction, though few participants in the video group sought in-person clarification.Conclusions Incorporating breast density and PRS into risk assessments led to substantial reclassification, with 1 in 5 women facing de-escalated surveillance. Personalized assessments improve objective perceptions alignment. A model using a pre-recorded video-based model matches in-person delivery for moderate and average-risk women and is scalable for population-level implementation. 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referenced object 'bdjaf067-B11' cannot be found ID: PDF-HUL-122 Offset: 1442489 ErrorMessage: edu.harvard.hul.ois.jhove.module.pdf.PdfInvalidException: Invalid indirect destination - referenced object 'bdjaf067-B13' cannot be found ID: PDF-HUL-122 Offset: 1442489 ErrorMessage: edu.harvard.hul.ois.jhove.module.pdf.PdfInvalidException: Invalid indirect destination - referenced object 'bdjaf067-B37' cannot be found ID: PDF-HUL-122 Offset: 1442489 MIMEtype: application/pdf Profile: Tagged PDF PDFMetadata: Objects: 1279 FreeObjects: 1 IncrementalUpdates: 2 DocumentCatalog: ViewerPreferences: HideToolbar: false HideMenubar: false HideWindowUI: false FitWindow: false CenterWindow: false DisplayDocTitle: true NonFullScreenPageMode: UseNone Direction: L2R ViewArea: CropBox ViewClip: CropBox PrintArea: CropBox PageClip: CropBox PageLayout: OneColumn PageMode: UseOutlines Language: en Outlines: Item: Title: Active Content List Destination: mkchap_artid Children: Item: Title: Introduction Destination: mkchap5__sec Item: Title: Methods Destination: mkchap6__sec Item: Title: Results Destination: mkchap15__sec Item: Title: Discussion Destination: mkchap20__sec Item: Title: Conclusions Destination: mkchap21__sec Item: Title: Acknowledgments Destination: mkchap22_ack1_ack Item: Title: Author contributions Destination: mkchap22__sec Item: Title: Supplementary material Destination: mkchap23__sec Item: Title: Funding Destination: mkchap24__sec Item: Title: Conflicts of interest Destination: mkchap25__sec Item: Title: Data availability Destination: mkchap26__sec Item: Title: References Destination: mkchap27_ref1_ref-list Info: Title: A randomized study of 2 risk assessment models for individualized breast cancer risk estimation Subject: Doi: 10.1093/jnci/djaf067 JNCI: Journal of the National Cancer Institute, 00, 00, 2025 Publication Date: 01/04/2025 Abstract Background Estimating breast cancer risk involves quantifying genetic and non-genetic factors. This supports health interventions and risk communication to ensure adherence to screening recommendations. This study evaluated the change in risk estimation when incorporating breast density and polygenic risk score (PRS) into the baseline cancer risk assessment and compared the efficacy of 2 risk-assessment delivery models.Methods This 2-step study included 663 healthy women with a family history of breast cancer in which no pathogenic variants were identified. First, breast density and PRS were added to the baseline risk assessment for all participants. A randomized intervention study compared 2 delivery models (in-person vs pre-recorded video) for risk assessment in women at moderate or average risk. All tests were 2-sided.Results Breast density and PRS reclassified the risk group into 33% of the participants, with only 5% reclassified as high-risk. After disclosure of their estimated multifactorial risk, 65% of women aligned their risk perception with their estimated risk, compared to 47% at baseline (P < .05). No statistically significant differences were found in the primary endpoint cancer worry, mean = 10.2 (SD = 3.1) vs 10.1 (2.7), between delivery models. In-person delivery had slightly better psychological outcomes (excluding the primary outcome) and higher satisfaction, though few participants in the video group sought in-person clarification.Conclusions Incorporating breast density and PRS into risk assessments led to substantial reclassification, with 1 in 5 women facing de-escalated surveillance. Personalized assessments improve objective perceptions alignment. A model using a pre-recorded video-based model matches in-person delivery for moderate and average-risk women and is scalable for population-level implementation. 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Differences: true ToUnicode: true XMP: uuid:36b91a05-1cdd-2dff-74d2-ebe21839d3f6 uuid:C1CDF9BC-A51A-3C22-6B95-A6055CCBE6C3 2025-07-21T11:30:12+05:30 2025-07-21T11:30:17+05:30 Servigistics Arbortext Advanced Print Publisher 11.1.4667/W 2025-07-21T11:30:17+05:30 PDFlib+PDI 9.0.7p3 (C++/Win32) A randomized study of 2 risk assessment models for individualized breast cancer risk estimation Adrià López-Fernández Laura Duran-Lozano Guillermo Villacampa Mónica Pardo Eduard Pérez Esther Darder Anna Vallmajó Rosa Alfonso Mara Cruellas Ariadna Roqué Mireia Cartró Adriana Bareas Estela Carrasco Alejandra Rezqallah Ana Raquel Jimenez-Macedo Sara Torres-Esquius Maite Torres Consol Lopez Martín Espinosa Alex Teulé Elisabet Munté Noemi Tuset Orland Diez Lidia Feliubadaló Conxi Lázaro Gemma Llort Tim Carver Lorenzo Ficorella Nasim Mavaddat Anna Mercadé Antonis C Antoniou Joan Brunet Teresa Ramon y Cajal Judith Balmaña Doi: 10.1093/jnci/djaf067 JNCI: Journal of the National Cancer Institute, 00, 00, 2025 Publication Date: 01/04/2025 Abstract Background Estimating breast cancer risk involves quantifying genetic and non-genetic factors. This supports health interventions and risk communication to ensure adherence to screening recommendations. This study evaluated the change in risk estimation when incorporating breast density and polygenic risk score (PRS) into the baseline cancer risk assessment and compared the efficacy of 2 risk-assessment delivery models.Methods This 2-step study included 663 healthy women with a family history of breast cancer in which no pathogenic variants were identified. First, breast density and PRS were added to the baseline risk assessment for all participants. A randomized intervention study compared 2 delivery models (in-person vs pre-recorded video) for risk assessment in women at moderate or average risk. All tests were 2-sided.Results Breast density and PRS reclassified the risk group into 33% of the participants, with only 5% reclassified as high-risk. After disclosure of their estimated multifactorial risk, 65% of women aligned their risk perception with their estimated risk, compared to 47% at baseline (P < .05). No statistically significant differences were found in the primary endpoint cancer worry, mean = 10.2 (SD = 3.1) vs 10.1 (2.7), between delivery models. In-person delivery had slightly better psychological outcomes (excluding the primary outcome) and higher satisfaction, though few participants in the video group sought in-person clarification.Conclusions Incorporating breast density and PRS into risk assessments led to substantial reclassification, with 1 in 5 women facing de-escalated surveillance. Personalized assessments improve objective perceptions alignment. A model using a pre-recorded video-based model matches in-person delivery for moderate and average-risk women and is scalable for population-level implementation. © The Author(s) 2025. 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