López-Fernández Adrià, Duran-Lozano Laura, Villacampa Guillermo, Pardo Mónica, Pérez Eduard, Darder Esther, Vallmajó Anna, Alfonso Rosa, Cruellas Mara, Roqué Ariadna, Cartró Mireia, Bareas Adriana, Carrasco Estela, Rezqallah Alejandra, Jimenez-Macedo Ana Raquel, Torres-Esquius Sara, Torres Maite, Lopez Consol, Espinosa Martín, Teulé Alex, Munté Elisabet, Tuset Noemi, Diez Orland, Feliubadaló Lidia, Lázaro Conxi, Llort Gemma, Carver Tim, Ficorella Lorenzo, Mavaddat Nasim, Mercadé Anna, Antoniou Antonis C, Brunet Joan, Ramon Y Cajal Teresa, Balmaña Judith
Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain.
Medical Oncology Department, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain.
J Natl Cancer Inst. 2025 Aug 1;117(8):1593-1604. doi: 10.1093/jnci/djaf067.
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.
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.
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.
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.
评估乳腺癌风险涉及对遗传和非遗传因素进行量化。这有助于健康干预和风险沟通，以确保遵循筛查建议。本研究评估了将乳腺密度和多基因风险评分（PRS）纳入基线癌症风险评估时风险估计的变化，并比较了两种风险评估交付模式的效果。
这项分两步进行的研究纳入了663名有乳腺癌家族史但未发现致病变异的健康女性。首先，将乳腺密度和PRS添加到所有参与者的基线风险评估中。一项随机干预研究比较了两种针对中度或平均风险女性的风险评估交付模式（面对面与预录制视频）。所有检验均为双侧检验。
乳腺密度和PRS使33%的参与者的风险组重新分类，只有5%被重新分类为高风险。在披露其估计的多因素风险后，65%的女性将其风险认知与估计风险保持一致，而基线时这一比例为47%（P < 0.05）。在主要终点癌症担忧方面，两种交付模式之间未发现统计学显著差异，面对面交付的平均评分为10.2（标准差 = 3.1），视频交付的平均评分为10.1（2.7）。面对面交付在心理结果（不包括主要结果）方面略好，满意度更高，尽管视频组中很少有参与者寻求面对面的澄清。
将乳腺密度和PRS纳入风险评估导致了大量的重新分类，五分之一的女性面临监测降级。个性化评估改善了客观认知的一致性。一种基于预录制视频的模式与针对中度和平均风险女性的面对面交付效果相当，并且可扩展用于人群水平的实施。
